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circle{fill:var(--md-mermaid-label-bg-color)}.actor{fill:var(--md-mermaid-sequence-actor-bg-color);stroke:var(--md-mermaid-sequence-actor-border-color)}text.actor>tspan{fill:var(--md-mermaid-sequence-actor-fg-color);font-family:var(--md-mermaid-font-family)}line{stroke:var(--md-mermaid-sequence-actor-line-color)}.actor-man circle,.actor-man line{fill:var(--md-mermaid-sequence-actorman-bg-color);stroke:var(--md-mermaid-sequence-actorman-line-color)}.messageLine0,.messageLine1{stroke:var(--md-mermaid-sequence-message-line-color)}.note{fill:var(--md-mermaid-sequence-note-bg-color);stroke:var(--md-mermaid-sequence-note-border-color)}.loopText,.loopText>tspan,.messageText,.noteText>tspan{stroke:none;font-family:var(--md-mermaid-font-family)!important}.messageText{fill:var(--md-mermaid-sequence-message-fg-color)}.loopText,.loopText>tspan{fill:var(--md-mermaid-sequence-loop-fg-color)}.noteText>tspan{fill:var(--md-mermaid-sequence-note-fg-color)}#arrowhead 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I(...e).pipe(oe(o=>d(o,"change").pipe(m(()=>o))),Q(e[r]),m(o=>({index:e.indexOf(o),color:{media:o.getAttribute("data-md-color-media"),scheme:o.getAttribute("data-md-color-scheme"),primary:o.getAttribute("data-md-color-primary"),accent:o.getAttribute("data-md-color-accent")}})),G(1))}function Kn(e){let t=$("input",e),r=x("meta",{name:"theme-color"});document.head.appendChild(r);let o=x("meta",{name:"color-scheme"});document.head.appendChild(o);let n=$t("(prefers-color-scheme: light)");return C(()=>{let i=new g;return i.subscribe(a=>{if(document.body.setAttribute("data-md-color-switching",""),a.color.media==="(prefers-color-scheme)"){let s=matchMedia("(prefers-color-scheme: light)"),p=document.querySelector(s.matches?"[data-md-color-media='(prefers-color-scheme: light)']":"[data-md-color-media='(prefers-color-scheme: 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Gr=Vt(Yr());function Ga(e){e.setAttribute("data-md-copying","");let t=e.closest("[data-copy]"),r=t?t.getAttribute("data-copy"):e.innerText;return e.removeAttribute("data-md-copying"),r.trimEnd()}function Bn({alert$:e}){Gr.default.isSupported()&&new F(t=>{new Gr.default("[data-clipboard-target], [data-clipboard-text]",{text:r=>r.getAttribute("data-clipboard-text")||Ga(P(r.getAttribute("data-clipboard-target")))}).on("success",r=>t.next(r))}).pipe(E(t=>{t.trigger.focus()}),m(()=>Ee("clipboard.copied"))).subscribe(e)}function Gn(e,t){return e.protocol=t.protocol,e.hostname=t.hostname,e}function Ja(e,t){let r=new Map;for(let o of $("url",e)){let n=P("loc",o),i=[Gn(new URL(n.textContent),t)];r.set(`${i[0]}`,i);for(let a of $("[rel=alternate]",o)){let s=a.getAttribute("href");s!=null&&i.push(Gn(new URL(s),t))}}return r}function ur(e){return mn(new URL("sitemap.xml",e)).pipe(m(t=>Ja(t,new URL(e))),ve(()=>I(new Map)))}function Xa(e,t){if(!(e.target instanceof Element))return O;let 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g,o=r.pipe(X(),ne(!0));z([t.pipe(Ae(It)),r],(i,a)=>a).pipe(Z("value")).subscribe(({value:i})=>t.next({type:2,data:i})),r.pipe(Z("focus")).subscribe(({focus:i})=>{i&&Je("search",i)}),d(e.form,"reset").pipe(U(o)).subscribe(()=>e.focus());let n=P("header [for=__search]");return d(n,"click").subscribe(()=>e.focus()),ns(e,{worker$:t}).pipe(E(i=>r.next(i)),L(()=>r.complete()),m(i=>R({ref:e},i)),G(1))}function si(e,{worker$:t,query$:r}){let o=new g,n=tn(e.parentElement).pipe(b(Boolean)),i=e.parentElement,a=P(":scope > :first-child",e),s=P(":scope > :last-child",e);Ve("search").subscribe(l=>s.setAttribute("role",l?"list":"presentation")),o.pipe(ee(r),Ur(t.pipe(Ae(It)))).subscribe(([{items:l},{value:f}])=>{switch(l.length){case 0:a.textContent=f.length?Ee("search.result.none"):Ee("search.result.placeholder");break;case 1:a.textContent=Ee("search.result.one");break;default:let u=sr(l.length);a.textContent=Ee("search.result.other",u)}});let p=o.pipe(E(()=>s.innerHTML=""),v(({items:l})=>S(I(...l.slice(0,10)),I(...l.slice(10)).pipe(Ye(4),Vr(n),v(([f])=>f)))),m(Tn),pe());return p.subscribe(l=>s.appendChild(l)),p.pipe(oe(l=>{let f=fe("details",l);return typeof f=="undefined"?O:d(f,"toggle").pipe(U(o),m(()=>f))})).subscribe(l=>{l.open===!1&&l.offsetTop<=i.scrollTop&&i.scrollTo({top:l.offsetTop})}),t.pipe(b(dr),m(({data:l})=>l)).pipe(E(l=>o.next(l)),L(()=>o.complete()),m(l=>R({ref:e},l)))}function is(e,{query$:t}){return t.pipe(m(({value:r})=>{let o=xe();return o.hash="",r=r.replace(/\s+/g,"+").replace(/&/g,"%26").replace(/=/g,"%3D"),o.search=`q=${r}`,{url:o}}))}function ci(e,t){let r=new g,o=r.pipe(X(),ne(!0));return r.subscribe(({url:n})=>{e.setAttribute("data-clipboard-text",e.href),e.href=`${n}`}),d(e,"click").pipe(U(o)).subscribe(n=>n.preventDefault()),is(e,t).pipe(E(n=>r.next(n)),L(()=>r.complete()),m(n=>R({ref:e},n)))}function pi(e,{worker$:t,keyboard$:r}){let o=new g,n=Se("search-query"),i=S(d(n,"keydown"),d(n,"focus")).pipe(be(se),m(()=>n.value),K());return o.pipe(We(i),m(([{suggest:s},p])=>{let c=p.split(/([\s-]+)/);if(s!=null&&s.length&&c[c.length-1]){let l=s[s.length-1];l.startsWith(c[c.length-1])&&(c[c.length-1]=l)}else c.length=0;return c})).subscribe(s=>e.innerHTML=s.join("").replace(/\s/g," ")),r.pipe(b(({mode:s})=>s==="search")).subscribe(s=>{switch(s.type){case"ArrowRight":e.innerText.length&&n.selectionStart===n.value.length&&(n.value=e.innerText);break}}),t.pipe(b(dr),m(({data:s})=>s)).pipe(E(s=>o.next(s)),L(()=>o.complete()),m(()=>({ref:e})))}function li(e,{index$:t,keyboard$:r}){let o=ye();try{let n=ni(o.search,t),i=Se("search-query",e),a=Se("search-result",e);d(e,"click").pipe(b(({target:p})=>p instanceof Element&&!!p.closest("a"))).subscribe(()=>Je("search",!1)),r.pipe(b(({mode:p})=>p==="search")).subscribe(p=>{let c=Re();switch(p.type){case"Enter":if(c===i){let l=new Map;for(let f of $(":first-child [href]",a)){let 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z([t,r.pipe(Q(xe()),b(o=>!!o.searchParams.get("h")))]).pipe(m(([o,n])=>oi(o.config)(n.searchParams.get("h"))),m(o=>{var a;let n=new Map,i=document.createNodeIterator(e,NodeFilter.SHOW_TEXT);for(let s=i.nextNode();s;s=i.nextNode())if((a=s.parentElement)!=null&&a.offsetHeight){let p=s.textContent,c=o(p);c.length>p.length&&n.set(s,c)}for(let[s,p]of n){let{childNodes:c}=x("span",null,p);s.replaceWith(...Array.from(c))}return{ref:e,nodes:n}}))}function as(e,{viewport$:t,main$:r}){let o=e.closest(".md-grid"),n=o.offsetTop-o.parentElement.offsetTop;return z([r,t]).pipe(m(([{offset:i,height:a},{offset:{y:s}}])=>(a=a+Math.min(n,Math.max(0,s-i))-n,{height:a,locked:s>=i+n})),K((i,a)=>i.height===a.height&&i.locked===a.locked))}function Jr(e,o){var n=o,{header$:t}=n,r=io(n,["header$"]);let i=P(".md-sidebar__scrollwrap",e),{y:a}=Ue(i);return C(()=>{let s=new g,p=s.pipe(X(),ne(!0)),c=s.pipe(Le(0,me));return c.pipe(ee(t)).subscribe({next([{height:l},{height:f}]){i.style.height=`${l-2*a}px`,e.style.top=`${f}px`},complete(){i.style.height="",e.style.top=""}}),c.pipe(Ae()).subscribe(()=>{for(let l of $(".md-nav__link--active[href]",e)){if(!l.clientHeight)continue;let f=l.closest(".md-sidebar__scrollwrap");if(typeof f!="undefined"){let u=l.offsetTop-f.offsetTop,{height:h}=ce(f);f.scrollTo({top:u-h/2})}}}),ue($("label[tabindex]",e)).pipe(oe(l=>d(l,"click").pipe(be(se),m(()=>l),U(p)))).subscribe(l=>{let f=P(`[id="${l.htmlFor}"]`);P(`[aria-labelledby="${l.id}"]`).setAttribute("aria-expanded",`${f.checked}`)}),as(e,r).pipe(E(l=>s.next(l)),L(()=>s.complete()),m(l=>R({ref:e},l)))})}function fi(e,t){if(typeof t!="undefined"){let r=`https://api.github.com/repos/${e}/${t}`;return Ct(Ne(`${r}/releases/latest`).pipe(ve(()=>O),m(o=>({version:o.tag_name})),Be({})),Ne(r).pipe(ve(()=>O),m(o=>({stars:o.stargazers_count,forks:o.forks_count})),Be({}))).pipe(m(([o,n])=>R(R({},o),n)))}else{let r=`https://api.github.com/users/${e}`;return Ne(r).pipe(m(o=>({repositories:o.public_repos})),Be({}))}}function ui(e,t){let r=`https://${e}/api/v4/projects/${encodeURIComponent(t)}`;return Ne(r).pipe(ve(()=>O),m(({star_count:o,forks_count:n})=>({stars:o,forks:n})),Be({}))}function di(e){let t=e.match(/^.+github\.com\/([^/]+)\/?([^/]+)?/i);if(t){let[,r,o]=t;return fi(r,o)}if(t=e.match(/^.+?([^/]*gitlab[^/]+)\/(.+?)\/?$/i),t){let[,r,o]=t;return ui(r,o)}return O}var ss;function cs(e){return ss||(ss=C(()=>{let t=__md_get("__source",sessionStorage);if(t)return I(t);if(ae("consent").length){let o=__md_get("__consent");if(!(o&&o.github))return O}return di(e.href).pipe(E(o=>__md_set("__source",o,sessionStorage)))}).pipe(ve(()=>O),b(t=>Object.keys(t).length>0),m(t=>({facts:t})),G(1)))}function hi(e){let t=P(":scope > :last-child",e);return C(()=>{let r=new g;return 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n.title=o,B("content.tooltips")?lt(n,{viewport$:t}).pipe(U(e.pipe(Ce(1))),L(()=>n.removeAttribute("title"))):O})).subscribe(),B("content.tooltips")&&e.pipe(v(()=>$(".md-status")),oe(r=>lt(r,{viewport$:t}))).subscribe()}function yi({document$:e,tablet$:t}){e.pipe(v(()=>$(".md-toggle--indeterminate")),E(r=>{r.indeterminate=!0,r.checked=!1}),oe(r=>d(r,"change").pipe(Dr(()=>r.classList.contains("md-toggle--indeterminate")),m(()=>r))),ee(t)).subscribe(([r,o])=>{r.classList.remove("md-toggle--indeterminate"),o&&(r.checked=!1)})}function fs(){return/(iPad|iPhone|iPod)/.test(navigator.userAgent)}function Ei({document$:e}){e.pipe(v(()=>$("[data-md-scrollfix]")),E(t=>t.removeAttribute("data-md-scrollfix")),b(fs),oe(t=>d(t,"touchstart").pipe(m(()=>t)))).subscribe(t=>{let r=t.scrollTop;r===0?t.scrollTop=1:r+t.offsetHeight===t.scrollHeight&&(t.scrollTop=r-1)})}function 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o=="string"?o=document.createTextNode(o):o.parentNode&&o.parentNode.removeChild(o),r?t.insertBefore(this.previousSibling,o):t.replaceChild(o,this)}}}));function us(){return location.protocol==="file:"?wt(`${new URL("search/search_index.js",Xr.base)}`).pipe(m(()=>__index),G(1)):Ne(new URL("search/search_index.json",Xr.base))}document.documentElement.classList.remove("no-js");document.documentElement.classList.add("js");var ot=Yo(),jt=nn(),Ot=cn(jt),Zr=on(),Oe=bn(),hr=$t("(min-width: 960px)"),Si=$t("(min-width: 1220px)"),Oi=pn(),Xr=ye(),Mi=document.forms.namedItem("search")?us():Ke,eo=new g;Bn({alert$:eo});var to=new g;B("navigation.instant")&&Zn({location$:jt,viewport$:Oe,progress$:to}).subscribe(ot);var Ti;((Ti=Xr.version)==null?void 0:Ti.provider)==="mike"&&ii({document$:ot});S(jt,Ot).pipe(Ge(125)).subscribe(()=>{Je("drawer",!1),Je("search",!1)});Zr.pipe(b(({mode:e})=>e==="global")).subscribe(e=>{switch(e.type){case"p":case",":let t=fe("link[rel=prev]");typeof 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rt=Nn(Se("header"),{viewport$:Oe}),Ft=ot.pipe(m(()=>Se("main")),v(e=>Qn(e,{viewport$:Oe,header$:rt})),G(1)),ds=S(...ae("consent").map(e=>xn(e,{target$:Ot})),...ae("dialog").map(e=>Dn(e,{alert$:eo})),...ae("header").map(e=>zn(e,{viewport$:Oe,header$:rt,main$:Ft})),...ae("palette").map(e=>Kn(e)),...ae("progress").map(e=>Yn(e,{progress$:to})),...ae("search").map(e=>li(e,{index$:Mi,keyboard$:Zr})),...ae("source").map(e=>hi(e))),hs=C(()=>S(...ae("announce").map(e=>gn(e)),...ae("content").map(e=>Un(e,{viewport$:Oe,target$:Ot,print$:Oi})),...ae("content").map(e=>B("search.highlight")?mi(e,{index$:Mi,location$:jt}):O),...ae("header-title").map(e=>qn(e,{viewport$:Oe,header$:rt})),...ae("sidebar").map(e=>e.getAttribute("data-md-type")==="navigation"?Nr(Si,()=>Jr(e,{viewport$:Oe,header$:rt,main$:Ft})):Nr(hr,()=>Jr(e,{viewport$:Oe,header$:rt,main$:Ft}))),...ae("tabs").map(e=>bi(e,{viewport$:Oe,header$:rt})),...ae("toc").map(e=>vi(e,{viewport$:Oe,header$:rt,main$:Ft,target$:Ot})),...ae("top").map(e=>gi(e,{viewport$:Oe,header$:rt,main$:Ft,target$:Ot})))),Li=ot.pipe(v(()=>hs),Pe(ds),G(1));Li.subscribe();window.document$=ot;window.location$=jt;window.target$=Ot;window.keyboard$=Zr;window.viewport$=Oe;window.tablet$=hr;window.screen$=Si;window.print$=Oi;window.alert$=eo;window.progress$=to;window.component$=Li;})(); 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"src/templates/assets/javascripts/components/search/_/index.ts", "src/templates/assets/javascripts/components/search/highlight/index.ts", "src/templates/assets/javascripts/components/sidebar/index.ts", "src/templates/assets/javascripts/components/source/facts/github/index.ts", "src/templates/assets/javascripts/components/source/facts/gitlab/index.ts", "src/templates/assets/javascripts/components/source/facts/_/index.ts", "src/templates/assets/javascripts/components/source/_/index.ts", "src/templates/assets/javascripts/components/tabs/index.ts", "src/templates/assets/javascripts/components/toc/index.ts", "src/templates/assets/javascripts/components/top/index.ts", "src/templates/assets/javascripts/patches/ellipsis/index.ts", "src/templates/assets/javascripts/patches/indeterminate/index.ts", "src/templates/assets/javascripts/patches/scrollfix/index.ts", "src/templates/assets/javascripts/patches/scrolllock/index.ts", "src/templates/assets/javascripts/polyfills/index.ts"], + "sourcesContent": ["(function (global, factory) {\n typeof exports === 'object' && typeof module !== 'undefined' ? factory() :\n typeof define === 'function' && define.amd ? define(factory) :\n (factory());\n}(this, (function () { 'use strict';\n\n /**\n * Applies the :focus-visible polyfill at the given scope.\n * A scope in this case is either the top-level Document or a Shadow Root.\n *\n * @param {(Document|ShadowRoot)} scope\n * @see https://github.com/WICG/focus-visible\n */\n function applyFocusVisiblePolyfill(scope) {\n var hadKeyboardEvent = true;\n var hadFocusVisibleRecently = false;\n var hadFocusVisibleRecentlyTimeout = null;\n\n var inputTypesAllowlist = {\n text: true,\n search: true,\n url: true,\n tel: true,\n email: true,\n password: true,\n number: true,\n date: true,\n month: true,\n week: true,\n time: true,\n datetime: true,\n 'datetime-local': true\n };\n\n /**\n * Helper function for legacy browsers and iframes which sometimes focus\n * elements like document, body, and non-interactive SVG.\n * @param {Element} el\n */\n function isValidFocusTarget(el) {\n if (\n el &&\n el !== document &&\n el.nodeName !== 'HTML' &&\n el.nodeName !== 'BODY' &&\n 'classList' in el &&\n 'contains' in el.classList\n ) {\n return true;\n }\n return false;\n }\n\n /**\n * Computes whether the given element should automatically trigger the\n * `focus-visible` class being added, i.e. whether it should always match\n * `:focus-visible` when focused.\n * @param {Element} el\n * @return {boolean}\n */\n function focusTriggersKeyboardModality(el) {\n var type = el.type;\n var tagName = el.tagName;\n\n if (tagName === 'INPUT' && inputTypesAllowlist[type] && !el.readOnly) {\n return true;\n }\n\n if (tagName === 'TEXTAREA' && !el.readOnly) {\n return true;\n }\n\n if (el.isContentEditable) {\n return true;\n }\n\n return false;\n }\n\n /**\n * Add the `focus-visible` class to the given element if it was not added by\n * the author.\n * @param {Element} el\n */\n function addFocusVisibleClass(el) {\n if (el.classList.contains('focus-visible')) {\n return;\n }\n el.classList.add('focus-visible');\n el.setAttribute('data-focus-visible-added', '');\n }\n\n /**\n * Remove the `focus-visible` class from the given element if it was not\n * originally added by the author.\n * @param {Element} el\n */\n function removeFocusVisibleClass(el) {\n if (!el.hasAttribute('data-focus-visible-added')) {\n return;\n }\n el.classList.remove('focus-visible');\n el.removeAttribute('data-focus-visible-added');\n }\n\n /**\n * If the most recent user interaction was via the keyboard;\n * and the key press did not include a meta, alt/option, or control key;\n * then the modality is keyboard. Otherwise, the modality is not keyboard.\n * Apply `focus-visible` to any current active element and keep track\n * of our keyboard modality state with `hadKeyboardEvent`.\n * @param {KeyboardEvent} e\n */\n function onKeyDown(e) {\n if (e.metaKey || e.altKey || e.ctrlKey) {\n return;\n }\n\n if (isValidFocusTarget(scope.activeElement)) {\n addFocusVisibleClass(scope.activeElement);\n }\n\n hadKeyboardEvent = true;\n }\n\n /**\n * If at any point a user clicks with a pointing device, ensure that we change\n * the modality away from keyboard.\n * This avoids the situation where a user presses a key on an already focused\n * element, and then clicks on a different element, focusing it with a\n * pointing device, while we still think we're in keyboard modality.\n * @param {Event} e\n */\n function onPointerDown(e) {\n hadKeyboardEvent = false;\n }\n\n /**\n * On `focus`, add the `focus-visible` class to the target if:\n * - the target received focus as a result of keyboard navigation, or\n * - the event target is an element that will likely require interaction\n * via the keyboard (e.g. a text box)\n * @param {Event} e\n */\n function onFocus(e) {\n // Prevent IE from focusing the document or HTML element.\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (hadKeyboardEvent || focusTriggersKeyboardModality(e.target)) {\n addFocusVisibleClass(e.target);\n }\n }\n\n /**\n * On `blur`, remove the `focus-visible` class from the target.\n * @param {Event} e\n */\n function onBlur(e) {\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (\n e.target.classList.contains('focus-visible') ||\n e.target.hasAttribute('data-focus-visible-added')\n ) {\n // To detect a tab/window switch, we look for a blur event followed\n // rapidly by a visibility change.\n // If we don't see a visibility change within 100ms, it's probably a\n // regular focus change.\n hadFocusVisibleRecently = true;\n window.clearTimeout(hadFocusVisibleRecentlyTimeout);\n hadFocusVisibleRecentlyTimeout = window.setTimeout(function() {\n hadFocusVisibleRecently = false;\n }, 100);\n removeFocusVisibleClass(e.target);\n }\n }\n\n /**\n * If the user changes tabs, keep track of whether or not the previously\n * focused element had .focus-visible.\n * @param {Event} e\n */\n function onVisibilityChange(e) {\n if (document.visibilityState === 'hidden') {\n // If the tab becomes active again, the browser will handle calling focus\n // on the element (Safari actually calls it twice).\n // If this tab change caused a blur on an element with focus-visible,\n // re-apply the class when the user switches back to the tab.\n if (hadFocusVisibleRecently) {\n hadKeyboardEvent = true;\n }\n addInitialPointerMoveListeners();\n }\n }\n\n /**\n * Add a group of listeners to detect usage of any pointing devices.\n * These listeners will be added when the polyfill first loads, and anytime\n * the window is blurred, so that they are active when the window regains\n * focus.\n */\n function addInitialPointerMoveListeners() {\n document.addEventListener('mousemove', onInitialPointerMove);\n document.addEventListener('mousedown', onInitialPointerMove);\n document.addEventListener('mouseup', onInitialPointerMove);\n document.addEventListener('pointermove', onInitialPointerMove);\n document.addEventListener('pointerdown', onInitialPointerMove);\n document.addEventListener('pointerup', onInitialPointerMove);\n document.addEventListener('touchmove', onInitialPointerMove);\n document.addEventListener('touchstart', onInitialPointerMove);\n document.addEventListener('touchend', onInitialPointerMove);\n }\n\n function removeInitialPointerMoveListeners() {\n document.removeEventListener('mousemove', onInitialPointerMove);\n document.removeEventListener('mousedown', onInitialPointerMove);\n document.removeEventListener('mouseup', onInitialPointerMove);\n document.removeEventListener('pointermove', onInitialPointerMove);\n document.removeEventListener('pointerdown', onInitialPointerMove);\n document.removeEventListener('pointerup', onInitialPointerMove);\n document.removeEventListener('touchmove', onInitialPointerMove);\n document.removeEventListener('touchstart', onInitialPointerMove);\n document.removeEventListener('touchend', onInitialPointerMove);\n }\n\n /**\n * When the polfyill first loads, assume the user is in keyboard modality.\n * If any event is received from a pointing device (e.g. mouse, pointer,\n * touch), turn off keyboard modality.\n * This accounts for situations where focus enters the page from the URL bar.\n * @param {Event} e\n */\n function onInitialPointerMove(e) {\n // Work around a Safari quirk that fires a mousemove on whenever the\n // window blurs, even if you're tabbing out of the page. \u00AF\\_(\u30C4)_/\u00AF\n if (e.target.nodeName && e.target.nodeName.toLowerCase() === 'html') {\n return;\n }\n\n hadKeyboardEvent = false;\n removeInitialPointerMoveListeners();\n }\n\n // For some kinds of state, we are interested in changes at the global scope\n // only. For example, global pointer input, global key presses and global\n // visibility change should affect the state at every scope:\n document.addEventListener('keydown', onKeyDown, true);\n document.addEventListener('mousedown', onPointerDown, true);\n document.addEventListener('pointerdown', onPointerDown, true);\n document.addEventListener('touchstart', onPointerDown, true);\n document.addEventListener('visibilitychange', onVisibilityChange, true);\n\n addInitialPointerMoveListeners();\n\n // For focus and blur, we specifically care about state changes in the local\n // scope. This is because focus / blur events that originate from within a\n // shadow root are not re-dispatched from the host element if it was already\n // the active element in its own scope:\n scope.addEventListener('focus', onFocus, true);\n scope.addEventListener('blur', onBlur, true);\n\n // We detect that a node is a ShadowRoot by ensuring that it is a\n // DocumentFragment and also has a host property. This check covers native\n // implementation and polyfill implementation transparently. If we only cared\n // about the native implementation, we could just check if the scope was\n // an instance of a ShadowRoot.\n if (scope.nodeType === Node.DOCUMENT_FRAGMENT_NODE && scope.host) {\n // Since a ShadowRoot is a special kind of DocumentFragment, it does not\n // have a root element to add a class to. So, we add this attribute to the\n // host element instead:\n scope.host.setAttribute('data-js-focus-visible', '');\n } else if (scope.nodeType === Node.DOCUMENT_NODE) {\n document.documentElement.classList.add('js-focus-visible');\n document.documentElement.setAttribute('data-js-focus-visible', '');\n }\n }\n\n // It is important to wrap all references to global window and document in\n // these checks to support server-side rendering use cases\n // @see https://github.com/WICG/focus-visible/issues/199\n if (typeof window !== 'undefined' && typeof document !== 'undefined') {\n // Make the polyfill helper globally available. This can be used as a signal\n // to interested libraries that wish to coordinate with the polyfill for e.g.,\n // applying the polyfill to a shadow root:\n window.applyFocusVisiblePolyfill = applyFocusVisiblePolyfill;\n\n // Notify interested libraries of the polyfill's presence, in case the\n // polyfill was loaded lazily:\n var event;\n\n try {\n event = new CustomEvent('focus-visible-polyfill-ready');\n } catch (error) {\n // IE11 does not support using CustomEvent as a constructor directly:\n event = document.createEvent('CustomEvent');\n event.initCustomEvent('focus-visible-polyfill-ready', false, false, {});\n }\n\n window.dispatchEvent(event);\n }\n\n if (typeof document !== 'undefined') {\n // Apply the polyfill to the global document, so that no JavaScript\n // coordination is required to use the polyfill in the top-level document:\n applyFocusVisiblePolyfill(document);\n }\n\n})));\n", "/*!\n * clipboard.js v2.0.11\n * https://clipboardjs.com/\n *\n * Licensed MIT \u00A9 Zeno Rocha\n */\n(function webpackUniversalModuleDefinition(root, factory) {\n\tif(typeof exports === 'object' && typeof module === 'object')\n\t\tmodule.exports = factory();\n\telse if(typeof define === 'function' && define.amd)\n\t\tdefine([], factory);\n\telse if(typeof exports === 'object')\n\t\texports[\"ClipboardJS\"] = factory();\n\telse\n\t\troot[\"ClipboardJS\"] = factory();\n})(this, function() {\nreturn /******/ (function() { // webpackBootstrap\n/******/ \tvar __webpack_modules__ = ({\n\n/***/ 686:\n/***/ (function(__unused_webpack_module, __webpack_exports__, __webpack_require__) {\n\n\"use strict\";\n\n// EXPORTS\n__webpack_require__.d(__webpack_exports__, {\n \"default\": function() { return /* binding */ clipboard; }\n});\n\n// EXTERNAL MODULE: ./node_modules/tiny-emitter/index.js\nvar tiny_emitter = __webpack_require__(279);\nvar tiny_emitter_default = /*#__PURE__*/__webpack_require__.n(tiny_emitter);\n// EXTERNAL MODULE: ./node_modules/good-listener/src/listen.js\nvar listen = __webpack_require__(370);\nvar listen_default = /*#__PURE__*/__webpack_require__.n(listen);\n// EXTERNAL MODULE: ./node_modules/select/src/select.js\nvar src_select = __webpack_require__(817);\nvar select_default = /*#__PURE__*/__webpack_require__.n(src_select);\n;// CONCATENATED MODULE: ./src/common/command.js\n/**\n * Executes a given operation type.\n * @param {String} type\n * @return {Boolean}\n */\nfunction command(type) {\n try {\n return document.execCommand(type);\n } catch (err) {\n return false;\n }\n}\n;// CONCATENATED MODULE: ./src/actions/cut.js\n\n\n/**\n * Cut action wrapper.\n * @param {String|HTMLElement} target\n * @return {String}\n */\n\nvar ClipboardActionCut = function ClipboardActionCut(target) {\n var selectedText = select_default()(target);\n command('cut');\n return selectedText;\n};\n\n/* harmony default export */ var actions_cut = (ClipboardActionCut);\n;// CONCATENATED MODULE: ./src/common/create-fake-element.js\n/**\n * Creates a fake textarea element with a value.\n * @param {String} value\n * @return {HTMLElement}\n */\nfunction createFakeElement(value) {\n var isRTL = document.documentElement.getAttribute('dir') === 'rtl';\n var fakeElement = document.createElement('textarea'); // Prevent zooming on iOS\n\n fakeElement.style.fontSize = '12pt'; // Reset box model\n\n fakeElement.style.border = '0';\n fakeElement.style.padding = '0';\n fakeElement.style.margin = '0'; // Move element out of screen horizontally\n\n fakeElement.style.position = 'absolute';\n fakeElement.style[isRTL ? 'right' : 'left'] = '-9999px'; // Move element to the same position vertically\n\n var yPosition = window.pageYOffset || document.documentElement.scrollTop;\n fakeElement.style.top = \"\".concat(yPosition, \"px\");\n fakeElement.setAttribute('readonly', '');\n fakeElement.value = value;\n return fakeElement;\n}\n;// CONCATENATED MODULE: ./src/actions/copy.js\n\n\n\n/**\n * Create fake copy action wrapper using a fake element.\n * @param {String} target\n * @param {Object} options\n * @return {String}\n */\n\nvar fakeCopyAction = function fakeCopyAction(value, options) {\n var fakeElement = createFakeElement(value);\n options.container.appendChild(fakeElement);\n var selectedText = select_default()(fakeElement);\n command('copy');\n fakeElement.remove();\n return selectedText;\n};\n/**\n * Copy action wrapper.\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @return {String}\n */\n\n\nvar ClipboardActionCopy = function ClipboardActionCopy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n var selectedText = '';\n\n if (typeof target === 'string') {\n selectedText = fakeCopyAction(target, options);\n } else if (target instanceof HTMLInputElement && !['text', 'search', 'url', 'tel', 'password'].includes(target === null || target === void 0 ? void 0 : target.type)) {\n // If input type doesn't support `setSelectionRange`. Simulate it. https://developer.mozilla.org/en-US/docs/Web/API/HTMLInputElement/setSelectionRange\n selectedText = fakeCopyAction(target.value, options);\n } else {\n selectedText = select_default()(target);\n command('copy');\n }\n\n return selectedText;\n};\n\n/* harmony default export */ var actions_copy = (ClipboardActionCopy);\n;// CONCATENATED MODULE: ./src/actions/default.js\nfunction _typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { _typeof = function _typeof(obj) { return typeof obj; }; } else { _typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return _typeof(obj); }\n\n\n\n/**\n * Inner function which performs selection from either `text` or `target`\n * properties and then executes copy or cut operations.\n * @param {Object} options\n */\n\nvar ClipboardActionDefault = function ClipboardActionDefault() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n // Defines base properties passed from constructor.\n var _options$action = options.action,\n action = _options$action === void 0 ? 'copy' : _options$action,\n container = options.container,\n target = options.target,\n text = options.text; // Sets the `action` to be performed which can be either 'copy' or 'cut'.\n\n if (action !== 'copy' && action !== 'cut') {\n throw new Error('Invalid \"action\" value, use either \"copy\" or \"cut\"');\n } // Sets the `target` property using an element that will be have its content copied.\n\n\n if (target !== undefined) {\n if (target && _typeof(target) === 'object' && target.nodeType === 1) {\n if (action === 'copy' && target.hasAttribute('disabled')) {\n throw new Error('Invalid \"target\" attribute. Please use \"readonly\" instead of \"disabled\" attribute');\n }\n\n if (action === 'cut' && (target.hasAttribute('readonly') || target.hasAttribute('disabled'))) {\n throw new Error('Invalid \"target\" attribute. You can\\'t cut text from elements with \"readonly\" or \"disabled\" attributes');\n }\n } else {\n throw new Error('Invalid \"target\" value, use a valid Element');\n }\n } // Define selection strategy based on `text` property.\n\n\n if (text) {\n return actions_copy(text, {\n container: container\n });\n } // Defines which selection strategy based on `target` property.\n\n\n if (target) {\n return action === 'cut' ? actions_cut(target) : actions_copy(target, {\n container: container\n });\n }\n};\n\n/* harmony default export */ var actions_default = (ClipboardActionDefault);\n;// CONCATENATED MODULE: ./src/clipboard.js\nfunction clipboard_typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { clipboard_typeof = function _typeof(obj) { return typeof obj; }; } else { clipboard_typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return clipboard_typeof(obj); }\n\nfunction _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\nfunction _defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } }\n\nfunction _createClass(Constructor, protoProps, staticProps) { if (protoProps) _defineProperties(Constructor.prototype, protoProps); if (staticProps) _defineProperties(Constructor, staticProps); return Constructor; }\n\nfunction _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function\"); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, writable: true, configurable: true } }); if (superClass) _setPrototypeOf(subClass, superClass); }\n\nfunction _setPrototypeOf(o, p) { _setPrototypeOf = Object.setPrototypeOf || function _setPrototypeOf(o, p) { o.__proto__ = p; return o; }; return _setPrototypeOf(o, p); }\n\nfunction _createSuper(Derived) { var hasNativeReflectConstruct = _isNativeReflectConstruct(); return function _createSuperInternal() { var Super = _getPrototypeOf(Derived), result; if (hasNativeReflectConstruct) { var NewTarget = _getPrototypeOf(this).constructor; result = Reflect.construct(Super, arguments, NewTarget); } else { result = Super.apply(this, arguments); } return _possibleConstructorReturn(this, result); }; }\n\nfunction _possibleConstructorReturn(self, call) { if (call && (clipboard_typeof(call) === \"object\" || typeof call === \"function\")) { return call; } return _assertThisInitialized(self); }\n\nfunction _assertThisInitialized(self) { if (self === void 0) { throw new ReferenceError(\"this hasn't been initialised - super() hasn't been called\"); } return self; }\n\nfunction _isNativeReflectConstruct() { if (typeof Reflect === \"undefined\" || !Reflect.construct) return false; if (Reflect.construct.sham) return false; if (typeof Proxy === \"function\") return true; try { Date.prototype.toString.call(Reflect.construct(Date, [], function () {})); return true; } catch (e) { return false; } }\n\nfunction _getPrototypeOf(o) { _getPrototypeOf = Object.setPrototypeOf ? Object.getPrototypeOf : function _getPrototypeOf(o) { return o.__proto__ || Object.getPrototypeOf(o); }; return _getPrototypeOf(o); }\n\n\n\n\n\n\n/**\n * Helper function to retrieve attribute value.\n * @param {String} suffix\n * @param {Element} element\n */\n\nfunction getAttributeValue(suffix, element) {\n var attribute = \"data-clipboard-\".concat(suffix);\n\n if (!element.hasAttribute(attribute)) {\n return;\n }\n\n return element.getAttribute(attribute);\n}\n/**\n * Base class which takes one or more elements, adds event listeners to them,\n * and instantiates a new `ClipboardAction` on each click.\n */\n\n\nvar Clipboard = /*#__PURE__*/function (_Emitter) {\n _inherits(Clipboard, _Emitter);\n\n var _super = _createSuper(Clipboard);\n\n /**\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n * @param {Object} options\n */\n function Clipboard(trigger, options) {\n var _this;\n\n _classCallCheck(this, Clipboard);\n\n _this = _super.call(this);\n\n _this.resolveOptions(options);\n\n _this.listenClick(trigger);\n\n return _this;\n }\n /**\n * Defines if attributes would be resolved using internal setter functions\n * or custom functions that were passed in the constructor.\n * @param {Object} options\n */\n\n\n _createClass(Clipboard, [{\n key: \"resolveOptions\",\n value: function resolveOptions() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n this.action = typeof options.action === 'function' ? options.action : this.defaultAction;\n this.target = typeof options.target === 'function' ? options.target : this.defaultTarget;\n this.text = typeof options.text === 'function' ? options.text : this.defaultText;\n this.container = clipboard_typeof(options.container) === 'object' ? options.container : document.body;\n }\n /**\n * Adds a click event listener to the passed trigger.\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n */\n\n }, {\n key: \"listenClick\",\n value: function listenClick(trigger) {\n var _this2 = this;\n\n this.listener = listen_default()(trigger, 'click', function (e) {\n return _this2.onClick(e);\n });\n }\n /**\n * Defines a new `ClipboardAction` on each click event.\n * @param {Event} e\n */\n\n }, {\n key: \"onClick\",\n value: function onClick(e) {\n var trigger = e.delegateTarget || e.currentTarget;\n var action = this.action(trigger) || 'copy';\n var text = actions_default({\n action: action,\n container: this.container,\n target: this.target(trigger),\n text: this.text(trigger)\n }); // Fires an event based on the copy operation result.\n\n this.emit(text ? 'success' : 'error', {\n action: action,\n text: text,\n trigger: trigger,\n clearSelection: function clearSelection() {\n if (trigger) {\n trigger.focus();\n }\n\n window.getSelection().removeAllRanges();\n }\n });\n }\n /**\n * Default `action` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultAction\",\n value: function defaultAction(trigger) {\n return getAttributeValue('action', trigger);\n }\n /**\n * Default `target` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultTarget\",\n value: function defaultTarget(trigger) {\n var selector = getAttributeValue('target', trigger);\n\n if (selector) {\n return document.querySelector(selector);\n }\n }\n /**\n * Allow fire programmatically a copy action\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @returns Text copied.\n */\n\n }, {\n key: \"defaultText\",\n\n /**\n * Default `text` lookup function.\n * @param {Element} trigger\n */\n value: function defaultText(trigger) {\n return getAttributeValue('text', trigger);\n }\n /**\n * Destroy lifecycle.\n */\n\n }, {\n key: \"destroy\",\n value: function destroy() {\n this.listener.destroy();\n }\n }], [{\n key: \"copy\",\n value: function copy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n return actions_copy(target, options);\n }\n /**\n * Allow fire programmatically a cut action\n * @param {String|HTMLElement} target\n * @returns Text cutted.\n */\n\n }, {\n key: \"cut\",\n value: function cut(target) {\n return actions_cut(target);\n }\n /**\n * Returns the support of the given action, or all actions if no action is\n * given.\n * @param {String} [action]\n */\n\n }, {\n key: \"isSupported\",\n value: function isSupported() {\n var action = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : ['copy', 'cut'];\n var actions = typeof action === 'string' ? [action] : action;\n var support = !!document.queryCommandSupported;\n actions.forEach(function (action) {\n support = support && !!document.queryCommandSupported(action);\n });\n return support;\n }\n }]);\n\n return Clipboard;\n}((tiny_emitter_default()));\n\n/* harmony default export */ var clipboard = (Clipboard);\n\n/***/ }),\n\n/***/ 828:\n/***/ (function(module) {\n\nvar DOCUMENT_NODE_TYPE = 9;\n\n/**\n * A polyfill for Element.matches()\n */\nif (typeof Element !== 'undefined' && !Element.prototype.matches) {\n var proto = Element.prototype;\n\n proto.matches = proto.matchesSelector ||\n proto.mozMatchesSelector ||\n proto.msMatchesSelector ||\n proto.oMatchesSelector ||\n proto.webkitMatchesSelector;\n}\n\n/**\n * Finds the closest parent that matches a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @return {Function}\n */\nfunction closest (element, selector) {\n while (element && element.nodeType !== DOCUMENT_NODE_TYPE) {\n if (typeof element.matches === 'function' &&\n element.matches(selector)) {\n return element;\n }\n element = element.parentNode;\n }\n}\n\nmodule.exports = closest;\n\n\n/***/ }),\n\n/***/ 438:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar closest = __webpack_require__(828);\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction _delegate(element, selector, type, callback, useCapture) {\n var listenerFn = listener.apply(this, arguments);\n\n element.addEventListener(type, listenerFn, useCapture);\n\n return {\n destroy: function() {\n element.removeEventListener(type, listenerFn, useCapture);\n }\n }\n}\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element|String|Array} [elements]\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction delegate(elements, selector, type, callback, useCapture) {\n // Handle the regular Element usage\n if (typeof elements.addEventListener === 'function') {\n return _delegate.apply(null, arguments);\n }\n\n // Handle Element-less usage, it defaults to global delegation\n if (typeof type === 'function') {\n // Use `document` as the first parameter, then apply arguments\n // This is a short way to .unshift `arguments` without running into deoptimizations\n return _delegate.bind(null, document).apply(null, arguments);\n }\n\n // Handle Selector-based usage\n if (typeof elements === 'string') {\n elements = document.querySelectorAll(elements);\n }\n\n // Handle Array-like based usage\n return Array.prototype.map.call(elements, function (element) {\n return _delegate(element, selector, type, callback, useCapture);\n });\n}\n\n/**\n * Finds closest match and invokes callback.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Function}\n */\nfunction listener(element, selector, type, callback) {\n return function(e) {\n e.delegateTarget = closest(e.target, selector);\n\n if (e.delegateTarget) {\n callback.call(element, e);\n }\n }\n}\n\nmodule.exports = delegate;\n\n\n/***/ }),\n\n/***/ 879:\n/***/ (function(__unused_webpack_module, exports) {\n\n/**\n * Check if argument is a HTML element.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.node = function(value) {\n return value !== undefined\n && value instanceof HTMLElement\n && value.nodeType === 1;\n};\n\n/**\n * Check if argument is a list of HTML elements.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.nodeList = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return value !== undefined\n && (type === '[object NodeList]' || type === '[object HTMLCollection]')\n && ('length' in value)\n && (value.length === 0 || exports.node(value[0]));\n};\n\n/**\n * Check if argument is a string.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.string = function(value) {\n return typeof value === 'string'\n || value instanceof String;\n};\n\n/**\n * Check if argument is a function.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.fn = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return type === '[object Function]';\n};\n\n\n/***/ }),\n\n/***/ 370:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar is = __webpack_require__(879);\nvar delegate = __webpack_require__(438);\n\n/**\n * Validates all params and calls the right\n * listener function based on its target type.\n *\n * @param {String|HTMLElement|HTMLCollection|NodeList} target\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listen(target, type, callback) {\n if (!target && !type && !callback) {\n throw new Error('Missing required arguments');\n }\n\n if (!is.string(type)) {\n throw new TypeError('Second argument must be a String');\n }\n\n if (!is.fn(callback)) {\n throw new TypeError('Third argument must be a Function');\n }\n\n if (is.node(target)) {\n return listenNode(target, type, callback);\n }\n else if (is.nodeList(target)) {\n return listenNodeList(target, type, callback);\n }\n else if (is.string(target)) {\n return listenSelector(target, type, callback);\n }\n else {\n throw new TypeError('First argument must be a String, HTMLElement, HTMLCollection, or NodeList');\n }\n}\n\n/**\n * Adds an event listener to a HTML element\n * and returns a remove listener function.\n *\n * @param {HTMLElement} node\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNode(node, type, callback) {\n node.addEventListener(type, callback);\n\n return {\n destroy: function() {\n node.removeEventListener(type, callback);\n }\n }\n}\n\n/**\n * Add an event listener to a list of HTML elements\n * and returns a remove listener function.\n *\n * @param {NodeList|HTMLCollection} nodeList\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNodeList(nodeList, type, callback) {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.addEventListener(type, callback);\n });\n\n return {\n destroy: function() {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.removeEventListener(type, callback);\n });\n }\n }\n}\n\n/**\n * Add an event listener to a selector\n * and returns a remove listener function.\n *\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenSelector(selector, type, callback) {\n return delegate(document.body, selector, type, callback);\n}\n\nmodule.exports = listen;\n\n\n/***/ }),\n\n/***/ 817:\n/***/ (function(module) {\n\nfunction select(element) {\n var selectedText;\n\n if (element.nodeName === 'SELECT') {\n element.focus();\n\n selectedText = element.value;\n }\n else if (element.nodeName === 'INPUT' || element.nodeName === 'TEXTAREA') {\n var isReadOnly = element.hasAttribute('readonly');\n\n if (!isReadOnly) {\n element.setAttribute('readonly', '');\n }\n\n element.select();\n element.setSelectionRange(0, element.value.length);\n\n if (!isReadOnly) {\n element.removeAttribute('readonly');\n }\n\n selectedText = element.value;\n }\n else {\n if (element.hasAttribute('contenteditable')) {\n element.focus();\n }\n\n var selection = window.getSelection();\n var range = document.createRange();\n\n range.selectNodeContents(element);\n selection.removeAllRanges();\n selection.addRange(range);\n\n selectedText = selection.toString();\n }\n\n return selectedText;\n}\n\nmodule.exports = select;\n\n\n/***/ }),\n\n/***/ 279:\n/***/ (function(module) {\n\nfunction E () {\n // Keep this empty so it's easier to inherit from\n // (via https://github.com/lipsmack from https://github.com/scottcorgan/tiny-emitter/issues/3)\n}\n\nE.prototype = {\n on: function (name, callback, ctx) {\n var e = this.e || (this.e = {});\n\n (e[name] || (e[name] = [])).push({\n fn: callback,\n ctx: ctx\n });\n\n return this;\n },\n\n once: function (name, callback, ctx) {\n var self = this;\n function listener () {\n self.off(name, listener);\n callback.apply(ctx, arguments);\n };\n\n listener._ = callback\n return this.on(name, listener, ctx);\n },\n\n emit: function (name) {\n var data = [].slice.call(arguments, 1);\n var evtArr = ((this.e || (this.e = {}))[name] || []).slice();\n var i = 0;\n var len = evtArr.length;\n\n for (i; i < len; i++) {\n evtArr[i].fn.apply(evtArr[i].ctx, data);\n }\n\n return this;\n },\n\n off: function (name, callback) {\n var e = this.e || (this.e = {});\n var evts = e[name];\n var liveEvents = [];\n\n if (evts && callback) {\n for (var i = 0, len = evts.length; i < len; i++) {\n if (evts[i].fn !== callback && evts[i].fn._ !== callback)\n liveEvents.push(evts[i]);\n }\n }\n\n // Remove event from queue to prevent memory leak\n // Suggested by https://github.com/lazd\n // Ref: https://github.com/scottcorgan/tiny-emitter/commit/c6ebfaa9bc973b33d110a84a307742b7cf94c953#commitcomment-5024910\n\n (liveEvents.length)\n ? e[name] = liveEvents\n : delete e[name];\n\n return this;\n }\n};\n\nmodule.exports = E;\nmodule.exports.TinyEmitter = E;\n\n\n/***/ })\n\n/******/ \t});\n/************************************************************************/\n/******/ \t// The module cache\n/******/ \tvar __webpack_module_cache__ = {};\n/******/ \t\n/******/ \t// The require function\n/******/ \tfunction __webpack_require__(moduleId) {\n/******/ \t\t// Check if module is in cache\n/******/ \t\tif(__webpack_module_cache__[moduleId]) {\n/******/ \t\t\treturn __webpack_module_cache__[moduleId].exports;\n/******/ \t\t}\n/******/ \t\t// Create a new module (and put it into the cache)\n/******/ \t\tvar module = __webpack_module_cache__[moduleId] = {\n/******/ \t\t\t// no module.id needed\n/******/ \t\t\t// no module.loaded needed\n/******/ \t\t\texports: {}\n/******/ \t\t};\n/******/ \t\n/******/ \t\t// Execute the module function\n/******/ \t\t__webpack_modules__[moduleId](module, module.exports, __webpack_require__);\n/******/ \t\n/******/ \t\t// Return the exports of the module\n/******/ \t\treturn module.exports;\n/******/ \t}\n/******/ \t\n/************************************************************************/\n/******/ \t/* webpack/runtime/compat get default export */\n/******/ \t!function() {\n/******/ \t\t// getDefaultExport function for compatibility with non-harmony modules\n/******/ \t\t__webpack_require__.n = function(module) {\n/******/ \t\t\tvar getter = module && module.__esModule ?\n/******/ \t\t\t\tfunction() { return module['default']; } :\n/******/ \t\t\t\tfunction() { return module; };\n/******/ \t\t\t__webpack_require__.d(getter, { a: getter });\n/******/ \t\t\treturn getter;\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/define property getters */\n/******/ \t!function() {\n/******/ \t\t// define getter functions for harmony exports\n/******/ \t\t__webpack_require__.d = function(exports, definition) {\n/******/ \t\t\tfor(var key in definition) {\n/******/ \t\t\t\tif(__webpack_require__.o(definition, key) && !__webpack_require__.o(exports, key)) {\n/******/ \t\t\t\t\tObject.defineProperty(exports, key, { enumerable: true, get: definition[key] });\n/******/ \t\t\t\t}\n/******/ \t\t\t}\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/hasOwnProperty shorthand */\n/******/ \t!function() {\n/******/ \t\t__webpack_require__.o = function(obj, prop) { return Object.prototype.hasOwnProperty.call(obj, prop); }\n/******/ \t}();\n/******/ \t\n/************************************************************************/\n/******/ \t// module exports must be returned from runtime so entry inlining is disabled\n/******/ \t// startup\n/******/ \t// Load entry module and return exports\n/******/ \treturn __webpack_require__(686);\n/******/ })()\n.default;\n});", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n var str = '' + string;\n var match = matchHtmlRegExp.exec(str);\n\n if (!match) {\n return str;\n }\n\n var escape;\n var html = '';\n var index = 0;\n var lastIndex = 0;\n\n for (index = match.index; index < str.length; index++) {\n switch (str.charCodeAt(index)) {\n case 34: // \"\n escape = '"';\n break;\n case 38: // &\n escape = '&';\n break;\n case 39: // '\n escape = ''';\n break;\n case 60: // <\n escape = '<';\n break;\n case 62: // >\n escape = '>';\n break;\n default:\n continue;\n }\n\n if (lastIndex !== index) {\n html += str.substring(lastIndex, index);\n }\n\n lastIndex = index + 1;\n html += escape;\n }\n\n return lastIndex !== index\n ? html + str.substring(lastIndex, index)\n : html;\n}\n", "/*\n * Copyright (c) 2016-2024 Martin Donath \n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport \"focus-visible\"\n\nimport {\n EMPTY,\n NEVER,\n Observable,\n Subject,\n defer,\n delay,\n filter,\n map,\n merge,\n mergeWith,\n shareReplay,\n switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"./_\"\nimport {\n at,\n getActiveElement,\n getOptionalElement,\n requestJSON,\n setLocation,\n setToggle,\n watchDocument,\n watchKeyboard,\n watchLocation,\n watchLocationTarget,\n watchMedia,\n watchPrint,\n watchScript,\n watchViewport\n} from \"./browser\"\nimport {\n getComponentElement,\n getComponentElements,\n mountAnnounce,\n mountBackToTop,\n mountConsent,\n mountContent,\n mountDialog,\n mountHeader,\n mountHeaderTitle,\n mountPalette,\n mountProgress,\n mountSearch,\n mountSearchHiglight,\n mountSidebar,\n mountSource,\n mountTableOfContents,\n mountTabs,\n watchHeader,\n watchMain\n} from \"./components\"\nimport {\n SearchIndex,\n setupClipboardJS,\n setupInstantNavigation,\n setupVersionSelector\n} from \"./integrations\"\nimport {\n patchEllipsis,\n patchIndeterminate,\n patchScrollfix,\n patchScrolllock\n} from \"./patches\"\nimport \"./polyfills\"\n\n/* ----------------------------------------------------------------------------\n * Functions - @todo refactor\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch search index\n *\n * @returns Search index observable\n */\nfunction fetchSearchIndex(): Observable {\n if (location.protocol === \"file:\") {\n return watchScript(\n `${new URL(\"search/search_index.js\", config.base)}`\n )\n .pipe(\n // @ts-ignore - @todo fix typings\n map(() => __index),\n shareReplay(1)\n )\n } else {\n return requestJSON(\n new URL(\"search/search_index.json\", config.base)\n )\n }\n}\n\n/* ----------------------------------------------------------------------------\n * Application\n * ------------------------------------------------------------------------- */\n\n/* Yay, JavaScript is available */\ndocument.documentElement.classList.remove(\"no-js\")\ndocument.documentElement.classList.add(\"js\")\n\n/* Set up navigation observables and subjects */\nconst document$ = watchDocument()\nconst location$ = watchLocation()\nconst target$ = watchLocationTarget(location$)\nconst keyboard$ = watchKeyboard()\n\n/* Set up media observables */\nconst viewport$ = watchViewport()\nconst tablet$ = watchMedia(\"(min-width: 960px)\")\nconst screen$ = watchMedia(\"(min-width: 1220px)\")\nconst print$ = watchPrint()\n\n/* Retrieve search index, if search is enabled */\nconst config = configuration()\nconst index$ = document.forms.namedItem(\"search\")\n ? fetchSearchIndex()\n : NEVER\n\n/* Set up Clipboard.js integration */\nconst alert$ = new Subject()\nsetupClipboardJS({ alert$ })\n\n/* Set up progress indicator */\nconst progress$ = new Subject()\n\n/* Set up instant navigation, if enabled */\nif (feature(\"navigation.instant\"))\n setupInstantNavigation({ location$, viewport$, progress$ })\n .subscribe(document$)\n\n/* Set up version selector */\nif (config.version?.provider === \"mike\")\n setupVersionSelector({ document$ })\n\n/* Always close drawer and search on navigation */\nmerge(location$, target$)\n .pipe(\n delay(125)\n )\n .subscribe(() => {\n setToggle(\"drawer\", false)\n setToggle(\"search\", false)\n })\n\n/* Set up global keyboard handlers */\nkeyboard$\n .pipe(\n filter(({ mode }) => mode === \"global\")\n )\n .subscribe(key => {\n switch (key.type) {\n\n /* Go to previous page */\n case \"p\":\n case \",\":\n const prev = getOptionalElement(\"link[rel=prev]\")\n if (typeof prev !== \"undefined\")\n setLocation(prev)\n break\n\n /* Go to next page */\n case \"n\":\n case \".\":\n const next = getOptionalElement(\"link[rel=next]\")\n if (typeof next !== \"undefined\")\n setLocation(next)\n break\n\n /* Expand navigation, see https://bit.ly/3ZjG5io */\n case \"Enter\":\n const active = getActiveElement()\n if (active instanceof HTMLLabelElement)\n active.click()\n }\n })\n\n/* Set up patches */\npatchEllipsis({ viewport$, document$ })\npatchIndeterminate({ document$, tablet$ })\npatchScrollfix({ document$ })\npatchScrolllock({ viewport$, tablet$ })\n\n/* Set up header and main area observable */\nconst header$ = watchHeader(getComponentElement(\"header\"), { viewport$ })\nconst main$ = document$\n .pipe(\n map(() => getComponentElement(\"main\")),\n switchMap(el => watchMain(el, { viewport$, header$ })),\n shareReplay(1)\n )\n\n/* Set up control component observables */\nconst control$ = merge(\n\n /* Consent */\n ...getComponentElements(\"consent\")\n .map(el => mountConsent(el, { target$ })),\n\n /* Dialog */\n ...getComponentElements(\"dialog\")\n .map(el => mountDialog(el, { alert$ })),\n\n /* Header */\n ...getComponentElements(\"header\")\n .map(el => mountHeader(el, { viewport$, header$, main$ })),\n\n /* Color palette */\n ...getComponentElements(\"palette\")\n .map(el => mountPalette(el)),\n\n /* Progress bar */\n ...getComponentElements(\"progress\")\n .map(el => mountProgress(el, { progress$ })),\n\n /* Search */\n ...getComponentElements(\"search\")\n .map(el => mountSearch(el, { index$, keyboard$ })),\n\n /* Repository information */\n ...getComponentElements(\"source\")\n .map(el => mountSource(el))\n)\n\n/* Set up content component observables */\nconst content$ = defer(() => merge(\n\n /* Announcement bar */\n ...getComponentElements(\"announce\")\n .map(el => mountAnnounce(el)),\n\n /* Content */\n ...getComponentElements(\"content\")\n .map(el => mountContent(el, { viewport$, target$, print$ })),\n\n /* Search highlighting */\n ...getComponentElements(\"content\")\n .map(el => feature(\"search.highlight\")\n ? mountSearchHiglight(el, { index$, location$ })\n : EMPTY\n ),\n\n /* Header title */\n ...getComponentElements(\"header-title\")\n .map(el => mountHeaderTitle(el, { viewport$, header$ })),\n\n /* Sidebar */\n ...getComponentElements(\"sidebar\")\n .map(el => el.getAttribute(\"data-md-type\") === \"navigation\"\n ? at(screen$, () => mountSidebar(el, { viewport$, header$, main$ }))\n : at(tablet$, () => mountSidebar(el, { viewport$, header$, main$ }))\n ),\n\n /* Navigation tabs */\n ...getComponentElements(\"tabs\")\n .map(el => mountTabs(el, { viewport$, header$ })),\n\n /* Table of contents */\n ...getComponentElements(\"toc\")\n .map(el => mountTableOfContents(el, {\n viewport$, header$, main$, target$\n })),\n\n /* Back-to-top button */\n ...getComponentElements(\"top\")\n .map(el => mountBackToTop(el, { viewport$, header$, main$, target$ }))\n))\n\n/* Set up component observables */\nconst component$ = document$\n .pipe(\n switchMap(() => content$),\n mergeWith(control$),\n shareReplay(1)\n )\n\n/* Subscribe to all components */\ncomponent$.subscribe()\n\n/* ----------------------------------------------------------------------------\n * Exports\n * ------------------------------------------------------------------------- */\n\nwindow.document$ = document$ /* Document observable */\nwindow.location$ = location$ /* Location subject */\nwindow.target$ = target$ /* Location target observable */\nwindow.keyboard$ = keyboard$ /* Keyboard observable */\nwindow.viewport$ = viewport$ /* Viewport observable */\nwindow.tablet$ = tablet$ /* Media tablet observable */\nwindow.screen$ = screen$ /* Media screen observable */\nwindow.print$ = print$ /* Media print observable */\nwindow.alert$ = alert$ /* Alert subject */\nwindow.progress$ = progress$ /* Progress indicator subject */\nwindow.component$ = component$ /* Component observable */\n", "/*! *****************************************************************************\r\nCopyright (c) Microsoft Corporation.\r\n\r\nPermission to use, copy, modify, and/or distribute this software for any\r\npurpose with or without fee is hereby granted.\r\n\r\nTHE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\r\nREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\r\nAND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\r\nINDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\r\nLOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\r\nOTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\r\nPERFORMANCE OF THIS SOFTWARE.\r\n***************************************************************************** */\r\n/* global Reflect, Promise */\r\n\r\nvar extendStatics = function(d, b) {\r\n extendStatics = Object.setPrototypeOf ||\r\n ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||\r\n function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };\r\n return extendStatics(d, b);\r\n};\r\n\r\nexport function __extends(d, b) {\r\n if (typeof b !== \"function\" && b !== null)\r\n throw new TypeError(\"Class extends value \" + String(b) + \" is not a constructor or null\");\r\n extendStatics(d, b);\r\n function __() { this.constructor = d; }\r\n d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());\r\n}\r\n\r\nexport var __assign = function() {\r\n __assign = Object.assign || function __assign(t) {\r\n for (var s, i = 1, n = arguments.length; i < n; i++) {\r\n s = arguments[i];\r\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p)) t[p] = s[p];\r\n }\r\n return t;\r\n }\r\n return __assign.apply(this, arguments);\r\n}\r\n\r\nexport function __rest(s, e) {\r\n var t = {};\r\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)\r\n t[p] = s[p];\r\n if (s != null && typeof Object.getOwnPropertySymbols === \"function\")\r\n for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {\r\n if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))\r\n t[p[i]] = s[p[i]];\r\n }\r\n return t;\r\n}\r\n\r\nexport function __decorate(decorators, target, key, desc) {\r\n var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;\r\n if (typeof Reflect === \"object\" && typeof Reflect.decorate === \"function\") r = Reflect.decorate(decorators, target, key, desc);\r\n else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;\r\n return c > 3 && r && Object.defineProperty(target, key, r), r;\r\n}\r\n\r\nexport function __param(paramIndex, decorator) {\r\n return function (target, key) { decorator(target, key, paramIndex); }\r\n}\r\n\r\nexport function __metadata(metadataKey, metadataValue) {\r\n if (typeof Reflect === \"object\" && typeof Reflect.metadata === \"function\") return Reflect.metadata(metadataKey, metadataValue);\r\n}\r\n\r\nexport function __awaiter(thisArg, _arguments, P, generator) {\r\n function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }\r\n return new (P || (P = Promise))(function (resolve, reject) {\r\n function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }\r\n function rejected(value) { try { step(generator[\"throw\"](value)); } catch (e) { reject(e); } }\r\n function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }\r\n step((generator = generator.apply(thisArg, _arguments || [])).next());\r\n });\r\n}\r\n\r\nexport function __generator(thisArg, body) {\r\n var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;\r\n return g = { next: verb(0), \"throw\": verb(1), \"return\": verb(2) }, typeof Symbol === \"function\" && (g[Symbol.iterator] = function() { return this; }), g;\r\n function verb(n) { return function (v) { return step([n, v]); }; }\r\n function step(op) {\r\n if (f) throw new TypeError(\"Generator is already executing.\");\r\n while (_) try {\r\n if (f = 1, y && (t = op[0] & 2 ? y[\"return\"] : op[0] ? y[\"throw\"] || ((t = y[\"return\"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;\r\n if (y = 0, t) op = [op[0] & 2, t.value];\r\n switch (op[0]) {\r\n case 0: case 1: t = op; break;\r\n case 4: _.label++; return { value: op[1], done: false };\r\n case 5: _.label++; y = op[1]; op = [0]; continue;\r\n case 7: op = _.ops.pop(); _.trys.pop(); continue;\r\n default:\r\n if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }\r\n if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }\r\n if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }\r\n if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }\r\n if (t[2]) _.ops.pop();\r\n _.trys.pop(); continue;\r\n }\r\n op = body.call(thisArg, _);\r\n } catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }\r\n if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };\r\n }\r\n}\r\n\r\nexport var __createBinding = Object.create ? (function(o, m, k, k2) {\r\n if (k2 === undefined) k2 = k;\r\n Object.defineProperty(o, k2, { enumerable: true, get: function() { return m[k]; } });\r\n}) : (function(o, m, k, k2) {\r\n if (k2 === undefined) k2 = k;\r\n o[k2] = m[k];\r\n});\r\n\r\nexport function __exportStar(m, o) {\r\n for (var p in m) if (p !== \"default\" && !Object.prototype.hasOwnProperty.call(o, p)) __createBinding(o, m, p);\r\n}\r\n\r\nexport function __values(o) {\r\n var s = typeof Symbol === \"function\" && Symbol.iterator, m = s && o[s], i = 0;\r\n if (m) return m.call(o);\r\n if (o && typeof o.length === \"number\") return {\r\n next: function () {\r\n if (o && i >= o.length) o = void 0;\r\n return { value: o && o[i++], done: !o };\r\n }\r\n };\r\n throw new TypeError(s ? \"Object is not iterable.\" : \"Symbol.iterator is not defined.\");\r\n}\r\n\r\nexport function __read(o, n) {\r\n var m = typeof Symbol === \"function\" && o[Symbol.iterator];\r\n if (!m) return o;\r\n var i = m.call(o), r, ar = [], e;\r\n try {\r\n while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);\r\n }\r\n catch (error) { e = { error: error }; }\r\n finally {\r\n try {\r\n if (r && !r.done && (m = i[\"return\"])) m.call(i);\r\n }\r\n finally { if (e) throw e.error; }\r\n }\r\n return ar;\r\n}\r\n\r\n/** @deprecated */\r\nexport function __spread() {\r\n for (var ar = [], i = 0; i < arguments.length; i++)\r\n ar = ar.concat(__read(arguments[i]));\r\n return ar;\r\n}\r\n\r\n/** @deprecated */\r\nexport function __spreadArrays() {\r\n for (var s = 0, i = 0, il = arguments.length; i < il; i++) s += arguments[i].length;\r\n for (var r = Array(s), k = 0, i = 0; i < il; i++)\r\n for (var a = arguments[i], j = 0, jl = a.length; j < jl; j++, k++)\r\n r[k] = a[j];\r\n return r;\r\n}\r\n\r\nexport function __spreadArray(to, from, pack) {\r\n if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {\r\n if (ar || !(i in from)) {\r\n if (!ar) ar = Array.prototype.slice.call(from, 0, i);\r\n ar[i] = from[i];\r\n }\r\n }\r\n return to.concat(ar || Array.prototype.slice.call(from));\r\n}\r\n\r\nexport function __await(v) {\r\n return this instanceof __await ? (this.v = v, this) : new __await(v);\r\n}\r\n\r\nexport function __asyncGenerator(thisArg, _arguments, generator) {\r\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n var g = generator.apply(thisArg, _arguments || []), i, q = [];\r\n return i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i;\r\n function verb(n) { if (g[n]) i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; }\r\n function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }\r\n function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r); }\r\n function fulfill(value) { resume(\"next\", value); }\r\n function reject(value) { resume(\"throw\", value); }\r\n function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }\r\n}\r\n\r\nexport function __asyncDelegator(o) {\r\n var i, p;\r\n return i = {}, verb(\"next\"), verb(\"throw\", function (e) { throw e; }), verb(\"return\"), i[Symbol.iterator] = function () { return this; }, i;\r\n function verb(n, f) { i[n] = o[n] ? function (v) { return (p = !p) ? { value: __await(o[n](v)), done: n === \"return\" } : f ? f(v) : v; } : f; }\r\n}\r\n\r\nexport function __asyncValues(o) {\r\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n var m = o[Symbol.asyncIterator], i;\r\n return m ? m.call(o) : (o = typeof __values === \"function\" ? __values(o) : o[Symbol.iterator](), i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i);\r\n function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }\r\n function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }\r\n}\r\n\r\nexport function __makeTemplateObject(cooked, raw) {\r\n if (Object.defineProperty) { Object.defineProperty(cooked, \"raw\", { value: raw }); } else { cooked.raw = raw; }\r\n return cooked;\r\n};\r\n\r\nvar __setModuleDefault = Object.create ? (function(o, v) {\r\n Object.defineProperty(o, \"default\", { enumerable: true, value: v });\r\n}) : function(o, v) {\r\n o[\"default\"] = v;\r\n};\r\n\r\nexport function __importStar(mod) {\r\n if (mod && mod.__esModule) return mod;\r\n var result = {};\r\n if (mod != null) for (var k in mod) if (k !== \"default\" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);\r\n __setModuleDefault(result, mod);\r\n return result;\r\n}\r\n\r\nexport function __importDefault(mod) {\r\n return (mod && mod.__esModule) ? mod : { default: mod };\r\n}\r\n\r\nexport function __classPrivateFieldGet(receiver, state, kind, f) {\r\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a getter\");\r\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot read private member from an object whose class did not declare it\");\r\n return kind === \"m\" ? f : kind === \"a\" ? f.call(receiver) : f ? f.value : state.get(receiver);\r\n}\r\n\r\nexport function __classPrivateFieldSet(receiver, state, value, kind, f) {\r\n if (kind === \"m\") throw new TypeError(\"Private method is not writable\");\r\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a setter\");\r\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot write private member to an object whose class did not declare it\");\r\n return (kind === \"a\" ? f.call(receiver, value) : f ? f.value = value : state.set(receiver, value)), value;\r\n}\r\n", "/**\n * Returns true if the object is a function.\n * @param value The value to check\n */\nexport function isFunction(value: any): value is (...args: any[]) => any {\n return typeof value === 'function';\n}\n", "/**\n * Used to create Error subclasses until the community moves away from ES5.\n *\n * This is because compiling from TypeScript down to ES5 has issues with subclassing Errors\n * as well as other built-in types: https://github.com/Microsoft/TypeScript/issues/12123\n *\n * @param createImpl A factory function to create the actual constructor implementation. The returned\n * function should be a named function that calls `_super` internally.\n */\nexport function createErrorClass(createImpl: (_super: any) => any): T {\n const _super = (instance: any) => {\n Error.call(instance);\n instance.stack = new Error().stack;\n };\n\n const ctorFunc = createImpl(_super);\n ctorFunc.prototype = Object.create(Error.prototype);\n ctorFunc.prototype.constructor = ctorFunc;\n return ctorFunc;\n}\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface UnsubscriptionError extends Error {\n readonly errors: any[];\n}\n\nexport interface UnsubscriptionErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (errors: any[]): UnsubscriptionError;\n}\n\n/**\n * An error thrown when one or more errors have occurred during the\n * `unsubscribe` of a {@link Subscription}.\n */\nexport const UnsubscriptionError: UnsubscriptionErrorCtor = createErrorClass(\n (_super) =>\n function UnsubscriptionErrorImpl(this: any, errors: (Error | string)[]) {\n _super(this);\n this.message = errors\n ? `${errors.length} errors occurred during unsubscription:\n${errors.map((err, i) => `${i + 1}) ${err.toString()}`).join('\\n ')}`\n : '';\n this.name = 'UnsubscriptionError';\n this.errors = errors;\n }\n);\n", "/**\n * Removes an item from an array, mutating it.\n * @param arr The array to remove the item from\n * @param item The item to remove\n */\nexport function arrRemove(arr: T[] | undefined | null, item: T) {\n if (arr) {\n const index = arr.indexOf(item);\n 0 <= index && arr.splice(index, 1);\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { UnsubscriptionError } from './util/UnsubscriptionError';\nimport { SubscriptionLike, TeardownLogic, Unsubscribable } from './types';\nimport { arrRemove } from './util/arrRemove';\n\n/**\n * Represents a disposable resource, such as the execution of an Observable. A\n * Subscription has one important method, `unsubscribe`, that takes no argument\n * and just disposes the resource held by the subscription.\n *\n * Additionally, subscriptions may be grouped together through the `add()`\n * method, which will attach a child Subscription to the current Subscription.\n * When a Subscription is unsubscribed, all its children (and its grandchildren)\n * will be unsubscribed as well.\n *\n * @class Subscription\n */\nexport class Subscription implements SubscriptionLike {\n /** @nocollapse */\n public static EMPTY = (() => {\n const empty = new Subscription();\n empty.closed = true;\n return empty;\n })();\n\n /**\n * A flag to indicate whether this Subscription has already been unsubscribed.\n */\n public closed = false;\n\n private _parentage: Subscription[] | Subscription | null = null;\n\n /**\n * The list of registered finalizers to execute upon unsubscription. Adding and removing from this\n * list occurs in the {@link #add} and {@link #remove} methods.\n */\n private _finalizers: Exclude[] | null = null;\n\n /**\n * @param initialTeardown A function executed first as part of the finalization\n * process that is kicked off when {@link #unsubscribe} is called.\n */\n constructor(private initialTeardown?: () => void) {}\n\n /**\n * Disposes the resources held by the subscription. May, for instance, cancel\n * an ongoing Observable execution or cancel any other type of work that\n * started when the Subscription was created.\n * @return {void}\n */\n unsubscribe(): void {\n let errors: any[] | undefined;\n\n if (!this.closed) {\n this.closed = true;\n\n // Remove this from it's parents.\n const { _parentage } = this;\n if (_parentage) {\n this._parentage = null;\n if (Array.isArray(_parentage)) {\n for (const parent of _parentage) {\n parent.remove(this);\n }\n } else {\n _parentage.remove(this);\n }\n }\n\n const { initialTeardown: initialFinalizer } = this;\n if (isFunction(initialFinalizer)) {\n try {\n initialFinalizer();\n } catch (e) {\n errors = e instanceof UnsubscriptionError ? e.errors : [e];\n }\n }\n\n const { _finalizers } = this;\n if (_finalizers) {\n this._finalizers = null;\n for (const finalizer of _finalizers) {\n try {\n execFinalizer(finalizer);\n } catch (err) {\n errors = errors ?? [];\n if (err instanceof UnsubscriptionError) {\n errors = [...errors, ...err.errors];\n } else {\n errors.push(err);\n }\n }\n }\n }\n\n if (errors) {\n throw new UnsubscriptionError(errors);\n }\n }\n }\n\n /**\n * Adds a finalizer to this subscription, so that finalization will be unsubscribed/called\n * when this subscription is unsubscribed. If this subscription is already {@link #closed},\n * because it has already been unsubscribed, then whatever finalizer is passed to it\n * will automatically be executed (unless the finalizer itself is also a closed subscription).\n *\n * Closed Subscriptions cannot be added as finalizers to any subscription. Adding a closed\n * subscription to a any subscription will result in no operation. (A noop).\n *\n * Adding a subscription to itself, or adding `null` or `undefined` will not perform any\n * operation at all. (A noop).\n *\n * `Subscription` instances that are added to this instance will automatically remove themselves\n * if they are unsubscribed. Functions and {@link Unsubscribable} objects that you wish to remove\n * will need to be removed manually with {@link #remove}\n *\n * @param teardown The finalization logic to add to this subscription.\n */\n add(teardown: TeardownLogic): void {\n // Only add the finalizer if it's not undefined\n // and don't add a subscription to itself.\n if (teardown && teardown !== this) {\n if (this.closed) {\n // If this subscription is already closed,\n // execute whatever finalizer is handed to it automatically.\n execFinalizer(teardown);\n } else {\n if (teardown instanceof Subscription) {\n // We don't add closed subscriptions, and we don't add the same subscription\n // twice. Subscription unsubscribe is idempotent.\n if (teardown.closed || teardown._hasParent(this)) {\n return;\n }\n teardown._addParent(this);\n }\n (this._finalizers = this._finalizers ?? []).push(teardown);\n }\n }\n }\n\n /**\n * Checks to see if a this subscription already has a particular parent.\n * This will signal that this subscription has already been added to the parent in question.\n * @param parent the parent to check for\n */\n private _hasParent(parent: Subscription) {\n const { _parentage } = this;\n return _parentage === parent || (Array.isArray(_parentage) && _parentage.includes(parent));\n }\n\n /**\n * Adds a parent to this subscription so it can be removed from the parent if it\n * unsubscribes on it's own.\n *\n * NOTE: THIS ASSUMES THAT {@link _hasParent} HAS ALREADY BEEN CHECKED.\n * @param parent The parent subscription to add\n */\n private _addParent(parent: Subscription) {\n const { _parentage } = this;\n this._parentage = Array.isArray(_parentage) ? (_parentage.push(parent), _parentage) : _parentage ? [_parentage, parent] : parent;\n }\n\n /**\n * Called on a child when it is removed via {@link #remove}.\n * @param parent The parent to remove\n */\n private _removeParent(parent: Subscription) {\n const { _parentage } = this;\n if (_parentage === parent) {\n this._parentage = null;\n } else if (Array.isArray(_parentage)) {\n arrRemove(_parentage, parent);\n }\n }\n\n /**\n * Removes a finalizer from this subscription that was previously added with the {@link #add} method.\n *\n * Note that `Subscription` instances, when unsubscribed, will automatically remove themselves\n * from every other `Subscription` they have been added to. This means that using the `remove` method\n * is not a common thing and should be used thoughtfully.\n *\n * If you add the same finalizer instance of a function or an unsubscribable object to a `Subscription` instance\n * more than once, you will need to call `remove` the same number of times to remove all instances.\n *\n * All finalizer instances are removed to free up memory upon unsubscription.\n *\n * @param teardown The finalizer to remove from this subscription\n */\n remove(teardown: Exclude): void {\n const { _finalizers } = this;\n _finalizers && arrRemove(_finalizers, teardown);\n\n if (teardown instanceof Subscription) {\n teardown._removeParent(this);\n }\n }\n}\n\nexport const EMPTY_SUBSCRIPTION = Subscription.EMPTY;\n\nexport function isSubscription(value: any): value is Subscription {\n return (\n value instanceof Subscription ||\n (value && 'closed' in value && isFunction(value.remove) && isFunction(value.add) && isFunction(value.unsubscribe))\n );\n}\n\nfunction execFinalizer(finalizer: Unsubscribable | (() => void)) {\n if (isFunction(finalizer)) {\n finalizer();\n } else {\n finalizer.unsubscribe();\n }\n}\n", "import { Subscriber } from './Subscriber';\nimport { ObservableNotification } from './types';\n\n/**\n * The {@link GlobalConfig} object for RxJS. It is used to configure things\n * like how to react on unhandled errors.\n */\nexport const config: GlobalConfig = {\n onUnhandledError: null,\n onStoppedNotification: null,\n Promise: undefined,\n useDeprecatedSynchronousErrorHandling: false,\n useDeprecatedNextContext: false,\n};\n\n/**\n * The global configuration object for RxJS, used to configure things\n * like how to react on unhandled errors. Accessible via {@link config}\n * object.\n */\nexport interface GlobalConfig {\n /**\n * A registration point for unhandled errors from RxJS. These are errors that\n * cannot were not handled by consuming code in the usual subscription path. For\n * example, if you have this configured, and you subscribe to an observable without\n * providing an error handler, errors from that subscription will end up here. This\n * will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onUnhandledError: ((err: any) => void) | null;\n\n /**\n * A registration point for notifications that cannot be sent to subscribers because they\n * have completed, errored or have been explicitly unsubscribed. By default, next, complete\n * and error notifications sent to stopped subscribers are noops. However, sometimes callers\n * might want a different behavior. For example, with sources that attempt to report errors\n * to stopped subscribers, a caller can configure RxJS to throw an unhandled error instead.\n * This will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onStoppedNotification: ((notification: ObservableNotification, subscriber: Subscriber) => void) | null;\n\n /**\n * The promise constructor used by default for {@link Observable#toPromise toPromise} and {@link Observable#forEach forEach}\n * methods.\n *\n * @deprecated As of version 8, RxJS will no longer support this sort of injection of a\n * Promise constructor. If you need a Promise implementation other than native promises,\n * please polyfill/patch Promise as you see appropriate. Will be removed in v8.\n */\n Promise?: PromiseConstructorLike;\n\n /**\n * If true, turns on synchronous error rethrowing, which is a deprecated behavior\n * in v6 and higher. This behavior enables bad patterns like wrapping a subscribe\n * call in a try/catch block. It also enables producer interference, a nasty bug\n * where a multicast can be broken for all observers by a downstream consumer with\n * an unhandled error. DO NOT USE THIS FLAG UNLESS IT'S NEEDED TO BUY TIME\n * FOR MIGRATION REASONS.\n *\n * @deprecated As of version 8, RxJS will no longer support synchronous throwing\n * of unhandled errors. All errors will be thrown on a separate call stack to prevent bad\n * behaviors described above. Will be removed in v8.\n */\n useDeprecatedSynchronousErrorHandling: boolean;\n\n /**\n * If true, enables an as-of-yet undocumented feature from v5: The ability to access\n * `unsubscribe()` via `this` context in `next` functions created in observers passed\n * to `subscribe`.\n *\n * This is being removed because the performance was severely problematic, and it could also cause\n * issues when types other than POJOs are passed to subscribe as subscribers, as they will likely have\n * their `this` context overwritten.\n *\n * @deprecated As of version 8, RxJS will no longer support altering the\n * context of next functions provided as part of an observer to Subscribe. Instead,\n * you will have access to a subscription or a signal or token that will allow you to do things like\n * unsubscribe and test closed status. Will be removed in v8.\n */\n useDeprecatedNextContext: boolean;\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetTimeoutFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearTimeoutFunction = (handle: TimerHandle) => void;\n\ninterface TimeoutProvider {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n delegate:\n | {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n }\n | undefined;\n}\n\nexport const timeoutProvider: TimeoutProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setTimeout(handler: () => void, timeout?: number, ...args) {\n const { delegate } = timeoutProvider;\n if (delegate?.setTimeout) {\n return delegate.setTimeout(handler, timeout, ...args);\n }\n return setTimeout(handler, timeout, ...args);\n },\n clearTimeout(handle) {\n const { delegate } = timeoutProvider;\n return (delegate?.clearTimeout || clearTimeout)(handle as any);\n },\n delegate: undefined,\n};\n", "import { config } from '../config';\nimport { timeoutProvider } from '../scheduler/timeoutProvider';\n\n/**\n * Handles an error on another job either with the user-configured {@link onUnhandledError},\n * or by throwing it on that new job so it can be picked up by `window.onerror`, `process.on('error')`, etc.\n *\n * This should be called whenever there is an error that is out-of-band with the subscription\n * or when an error hits a terminal boundary of the subscription and no error handler was provided.\n *\n * @param err the error to report\n */\nexport function reportUnhandledError(err: any) {\n timeoutProvider.setTimeout(() => {\n const { onUnhandledError } = config;\n if (onUnhandledError) {\n // Execute the user-configured error handler.\n onUnhandledError(err);\n } else {\n // Throw so it is picked up by the runtime's uncaught error mechanism.\n throw err;\n }\n });\n}\n", "/* tslint:disable:no-empty */\nexport function noop() { }\n", "import { CompleteNotification, NextNotification, ErrorNotification } from './types';\n\n/**\n * A completion object optimized for memory use and created to be the\n * same \"shape\" as other notifications in v8.\n * @internal\n */\nexport const COMPLETE_NOTIFICATION = (() => createNotification('C', undefined, undefined) as CompleteNotification)();\n\n/**\n * Internal use only. Creates an optimized error notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function errorNotification(error: any): ErrorNotification {\n return createNotification('E', undefined, error) as any;\n}\n\n/**\n * Internal use only. Creates an optimized next notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function nextNotification(value: T) {\n return createNotification('N', value, undefined) as NextNotification;\n}\n\n/**\n * Ensures that all notifications created internally have the same \"shape\" in v8.\n *\n * TODO: This is only exported to support a crazy legacy test in `groupBy`.\n * @internal\n */\nexport function createNotification(kind: 'N' | 'E' | 'C', value: any, error: any) {\n return {\n kind,\n value,\n error,\n };\n}\n", "import { config } from '../config';\n\nlet context: { errorThrown: boolean; error: any } | null = null;\n\n/**\n * Handles dealing with errors for super-gross mode. Creates a context, in which\n * any synchronously thrown errors will be passed to {@link captureError}. Which\n * will record the error such that it will be rethrown after the call back is complete.\n * TODO: Remove in v8\n * @param cb An immediately executed function.\n */\nexport function errorContext(cb: () => void) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n const isRoot = !context;\n if (isRoot) {\n context = { errorThrown: false, error: null };\n }\n cb();\n if (isRoot) {\n const { errorThrown, error } = context!;\n context = null;\n if (errorThrown) {\n throw error;\n }\n }\n } else {\n // This is the general non-deprecated path for everyone that\n // isn't crazy enough to use super-gross mode (useDeprecatedSynchronousErrorHandling)\n cb();\n }\n}\n\n/**\n * Captures errors only in super-gross mode.\n * @param err the error to capture\n */\nexport function captureError(err: any) {\n if (config.useDeprecatedSynchronousErrorHandling && context) {\n context.errorThrown = true;\n context.error = err;\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { Observer, ObservableNotification } from './types';\nimport { isSubscription, Subscription } from './Subscription';\nimport { config } from './config';\nimport { reportUnhandledError } from './util/reportUnhandledError';\nimport { noop } from './util/noop';\nimport { nextNotification, errorNotification, COMPLETE_NOTIFICATION } from './NotificationFactories';\nimport { timeoutProvider } from './scheduler/timeoutProvider';\nimport { captureError } from './util/errorContext';\n\n/**\n * Implements the {@link Observer} interface and extends the\n * {@link Subscription} class. While the {@link Observer} is the public API for\n * consuming the values of an {@link Observable}, all Observers get converted to\n * a Subscriber, in order to provide Subscription-like capabilities such as\n * `unsubscribe`. Subscriber is a common type in RxJS, and crucial for\n * implementing operators, but it is rarely used as a public API.\n *\n * @class Subscriber\n */\nexport class Subscriber extends Subscription implements Observer {\n /**\n * A static factory for a Subscriber, given a (potentially partial) definition\n * of an Observer.\n * @param next The `next` callback of an Observer.\n * @param error The `error` callback of an\n * Observer.\n * @param complete The `complete` callback of an\n * Observer.\n * @return A Subscriber wrapping the (partially defined)\n * Observer represented by the given arguments.\n * @nocollapse\n * @deprecated Do not use. Will be removed in v8. There is no replacement for this\n * method, and there is no reason to be creating instances of `Subscriber` directly.\n * If you have a specific use case, please file an issue.\n */\n static create(next?: (x?: T) => void, error?: (e?: any) => void, complete?: () => void): Subscriber {\n return new SafeSubscriber(next, error, complete);\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected isStopped: boolean = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected destination: Subscriber | Observer; // this `any` is the escape hatch to erase extra type param (e.g. R)\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * There is no reason to directly create an instance of Subscriber. This type is exported for typings reasons.\n */\n constructor(destination?: Subscriber | Observer) {\n super();\n if (destination) {\n this.destination = destination;\n // Automatically chain subscriptions together here.\n // if destination is a Subscription, then it is a Subscriber.\n if (isSubscription(destination)) {\n destination.add(this);\n }\n } else {\n this.destination = EMPTY_OBSERVER;\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `next` from\n * the Observable, with a value. The Observable may call this method 0 or more\n * times.\n * @param {T} [value] The `next` value.\n * @return {void}\n */\n next(value?: T): void {\n if (this.isStopped) {\n handleStoppedNotification(nextNotification(value), this);\n } else {\n this._next(value!);\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `error` from\n * the Observable, with an attached `Error`. Notifies the Observer that\n * the Observable has experienced an error condition.\n * @param {any} [err] The `error` exception.\n * @return {void}\n */\n error(err?: any): void {\n if (this.isStopped) {\n handleStoppedNotification(errorNotification(err), this);\n } else {\n this.isStopped = true;\n this._error(err);\n }\n }\n\n /**\n * The {@link Observer} callback to receive a valueless notification of type\n * `complete` from the Observable. Notifies the Observer that the Observable\n * has finished sending push-based notifications.\n * @return {void}\n */\n complete(): void {\n if (this.isStopped) {\n handleStoppedNotification(COMPLETE_NOTIFICATION, this);\n } else {\n this.isStopped = true;\n this._complete();\n }\n }\n\n unsubscribe(): void {\n if (!this.closed) {\n this.isStopped = true;\n super.unsubscribe();\n this.destination = null!;\n }\n }\n\n protected _next(value: T): void {\n this.destination.next(value);\n }\n\n protected _error(err: any): void {\n try {\n this.destination.error(err);\n } finally {\n this.unsubscribe();\n }\n }\n\n protected _complete(): void {\n try {\n this.destination.complete();\n } finally {\n this.unsubscribe();\n }\n }\n}\n\n/**\n * This bind is captured here because we want to be able to have\n * compatibility with monoid libraries that tend to use a method named\n * `bind`. In particular, a library called Monio requires this.\n */\nconst _bind = Function.prototype.bind;\n\nfunction bind any>(fn: Fn, thisArg: any): Fn {\n return _bind.call(fn, thisArg);\n}\n\n/**\n * Internal optimization only, DO NOT EXPOSE.\n * @internal\n */\nclass ConsumerObserver implements Observer {\n constructor(private partialObserver: Partial>) {}\n\n next(value: T): void {\n const { partialObserver } = this;\n if (partialObserver.next) {\n try {\n partialObserver.next(value);\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n\n error(err: any): void {\n const { partialObserver } = this;\n if (partialObserver.error) {\n try {\n partialObserver.error(err);\n } catch (error) {\n handleUnhandledError(error);\n }\n } else {\n handleUnhandledError(err);\n }\n }\n\n complete(): void {\n const { partialObserver } = this;\n if (partialObserver.complete) {\n try {\n partialObserver.complete();\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n}\n\nexport class SafeSubscriber extends Subscriber {\n constructor(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((e?: any) => void) | null,\n complete?: (() => void) | null\n ) {\n super();\n\n let partialObserver: Partial>;\n if (isFunction(observerOrNext) || !observerOrNext) {\n // The first argument is a function, not an observer. The next\n // two arguments *could* be observers, or they could be empty.\n partialObserver = {\n next: (observerOrNext ?? undefined) as (((value: T) => void) | undefined),\n error: error ?? undefined,\n complete: complete ?? undefined,\n };\n } else {\n // The first argument is a partial observer.\n let context: any;\n if (this && config.useDeprecatedNextContext) {\n // This is a deprecated path that made `this.unsubscribe()` available in\n // next handler functions passed to subscribe. This only exists behind a flag\n // now, as it is *very* slow.\n context = Object.create(observerOrNext);\n context.unsubscribe = () => this.unsubscribe();\n partialObserver = {\n next: observerOrNext.next && bind(observerOrNext.next, context),\n error: observerOrNext.error && bind(observerOrNext.error, context),\n complete: observerOrNext.complete && bind(observerOrNext.complete, context),\n };\n } else {\n // The \"normal\" path. Just use the partial observer directly.\n partialObserver = observerOrNext;\n }\n }\n\n // Wrap the partial observer to ensure it's a full observer, and\n // make sure proper error handling is accounted for.\n this.destination = new ConsumerObserver(partialObserver);\n }\n}\n\nfunction handleUnhandledError(error: any) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n captureError(error);\n } else {\n // Ideal path, we report this as an unhandled error,\n // which is thrown on a new call stack.\n reportUnhandledError(error);\n }\n}\n\n/**\n * An error handler used when no error handler was supplied\n * to the SafeSubscriber -- meaning no error handler was supplied\n * do the `subscribe` call on our observable.\n * @param err The error to handle\n */\nfunction defaultErrorHandler(err: any) {\n throw err;\n}\n\n/**\n * A handler for notifications that cannot be sent to a stopped subscriber.\n * @param notification The notification being sent\n * @param subscriber The stopped subscriber\n */\nfunction handleStoppedNotification(notification: ObservableNotification, subscriber: Subscriber) {\n const { onStoppedNotification } = config;\n onStoppedNotification && timeoutProvider.setTimeout(() => onStoppedNotification(notification, subscriber));\n}\n\n/**\n * The observer used as a stub for subscriptions where the user did not\n * pass any arguments to `subscribe`. Comes with the default error handling\n * behavior.\n */\nexport const EMPTY_OBSERVER: Readonly> & { closed: true } = {\n closed: true,\n next: noop,\n error: defaultErrorHandler,\n complete: noop,\n};\n", "/**\n * Symbol.observable or a string \"@@observable\". Used for interop\n *\n * @deprecated We will no longer be exporting this symbol in upcoming versions of RxJS.\n * Instead polyfill and use Symbol.observable directly *or* use https://www.npmjs.com/package/symbol-observable\n */\nexport const observable: string | symbol = (() => (typeof Symbol === 'function' && Symbol.observable) || '@@observable')();\n", "/**\n * This function takes one parameter and just returns it. Simply put,\n * this is like `(x: T): T => x`.\n *\n * ## Examples\n *\n * This is useful in some cases when using things like `mergeMap`\n *\n * ```ts\n * import { interval, take, map, range, mergeMap, identity } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(5));\n *\n * const result$ = source$.pipe(\n * map(i => range(i)),\n * mergeMap(identity) // same as mergeMap(x => x)\n * );\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * Or when you want to selectively apply an operator\n *\n * ```ts\n * import { interval, take, identity } from 'rxjs';\n *\n * const shouldLimit = () => Math.random() < 0.5;\n *\n * const source$ = interval(1000);\n *\n * const result$ = source$.pipe(shouldLimit() ? take(5) : identity);\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * @param x Any value that is returned by this function\n * @returns The value passed as the first parameter to this function\n */\nexport function identity(x: T): T {\n return x;\n}\n", "import { identity } from './identity';\nimport { UnaryFunction } from '../types';\n\nexport function pipe(): typeof identity;\nexport function pipe(fn1: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction, fn3: UnaryFunction): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction,\n ...fns: UnaryFunction[]\n): UnaryFunction;\n\n/**\n * pipe() can be called on one or more functions, each of which can take one argument (\"UnaryFunction\")\n * and uses it to return a value.\n * It returns a function that takes one argument, passes it to the first UnaryFunction, and then\n * passes the result to the next one, passes that result to the next one, and so on. \n */\nexport function pipe(...fns: Array>): UnaryFunction {\n return pipeFromArray(fns);\n}\n\n/** @internal */\nexport function pipeFromArray(fns: Array>): UnaryFunction {\n if (fns.length === 0) {\n return identity as UnaryFunction;\n }\n\n if (fns.length === 1) {\n return fns[0];\n }\n\n return function piped(input: T): R {\n return fns.reduce((prev: any, fn: UnaryFunction) => fn(prev), input as any);\n };\n}\n", "import { Operator } from './Operator';\nimport { SafeSubscriber, Subscriber } from './Subscriber';\nimport { isSubscription, Subscription } from './Subscription';\nimport { TeardownLogic, OperatorFunction, Subscribable, Observer } from './types';\nimport { observable as Symbol_observable } from './symbol/observable';\nimport { pipeFromArray } from './util/pipe';\nimport { config } from './config';\nimport { isFunction } from './util/isFunction';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A representation of any set of values over any amount of time. This is the most basic building block\n * of RxJS.\n *\n * @class Observable\n */\nexport class Observable implements Subscribable {\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n source: Observable | undefined;\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n operator: Operator | undefined;\n\n /**\n * @constructor\n * @param {Function} subscribe the function that is called when the Observable is\n * initially subscribed to. This function is given a Subscriber, to which new values\n * can be `next`ed, or an `error` method can be called to raise an error, or\n * `complete` can be called to notify of a successful completion.\n */\n constructor(subscribe?: (this: Observable, subscriber: Subscriber) => TeardownLogic) {\n if (subscribe) {\n this._subscribe = subscribe;\n }\n }\n\n // HACK: Since TypeScript inherits static properties too, we have to\n // fight against TypeScript here so Subject can have a different static create signature\n /**\n * Creates a new Observable by calling the Observable constructor\n * @owner Observable\n * @method create\n * @param {Function} subscribe? the subscriber function to be passed to the Observable constructor\n * @return {Observable} a new observable\n * @nocollapse\n * @deprecated Use `new Observable()` instead. Will be removed in v8.\n */\n static create: (...args: any[]) => any = (subscribe?: (subscriber: Subscriber) => TeardownLogic) => {\n return new Observable(subscribe);\n };\n\n /**\n * Creates a new Observable, with this Observable instance as the source, and the passed\n * operator defined as the new observable's operator.\n * @method lift\n * @param operator the operator defining the operation to take on the observable\n * @return a new observable with the Operator applied\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * If you have implemented an operator using `lift`, it is recommended that you create an\n * operator by simply returning `new Observable()` directly. See \"Creating new operators from\n * scratch\" section here: https://rxjs.dev/guide/operators\n */\n lift(operator?: Operator): Observable {\n const observable = new Observable();\n observable.source = this;\n observable.operator = operator;\n return observable;\n }\n\n subscribe(observerOrNext?: Partial> | ((value: T) => void)): Subscription;\n /** @deprecated Instead of passing separate callback arguments, use an observer argument. Signatures taking separate callback arguments will be removed in v8. Details: https://rxjs.dev/deprecations/subscribe-arguments */\n subscribe(next?: ((value: T) => void) | null, error?: ((error: any) => void) | null, complete?: (() => void) | null): Subscription;\n /**\n * Invokes an execution of an Observable and registers Observer handlers for notifications it will emit.\n *\n * Use it when you have all these Observables, but still nothing is happening.\n *\n * `subscribe` is not a regular operator, but a method that calls Observable's internal `subscribe` function. It\n * might be for example a function that you passed to Observable's constructor, but most of the time it is\n * a library implementation, which defines what will be emitted by an Observable, and when it be will emitted. This means\n * that calling `subscribe` is actually the moment when Observable starts its work, not when it is created, as it is often\n * the thought.\n *\n * Apart from starting the execution of an Observable, this method allows you to listen for values\n * that an Observable emits, as well as for when it completes or errors. You can achieve this in two\n * of the following ways.\n *\n * The first way is creating an object that implements {@link Observer} interface. It should have methods\n * defined by that interface, but note that it should be just a regular JavaScript object, which you can create\n * yourself in any way you want (ES6 class, classic function constructor, object literal etc.). In particular, do\n * not attempt to use any RxJS implementation details to create Observers - you don't need them. Remember also\n * that your object does not have to implement all methods. If you find yourself creating a method that doesn't\n * do anything, you can simply omit it. Note however, if the `error` method is not provided and an error happens,\n * it will be thrown asynchronously. Errors thrown asynchronously cannot be caught using `try`/`catch`. Instead,\n * use the {@link onUnhandledError} configuration option or use a runtime handler (like `window.onerror` or\n * `process.on('error)`) to be notified of unhandled errors. Because of this, it's recommended that you provide\n * an `error` method to avoid missing thrown errors.\n *\n * The second way is to give up on Observer object altogether and simply provide callback functions in place of its methods.\n * This means you can provide three functions as arguments to `subscribe`, where the first function is equivalent\n * of a `next` method, the second of an `error` method and the third of a `complete` method. Just as in case of an Observer,\n * if you do not need to listen for something, you can omit a function by passing `undefined` or `null`,\n * since `subscribe` recognizes these functions by where they were placed in function call. When it comes\n * to the `error` function, as with an Observer, if not provided, errors emitted by an Observable will be thrown asynchronously.\n *\n * You can, however, subscribe with no parameters at all. This may be the case where you're not interested in terminal events\n * and you also handled emissions internally by using operators (e.g. using `tap`).\n *\n * Whichever style of calling `subscribe` you use, in both cases it returns a Subscription object.\n * This object allows you to call `unsubscribe` on it, which in turn will stop the work that an Observable does and will clean\n * up all resources that an Observable used. Note that cancelling a subscription will not call `complete` callback\n * provided to `subscribe` function, which is reserved for a regular completion signal that comes from an Observable.\n *\n * Remember that callbacks provided to `subscribe` are not guaranteed to be called asynchronously.\n * It is an Observable itself that decides when these functions will be called. For example {@link of}\n * by default emits all its values synchronously. Always check documentation for how given Observable\n * will behave when subscribed and if its default behavior can be modified with a `scheduler`.\n *\n * #### Examples\n *\n * Subscribe with an {@link guide/observer Observer}\n *\n * ```ts\n * import { of } from 'rxjs';\n *\n * const sumObserver = {\n * sum: 0,\n * next(value) {\n * console.log('Adding: ' + value);\n * this.sum = this.sum + value;\n * },\n * error() {\n * // We actually could just remove this method,\n * // since we do not really care about errors right now.\n * },\n * complete() {\n * console.log('Sum equals: ' + this.sum);\n * }\n * };\n *\n * of(1, 2, 3) // Synchronously emits 1, 2, 3 and then completes.\n * .subscribe(sumObserver);\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Subscribe with functions ({@link deprecations/subscribe-arguments deprecated})\n *\n * ```ts\n * import { of } from 'rxjs'\n *\n * let sum = 0;\n *\n * of(1, 2, 3).subscribe(\n * value => {\n * console.log('Adding: ' + value);\n * sum = sum + value;\n * },\n * undefined,\n * () => console.log('Sum equals: ' + sum)\n * );\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Cancel a subscription\n *\n * ```ts\n * import { interval } from 'rxjs';\n *\n * const subscription = interval(1000).subscribe({\n * next(num) {\n * console.log(num)\n * },\n * complete() {\n * // Will not be called, even when cancelling subscription.\n * console.log('completed!');\n * }\n * });\n *\n * setTimeout(() => {\n * subscription.unsubscribe();\n * console.log('unsubscribed!');\n * }, 2500);\n *\n * // Logs:\n * // 0 after 1s\n * // 1 after 2s\n * // 'unsubscribed!' after 2.5s\n * ```\n *\n * @param {Observer|Function} observerOrNext (optional) Either an observer with methods to be called,\n * or the first of three possible handlers, which is the handler for each value emitted from the subscribed\n * Observable.\n * @param {Function} error (optional) A handler for a terminal event resulting from an error. If no error handler is provided,\n * the error will be thrown asynchronously as unhandled.\n * @param {Function} complete (optional) A handler for a terminal event resulting from successful completion.\n * @return {Subscription} a subscription reference to the registered handlers\n * @method subscribe\n */\n subscribe(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((error: any) => void) | null,\n complete?: (() => void) | null\n ): Subscription {\n const subscriber = isSubscriber(observerOrNext) ? observerOrNext : new SafeSubscriber(observerOrNext, error, complete);\n\n errorContext(() => {\n const { operator, source } = this;\n subscriber.add(\n operator\n ? // We're dealing with a subscription in the\n // operator chain to one of our lifted operators.\n operator.call(subscriber, source)\n : source\n ? // If `source` has a value, but `operator` does not, something that\n // had intimate knowledge of our API, like our `Subject`, must have\n // set it. We're going to just call `_subscribe` directly.\n this._subscribe(subscriber)\n : // In all other cases, we're likely wrapping a user-provided initializer\n // function, so we need to catch errors and handle them appropriately.\n this._trySubscribe(subscriber)\n );\n });\n\n return subscriber;\n }\n\n /** @internal */\n protected _trySubscribe(sink: Subscriber): TeardownLogic {\n try {\n return this._subscribe(sink);\n } catch (err) {\n // We don't need to return anything in this case,\n // because it's just going to try to `add()` to a subscription\n // above.\n sink.error(err);\n }\n }\n\n /**\n * Used as a NON-CANCELLABLE means of subscribing to an observable, for use with\n * APIs that expect promises, like `async/await`. You cannot unsubscribe from this.\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * #### Example\n *\n * ```ts\n * import { interval, take } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(4));\n *\n * async function getTotal() {\n * let total = 0;\n *\n * await source$.forEach(value => {\n * total += value;\n * console.log('observable -> ' + value);\n * });\n *\n * return total;\n * }\n *\n * getTotal().then(\n * total => console.log('Total: ' + total)\n * );\n *\n * // Expected:\n * // 'observable -> 0'\n * // 'observable -> 1'\n * // 'observable -> 2'\n * // 'observable -> 3'\n * // 'Total: 6'\n * ```\n *\n * @param next a handler for each value emitted by the observable\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n */\n forEach(next: (value: T) => void): Promise;\n\n /**\n * @param next a handler for each value emitted by the observable\n * @param promiseCtor a constructor function used to instantiate the Promise\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n * @deprecated Passing a Promise constructor will no longer be available\n * in upcoming versions of RxJS. This is because it adds weight to the library, for very\n * little benefit. If you need this functionality, it is recommended that you either\n * polyfill Promise, or you create an adapter to convert the returned native promise\n * to whatever promise implementation you wanted. Will be removed in v8.\n */\n forEach(next: (value: T) => void, promiseCtor: PromiseConstructorLike): Promise;\n\n forEach(next: (value: T) => void, promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n const subscriber = new SafeSubscriber({\n next: (value) => {\n try {\n next(value);\n } catch (err) {\n reject(err);\n subscriber.unsubscribe();\n }\n },\n error: reject,\n complete: resolve,\n });\n this.subscribe(subscriber);\n }) as Promise;\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): TeardownLogic {\n return this.source?.subscribe(subscriber);\n }\n\n /**\n * An interop point defined by the es7-observable spec https://github.com/zenparsing/es-observable\n * @method Symbol.observable\n * @return {Observable} this instance of the observable\n */\n [Symbol_observable]() {\n return this;\n }\n\n /* tslint:disable:max-line-length */\n pipe(): Observable;\n pipe(op1: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction, op3: OperatorFunction): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction,\n ...operations: OperatorFunction[]\n ): Observable;\n /* tslint:enable:max-line-length */\n\n /**\n * Used to stitch together functional operators into a chain.\n * @method pipe\n * @return {Observable} the Observable result of all of the operators having\n * been called in the order they were passed in.\n *\n * ## Example\n *\n * ```ts\n * import { interval, filter, map, scan } from 'rxjs';\n *\n * interval(1000)\n * .pipe(\n * filter(x => x % 2 === 0),\n * map(x => x + x),\n * scan((acc, x) => acc + x)\n * )\n * .subscribe(x => console.log(x));\n * ```\n */\n pipe(...operations: OperatorFunction[]): Observable {\n return pipeFromArray(operations)(this);\n }\n\n /* tslint:disable:max-line-length */\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: typeof Promise): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: PromiseConstructorLike): Promise;\n /* tslint:enable:max-line-length */\n\n /**\n * Subscribe to this Observable and get a Promise resolving on\n * `complete` with the last emission (if any).\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * @method toPromise\n * @param [promiseCtor] a constructor function used to instantiate\n * the Promise\n * @return A Promise that resolves with the last value emit, or\n * rejects on an error. If there were no emissions, Promise\n * resolves with undefined.\n * @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise\n */\n toPromise(promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n let value: T | undefined;\n this.subscribe(\n (x: T) => (value = x),\n (err: any) => reject(err),\n () => resolve(value)\n );\n }) as Promise;\n }\n}\n\n/**\n * Decides between a passed promise constructor from consuming code,\n * A default configured promise constructor, and the native promise\n * constructor and returns it. If nothing can be found, it will throw\n * an error.\n * @param promiseCtor The optional promise constructor to passed by consuming code\n */\nfunction getPromiseCtor(promiseCtor: PromiseConstructorLike | undefined) {\n return promiseCtor ?? config.Promise ?? Promise;\n}\n\nfunction isObserver(value: any): value is Observer {\n return value && isFunction(value.next) && isFunction(value.error) && isFunction(value.complete);\n}\n\nfunction isSubscriber(value: any): value is Subscriber {\n return (value && value instanceof Subscriber) || (isObserver(value) && isSubscription(value));\n}\n", "import { Observable } from '../Observable';\nimport { Subscriber } from '../Subscriber';\nimport { OperatorFunction } from '../types';\nimport { isFunction } from './isFunction';\n\n/**\n * Used to determine if an object is an Observable with a lift function.\n */\nexport function hasLift(source: any): source is { lift: InstanceType['lift'] } {\n return isFunction(source?.lift);\n}\n\n/**\n * Creates an `OperatorFunction`. Used to define operators throughout the library in a concise way.\n * @param init The logic to connect the liftedSource to the subscriber at the moment of subscription.\n */\nexport function operate(\n init: (liftedSource: Observable, subscriber: Subscriber) => (() => void) | void\n): OperatorFunction {\n return (source: Observable) => {\n if (hasLift(source)) {\n return source.lift(function (this: Subscriber, liftedSource: Observable) {\n try {\n return init(liftedSource, this);\n } catch (err) {\n this.error(err);\n }\n });\n }\n throw new TypeError('Unable to lift unknown Observable type');\n };\n}\n", "import { Subscriber } from '../Subscriber';\n\n/**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional teardown logic here. This will only be called on teardown if the\n * subscriber itself is not already closed. This is called after all other teardown logic is executed.\n */\nexport function createOperatorSubscriber(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n onFinalize?: () => void\n): Subscriber {\n return new OperatorSubscriber(destination, onNext, onComplete, onError, onFinalize);\n}\n\n/**\n * A generic helper for allowing operators to be created with a Subscriber and\n * use closures to capture necessary state from the operator function itself.\n */\nexport class OperatorSubscriber extends Subscriber {\n /**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional finalization logic here. This will only be called on finalization if the\n * subscriber itself is not already closed. This is called after all other finalization logic is executed.\n * @param shouldUnsubscribe An optional check to see if an unsubscribe call should truly unsubscribe.\n * NOTE: This currently **ONLY** exists to support the strange behavior of {@link groupBy}, where unsubscription\n * to the resulting observable does not actually disconnect from the source if there are active subscriptions\n * to any grouped observable. (DO NOT EXPOSE OR USE EXTERNALLY!!!)\n */\n constructor(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n private onFinalize?: () => void,\n private shouldUnsubscribe?: () => boolean\n ) {\n // It's important - for performance reasons - that all of this class's\n // members are initialized and that they are always initialized in the same\n // order. This will ensure that all OperatorSubscriber instances have the\n // same hidden class in V8. This, in turn, will help keep the number of\n // hidden classes involved in property accesses within the base class as\n // low as possible. If the number of hidden classes involved exceeds four,\n // the property accesses will become megamorphic and performance penalties\n // will be incurred - i.e. inline caches won't be used.\n //\n // The reasons for ensuring all instances have the same hidden class are\n // further discussed in this blog post from Benedikt Meurer:\n // https://benediktmeurer.de/2018/03/23/impact-of-polymorphism-on-component-based-frameworks-like-react/\n super(destination);\n this._next = onNext\n ? function (this: OperatorSubscriber, value: T) {\n try {\n onNext(value);\n } catch (err) {\n destination.error(err);\n }\n }\n : super._next;\n this._error = onError\n ? function (this: OperatorSubscriber, err: any) {\n try {\n onError(err);\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._error;\n this._complete = onComplete\n ? function (this: OperatorSubscriber) {\n try {\n onComplete();\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._complete;\n }\n\n unsubscribe() {\n if (!this.shouldUnsubscribe || this.shouldUnsubscribe()) {\n const { closed } = this;\n super.unsubscribe();\n // Execute additional teardown if we have any and we didn't already do so.\n !closed && this.onFinalize?.();\n }\n }\n}\n", "import { Subscription } from '../Subscription';\n\ninterface AnimationFrameProvider {\n schedule(callback: FrameRequestCallback): Subscription;\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n delegate:\n | {\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n }\n | undefined;\n}\n\nexport const animationFrameProvider: AnimationFrameProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n schedule(callback) {\n let request = requestAnimationFrame;\n let cancel: typeof cancelAnimationFrame | undefined = cancelAnimationFrame;\n const { delegate } = animationFrameProvider;\n if (delegate) {\n request = delegate.requestAnimationFrame;\n cancel = delegate.cancelAnimationFrame;\n }\n const handle = request((timestamp) => {\n // Clear the cancel function. The request has been fulfilled, so\n // attempting to cancel the request upon unsubscription would be\n // pointless.\n cancel = undefined;\n callback(timestamp);\n });\n return new Subscription(() => cancel?.(handle));\n },\n requestAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.requestAnimationFrame || requestAnimationFrame)(...args);\n },\n cancelAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.cancelAnimationFrame || cancelAnimationFrame)(...args);\n },\n delegate: undefined,\n};\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface ObjectUnsubscribedError extends Error {}\n\nexport interface ObjectUnsubscribedErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (): ObjectUnsubscribedError;\n}\n\n/**\n * An error thrown when an action is invalid because the object has been\n * unsubscribed.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n *\n * @class ObjectUnsubscribedError\n */\nexport const ObjectUnsubscribedError: ObjectUnsubscribedErrorCtor = createErrorClass(\n (_super) =>\n function ObjectUnsubscribedErrorImpl(this: any) {\n _super(this);\n this.name = 'ObjectUnsubscribedError';\n this.message = 'object unsubscribed';\n }\n);\n", "import { Operator } from './Operator';\nimport { Observable } from './Observable';\nimport { Subscriber } from './Subscriber';\nimport { Subscription, EMPTY_SUBSCRIPTION } from './Subscription';\nimport { Observer, SubscriptionLike, TeardownLogic } from './types';\nimport { ObjectUnsubscribedError } from './util/ObjectUnsubscribedError';\nimport { arrRemove } from './util/arrRemove';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A Subject is a special type of Observable that allows values to be\n * multicasted to many Observers. Subjects are like EventEmitters.\n *\n * Every Subject is an Observable and an Observer. You can subscribe to a\n * Subject, and you can call next to feed values as well as error and complete.\n */\nexport class Subject extends Observable implements SubscriptionLike {\n closed = false;\n\n private currentObservers: Observer[] | null = null;\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n observers: Observer[] = [];\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n isStopped = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n hasError = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n thrownError: any = null;\n\n /**\n * Creates a \"subject\" by basically gluing an observer to an observable.\n *\n * @nocollapse\n * @deprecated Recommended you do not use. Will be removed at some point in the future. Plans for replacement still under discussion.\n */\n static create: (...args: any[]) => any = (destination: Observer, source: Observable): AnonymousSubject => {\n return new AnonymousSubject(destination, source);\n };\n\n constructor() {\n // NOTE: This must be here to obscure Observable's constructor.\n super();\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n lift(operator: Operator): Observable {\n const subject = new AnonymousSubject(this, this);\n subject.operator = operator as any;\n return subject as any;\n }\n\n /** @internal */\n protected _throwIfClosed() {\n if (this.closed) {\n throw new ObjectUnsubscribedError();\n }\n }\n\n next(value: T) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n if (!this.currentObservers) {\n this.currentObservers = Array.from(this.observers);\n }\n for (const observer of this.currentObservers) {\n observer.next(value);\n }\n }\n });\n }\n\n error(err: any) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.hasError = this.isStopped = true;\n this.thrownError = err;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.error(err);\n }\n }\n });\n }\n\n complete() {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.isStopped = true;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.complete();\n }\n }\n });\n }\n\n unsubscribe() {\n this.isStopped = this.closed = true;\n this.observers = this.currentObservers = null!;\n }\n\n get observed() {\n return this.observers?.length > 0;\n }\n\n /** @internal */\n protected _trySubscribe(subscriber: Subscriber): TeardownLogic {\n this._throwIfClosed();\n return super._trySubscribe(subscriber);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._checkFinalizedStatuses(subscriber);\n return this._innerSubscribe(subscriber);\n }\n\n /** @internal */\n protected _innerSubscribe(subscriber: Subscriber) {\n const { hasError, isStopped, observers } = this;\n if (hasError || isStopped) {\n return EMPTY_SUBSCRIPTION;\n }\n this.currentObservers = null;\n observers.push(subscriber);\n return new Subscription(() => {\n this.currentObservers = null;\n arrRemove(observers, subscriber);\n });\n }\n\n /** @internal */\n protected _checkFinalizedStatuses(subscriber: Subscriber) {\n const { hasError, thrownError, isStopped } = this;\n if (hasError) {\n subscriber.error(thrownError);\n } else if (isStopped) {\n subscriber.complete();\n }\n }\n\n /**\n * Creates a new Observable with this Subject as the source. You can do this\n * to create custom Observer-side logic of the Subject and conceal it from\n * code that uses the Observable.\n * @return {Observable} Observable that the Subject casts to\n */\n asObservable(): Observable {\n const observable: any = new Observable();\n observable.source = this;\n return observable;\n }\n}\n\n/**\n * @class AnonymousSubject\n */\nexport class AnonymousSubject extends Subject {\n constructor(\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n public destination?: Observer,\n source?: Observable\n ) {\n super();\n this.source = source;\n }\n\n next(value: T) {\n this.destination?.next?.(value);\n }\n\n error(err: any) {\n this.destination?.error?.(err);\n }\n\n complete() {\n this.destination?.complete?.();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n return this.source?.subscribe(subscriber) ?? EMPTY_SUBSCRIPTION;\n }\n}\n", "import { Subject } from './Subject';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\n\n/**\n * A variant of Subject that requires an initial value and emits its current\n * value whenever it is subscribed to.\n *\n * @class BehaviorSubject\n */\nexport class BehaviorSubject extends Subject {\n constructor(private _value: T) {\n super();\n }\n\n get value(): T {\n return this.getValue();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n const subscription = super._subscribe(subscriber);\n !subscription.closed && subscriber.next(this._value);\n return subscription;\n }\n\n getValue(): T {\n const { hasError, thrownError, _value } = this;\n if (hasError) {\n throw thrownError;\n }\n this._throwIfClosed();\n return _value;\n }\n\n next(value: T): void {\n super.next((this._value = value));\n }\n}\n", "import { TimestampProvider } from '../types';\n\ninterface DateTimestampProvider extends TimestampProvider {\n delegate: TimestampProvider | undefined;\n}\n\nexport const dateTimestampProvider: DateTimestampProvider = {\n now() {\n // Use the variable rather than `this` so that the function can be called\n // without being bound to the provider.\n return (dateTimestampProvider.delegate || Date).now();\n },\n delegate: undefined,\n};\n", "import { Subject } from './Subject';\nimport { TimestampProvider } from './types';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * A variant of {@link Subject} that \"replays\" old values to new subscribers by emitting them when they first subscribe.\n *\n * `ReplaySubject` has an internal buffer that will store a specified number of values that it has observed. Like `Subject`,\n * `ReplaySubject` \"observes\" values by having them passed to its `next` method. When it observes a value, it will store that\n * value for a time determined by the configuration of the `ReplaySubject`, as passed to its constructor.\n *\n * When a new subscriber subscribes to the `ReplaySubject` instance, it will synchronously emit all values in its buffer in\n * a First-In-First-Out (FIFO) manner. The `ReplaySubject` will also complete, if it has observed completion; and it will\n * error if it has observed an error.\n *\n * There are two main configuration items to be concerned with:\n *\n * 1. `bufferSize` - This will determine how many items are stored in the buffer, defaults to infinite.\n * 2. `windowTime` - The amount of time to hold a value in the buffer before removing it from the buffer.\n *\n * Both configurations may exist simultaneously. So if you would like to buffer a maximum of 3 values, as long as the values\n * are less than 2 seconds old, you could do so with a `new ReplaySubject(3, 2000)`.\n *\n * ### Differences with BehaviorSubject\n *\n * `BehaviorSubject` is similar to `new ReplaySubject(1)`, with a couple of exceptions:\n *\n * 1. `BehaviorSubject` comes \"primed\" with a single value upon construction.\n * 2. `ReplaySubject` will replay values, even after observing an error, where `BehaviorSubject` will not.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n * @see {@link shareReplay}\n */\nexport class ReplaySubject extends Subject {\n private _buffer: (T | number)[] = [];\n private _infiniteTimeWindow = true;\n\n /**\n * @param bufferSize The size of the buffer to replay on subscription\n * @param windowTime The amount of time the buffered items will stay buffered\n * @param timestampProvider An object with a `now()` method that provides the current timestamp. This is used to\n * calculate the amount of time something has been buffered.\n */\n constructor(\n private _bufferSize = Infinity,\n private _windowTime = Infinity,\n private _timestampProvider: TimestampProvider = dateTimestampProvider\n ) {\n super();\n this._infiniteTimeWindow = _windowTime === Infinity;\n this._bufferSize = Math.max(1, _bufferSize);\n this._windowTime = Math.max(1, _windowTime);\n }\n\n next(value: T): void {\n const { isStopped, _buffer, _infiniteTimeWindow, _timestampProvider, _windowTime } = this;\n if (!isStopped) {\n _buffer.push(value);\n !_infiniteTimeWindow && _buffer.push(_timestampProvider.now() + _windowTime);\n }\n this._trimBuffer();\n super.next(value);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._trimBuffer();\n\n const subscription = this._innerSubscribe(subscriber);\n\n const { _infiniteTimeWindow, _buffer } = this;\n // We use a copy here, so reentrant code does not mutate our array while we're\n // emitting it to a new subscriber.\n const copy = _buffer.slice();\n for (let i = 0; i < copy.length && !subscriber.closed; i += _infiniteTimeWindow ? 1 : 2) {\n subscriber.next(copy[i] as T);\n }\n\n this._checkFinalizedStatuses(subscriber);\n\n return subscription;\n }\n\n private _trimBuffer() {\n const { _bufferSize, _timestampProvider, _buffer, _infiniteTimeWindow } = this;\n // If we don't have an infinite buffer size, and we're over the length,\n // use splice to truncate the old buffer values off. Note that we have to\n // double the size for instances where we're not using an infinite time window\n // because we're storing the values and the timestamps in the same array.\n const adjustedBufferSize = (_infiniteTimeWindow ? 1 : 2) * _bufferSize;\n _bufferSize < Infinity && adjustedBufferSize < _buffer.length && _buffer.splice(0, _buffer.length - adjustedBufferSize);\n\n // Now, if we're not in an infinite time window, remove all values where the time is\n // older than what is allowed.\n if (!_infiniteTimeWindow) {\n const now = _timestampProvider.now();\n let last = 0;\n // Search the array for the first timestamp that isn't expired and\n // truncate the buffer up to that point.\n for (let i = 1; i < _buffer.length && (_buffer[i] as number) <= now; i += 2) {\n last = i;\n }\n last && _buffer.splice(0, last + 1);\n }\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Subscription } from '../Subscription';\nimport { SchedulerAction } from '../types';\n\n/**\n * A unit of work to be executed in a `scheduler`. An action is typically\n * created from within a {@link SchedulerLike} and an RxJS user does not need to concern\n * themselves about creating and manipulating an Action.\n *\n * ```ts\n * class Action extends Subscription {\n * new (scheduler: Scheduler, work: (state?: T) => void);\n * schedule(state?: T, delay: number = 0): Subscription;\n * }\n * ```\n *\n * @class Action\n */\nexport class Action extends Subscription {\n constructor(scheduler: Scheduler, work: (this: SchedulerAction, state?: T) => void) {\n super();\n }\n /**\n * Schedules this action on its parent {@link SchedulerLike} for execution. May be passed\n * some context object, `state`. May happen at some point in the future,\n * according to the `delay` parameter, if specified.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler.\n * @return {void}\n */\n public schedule(state?: T, delay: number = 0): Subscription {\n return this;\n }\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetIntervalFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearIntervalFunction = (handle: TimerHandle) => void;\n\ninterface IntervalProvider {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n delegate:\n | {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n }\n | undefined;\n}\n\nexport const intervalProvider: IntervalProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setInterval(handler: () => void, timeout?: number, ...args) {\n const { delegate } = intervalProvider;\n if (delegate?.setInterval) {\n return delegate.setInterval(handler, timeout, ...args);\n }\n return setInterval(handler, timeout, ...args);\n },\n clearInterval(handle) {\n const { delegate } = intervalProvider;\n return (delegate?.clearInterval || clearInterval)(handle as any);\n },\n delegate: undefined,\n};\n", "import { Action } from './Action';\nimport { SchedulerAction } from '../types';\nimport { Subscription } from '../Subscription';\nimport { AsyncScheduler } from './AsyncScheduler';\nimport { intervalProvider } from './intervalProvider';\nimport { arrRemove } from '../util/arrRemove';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncAction extends Action {\n public id: TimerHandle | undefined;\n public state?: T;\n // @ts-ignore: Property has no initializer and is not definitely assigned\n public delay: number;\n protected pending: boolean = false;\n\n constructor(protected scheduler: AsyncScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (this.closed) {\n return this;\n }\n\n // Always replace the current state with the new state.\n this.state = state;\n\n const id = this.id;\n const scheduler = this.scheduler;\n\n //\n // Important implementation note:\n //\n // Actions only execute once by default, unless rescheduled from within the\n // scheduled callback. This allows us to implement single and repeat\n // actions via the same code path, without adding API surface area, as well\n // as mimic traditional recursion but across asynchronous boundaries.\n //\n // However, JS runtimes and timers distinguish between intervals achieved by\n // serial `setTimeout` calls vs. a single `setInterval` call. An interval of\n // serial `setTimeout` calls can be individually delayed, which delays\n // scheduling the next `setTimeout`, and so on. `setInterval` attempts to\n // guarantee the interval callback will be invoked more precisely to the\n // interval period, regardless of load.\n //\n // Therefore, we use `setInterval` to schedule single and repeat actions.\n // If the action reschedules itself with the same delay, the interval is not\n // canceled. If the action doesn't reschedule, or reschedules with a\n // different delay, the interval will be canceled after scheduled callback\n // execution.\n //\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, delay);\n }\n\n // Set the pending flag indicating that this action has been scheduled, or\n // has recursively rescheduled itself.\n this.pending = true;\n\n this.delay = delay;\n // If this action has already an async Id, don't request a new one.\n this.id = this.id ?? this.requestAsyncId(scheduler, this.id, delay);\n\n return this;\n }\n\n protected requestAsyncId(scheduler: AsyncScheduler, _id?: TimerHandle, delay: number = 0): TimerHandle {\n return intervalProvider.setInterval(scheduler.flush.bind(scheduler, this), delay);\n }\n\n protected recycleAsyncId(_scheduler: AsyncScheduler, id?: TimerHandle, delay: number | null = 0): TimerHandle | undefined {\n // If this action is rescheduled with the same delay time, don't clear the interval id.\n if (delay != null && this.delay === delay && this.pending === false) {\n return id;\n }\n // Otherwise, if the action's delay time is different from the current delay,\n // or the action has been rescheduled before it's executed, clear the interval id\n if (id != null) {\n intervalProvider.clearInterval(id);\n }\n\n return undefined;\n }\n\n /**\n * Immediately executes this action and the `work` it contains.\n * @return {any}\n */\n public execute(state: T, delay: number): any {\n if (this.closed) {\n return new Error('executing a cancelled action');\n }\n\n this.pending = false;\n const error = this._execute(state, delay);\n if (error) {\n return error;\n } else if (this.pending === false && this.id != null) {\n // Dequeue if the action didn't reschedule itself. Don't call\n // unsubscribe(), because the action could reschedule later.\n // For example:\n // ```\n // scheduler.schedule(function doWork(counter) {\n // /* ... I'm a busy worker bee ... */\n // var originalAction = this;\n // /* wait 100ms before rescheduling the action */\n // setTimeout(function () {\n // originalAction.schedule(counter + 1);\n // }, 100);\n // }, 1000);\n // ```\n this.id = this.recycleAsyncId(this.scheduler, this.id, null);\n }\n }\n\n protected _execute(state: T, _delay: number): any {\n let errored: boolean = false;\n let errorValue: any;\n try {\n this.work(state);\n } catch (e) {\n errored = true;\n // HACK: Since code elsewhere is relying on the \"truthiness\" of the\n // return here, we can't have it return \"\" or 0 or false.\n // TODO: Clean this up when we refactor schedulers mid-version-8 or so.\n errorValue = e ? e : new Error('Scheduled action threw falsy error');\n }\n if (errored) {\n this.unsubscribe();\n return errorValue;\n }\n }\n\n unsubscribe() {\n if (!this.closed) {\n const { id, scheduler } = this;\n const { actions } = scheduler;\n\n this.work = this.state = this.scheduler = null!;\n this.pending = false;\n\n arrRemove(actions, this);\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, null);\n }\n\n this.delay = null!;\n super.unsubscribe();\n }\n }\n}\n", "import { Action } from './scheduler/Action';\nimport { Subscription } from './Subscription';\nimport { SchedulerLike, SchedulerAction } from './types';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * An execution context and a data structure to order tasks and schedule their\n * execution. Provides a notion of (potentially virtual) time, through the\n * `now()` getter method.\n *\n * Each unit of work in a Scheduler is called an `Action`.\n *\n * ```ts\n * class Scheduler {\n * now(): number;\n * schedule(work, delay?, state?): Subscription;\n * }\n * ```\n *\n * @class Scheduler\n * @deprecated Scheduler is an internal implementation detail of RxJS, and\n * should not be used directly. Rather, create your own class and implement\n * {@link SchedulerLike}. Will be made internal in v8.\n */\nexport class Scheduler implements SchedulerLike {\n public static now: () => number = dateTimestampProvider.now;\n\n constructor(private schedulerActionCtor: typeof Action, now: () => number = Scheduler.now) {\n this.now = now;\n }\n\n /**\n * A getter method that returns a number representing the current time\n * (at the time this function was called) according to the scheduler's own\n * internal clock.\n * @return {number} A number that represents the current time. May or may not\n * have a relation to wall-clock time. May or may not refer to a time unit\n * (e.g. milliseconds).\n */\n public now: () => number;\n\n /**\n * Schedules a function, `work`, for execution. May happen at some point in\n * the future, according to the `delay` parameter, if specified. May be passed\n * some context object, `state`, which will be passed to the `work` function.\n *\n * The given arguments will be processed an stored as an Action object in a\n * queue of actions.\n *\n * @param {function(state: ?T): ?Subscription} work A function representing a\n * task, or some unit of work to be executed by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler itself.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @return {Subscription} A subscription in order to be able to unsubscribe\n * the scheduled work.\n */\n public schedule(work: (this: SchedulerAction, state?: T) => void, delay: number = 0, state?: T): Subscription {\n return new this.schedulerActionCtor(this, work).schedule(state, delay);\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Action } from './Action';\nimport { AsyncAction } from './AsyncAction';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncScheduler extends Scheduler {\n public actions: Array> = [];\n /**\n * A flag to indicate whether the Scheduler is currently executing a batch of\n * queued actions.\n * @type {boolean}\n * @internal\n */\n public _active: boolean = false;\n /**\n * An internal ID used to track the latest asynchronous task such as those\n * coming from `setTimeout`, `setInterval`, `requestAnimationFrame`, and\n * others.\n * @type {any}\n * @internal\n */\n public _scheduled: TimerHandle | undefined;\n\n constructor(SchedulerAction: typeof Action, now: () => number = Scheduler.now) {\n super(SchedulerAction, now);\n }\n\n public flush(action: AsyncAction): void {\n const { actions } = this;\n\n if (this._active) {\n actions.push(action);\n return;\n }\n\n let error: any;\n this._active = true;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions.shift()!)); // exhaust the scheduler queue\n\n this._active = false;\n\n if (error) {\n while ((action = actions.shift()!)) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\n/**\n *\n * Async Scheduler\n *\n * Schedule task as if you used setTimeout(task, duration)\n *\n * `async` scheduler schedules tasks asynchronously, by putting them on the JavaScript\n * event loop queue. It is best used to delay tasks in time or to schedule tasks repeating\n * in intervals.\n *\n * If you just want to \"defer\" task, that is to perform it right after currently\n * executing synchronous code ends (commonly achieved by `setTimeout(deferredTask, 0)`),\n * better choice will be the {@link asapScheduler} scheduler.\n *\n * ## Examples\n * Use async scheduler to delay task\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * const task = () => console.log('it works!');\n *\n * asyncScheduler.schedule(task, 2000);\n *\n * // After 2 seconds logs:\n * // \"it works!\"\n * ```\n *\n * Use async scheduler to repeat task in intervals\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * function task(state) {\n * console.log(state);\n * this.schedule(state + 1, 1000); // `this` references currently executing Action,\n * // which we reschedule with new state and delay\n * }\n *\n * asyncScheduler.schedule(task, 3000, 0);\n *\n * // Logs:\n * // 0 after 3s\n * // 1 after 4s\n * // 2 after 5s\n * // 3 after 6s\n * ```\n */\n\nexport const asyncScheduler = new AsyncScheduler(AsyncAction);\n\n/**\n * @deprecated Renamed to {@link asyncScheduler}. Will be removed in v8.\n */\nexport const async = asyncScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { Subscription } from '../Subscription';\nimport { QueueScheduler } from './QueueScheduler';\nimport { SchedulerAction } from '../types';\nimport { TimerHandle } from './timerHandle';\n\nexport class QueueAction extends AsyncAction {\n constructor(protected scheduler: QueueScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (delay > 0) {\n return super.schedule(state, delay);\n }\n this.delay = delay;\n this.state = state;\n this.scheduler.flush(this);\n return this;\n }\n\n public execute(state: T, delay: number): any {\n return delay > 0 || this.closed ? super.execute(state, delay) : this._execute(state, delay);\n }\n\n protected requestAsyncId(scheduler: QueueScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n\n if ((delay != null && delay > 0) || (delay == null && this.delay > 0)) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n\n // Otherwise flush the scheduler starting with this action.\n scheduler.flush(this);\n\n // HACK: In the past, this was returning `void`. However, `void` isn't a valid\n // `TimerHandle`, and generally the return value here isn't really used. So the\n // compromise is to return `0` which is both \"falsy\" and a valid `TimerHandle`,\n // as opposed to refactoring every other instanceo of `requestAsyncId`.\n return 0;\n }\n}\n", "import { AsyncScheduler } from './AsyncScheduler';\n\nexport class QueueScheduler extends AsyncScheduler {\n}\n", "import { QueueAction } from './QueueAction';\nimport { QueueScheduler } from './QueueScheduler';\n\n/**\n *\n * Queue Scheduler\n *\n * Put every next task on a queue, instead of executing it immediately\n *\n * `queue` scheduler, when used with delay, behaves the same as {@link asyncScheduler} scheduler.\n *\n * When used without delay, it schedules given task synchronously - executes it right when\n * it is scheduled. However when called recursively, that is when inside the scheduled task,\n * another task is scheduled with queue scheduler, instead of executing immediately as well,\n * that task will be put on a queue and wait for current one to finish.\n *\n * This means that when you execute task with `queue` scheduler, you are sure it will end\n * before any other task scheduled with that scheduler will start.\n *\n * ## Examples\n * Schedule recursively first, then do something\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(() => {\n * queueScheduler.schedule(() => console.log('second')); // will not happen now, but will be put on a queue\n *\n * console.log('first');\n * });\n *\n * // Logs:\n * // \"first\"\n * // \"second\"\n * ```\n *\n * Reschedule itself recursively\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(function(state) {\n * if (state !== 0) {\n * console.log('before', state);\n * this.schedule(state - 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * console.log('after', state);\n * }\n * }, 0, 3);\n *\n * // In scheduler that runs recursively, you would expect:\n * // \"before\", 3\n * // \"before\", 2\n * // \"before\", 1\n * // \"after\", 1\n * // \"after\", 2\n * // \"after\", 3\n *\n * // But with queue it logs:\n * // \"before\", 3\n * // \"after\", 3\n * // \"before\", 2\n * // \"after\", 2\n * // \"before\", 1\n * // \"after\", 1\n * ```\n */\n\nexport const queueScheduler = new QueueScheduler(QueueAction);\n\n/**\n * @deprecated Renamed to {@link queueScheduler}. Will be removed in v8.\n */\nexport const queue = queueScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\nimport { SchedulerAction } from '../types';\nimport { animationFrameProvider } from './animationFrameProvider';\nimport { TimerHandle } from './timerHandle';\n\nexport class AnimationFrameAction extends AsyncAction {\n constructor(protected scheduler: AnimationFrameScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n protected requestAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay is greater than 0, request as an async action.\n if (delay !== null && delay > 0) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n // Push the action to the end of the scheduler queue.\n scheduler.actions.push(this);\n // If an animation frame has already been requested, don't request another\n // one. If an animation frame hasn't been requested yet, request one. Return\n // the current animation frame request id.\n return scheduler._scheduled || (scheduler._scheduled = animationFrameProvider.requestAnimationFrame(() => scheduler.flush(undefined)));\n }\n\n protected recycleAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle | undefined {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n if (delay != null ? delay > 0 : this.delay > 0) {\n return super.recycleAsyncId(scheduler, id, delay);\n }\n // If the scheduler queue has no remaining actions with the same async id,\n // cancel the requested animation frame and set the scheduled flag to\n // undefined so the next AnimationFrameAction will request its own.\n const { actions } = scheduler;\n if (id != null && actions[actions.length - 1]?.id !== id) {\n animationFrameProvider.cancelAnimationFrame(id as number);\n scheduler._scheduled = undefined;\n }\n // Return undefined so the action knows to request a new async id if it's rescheduled.\n return undefined;\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\nexport class AnimationFrameScheduler extends AsyncScheduler {\n public flush(action?: AsyncAction): void {\n this._active = true;\n // The async id that effects a call to flush is stored in _scheduled.\n // Before executing an action, it's necessary to check the action's async\n // id to determine whether it's supposed to be executed in the current\n // flush.\n // Previous implementations of this method used a count to determine this,\n // but that was unsound, as actions that are unsubscribed - i.e. cancelled -\n // are removed from the actions array and that can shift actions that are\n // scheduled to be executed in a subsequent flush into positions at which\n // they are executed within the current flush.\n const flushId = this._scheduled;\n this._scheduled = undefined;\n\n const { actions } = this;\n let error: any;\n action = action || actions.shift()!;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions[0]) && action.id === flushId && actions.shift());\n\n this._active = false;\n\n if (error) {\n while ((action = actions[0]) && action.id === flushId && actions.shift()) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AnimationFrameAction } from './AnimationFrameAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\n\n/**\n *\n * Animation Frame Scheduler\n *\n * Perform task when `window.requestAnimationFrame` would fire\n *\n * When `animationFrame` scheduler is used with delay, it will fall back to {@link asyncScheduler} scheduler\n * behaviour.\n *\n * Without delay, `animationFrame` scheduler can be used to create smooth browser animations.\n * It makes sure scheduled task will happen just before next browser content repaint,\n * thus performing animations as efficiently as possible.\n *\n * ## Example\n * Schedule div height animation\n * ```ts\n * // html:
\n * import { animationFrameScheduler } from 'rxjs';\n *\n * const div = document.querySelector('div');\n *\n * animationFrameScheduler.schedule(function(height) {\n * div.style.height = height + \"px\";\n *\n * this.schedule(height + 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * }, 0, 0);\n *\n * // You will see a div element growing in height\n * ```\n */\n\nexport const animationFrameScheduler = new AnimationFrameScheduler(AnimationFrameAction);\n\n/**\n * @deprecated Renamed to {@link animationFrameScheduler}. Will be removed in v8.\n */\nexport const animationFrame = animationFrameScheduler;\n", "import { Observable } from '../Observable';\nimport { SchedulerLike } from '../types';\n\n/**\n * A simple Observable that emits no items to the Observer and immediately\n * emits a complete notification.\n *\n * Just emits 'complete', and nothing else.\n *\n * ![](empty.png)\n *\n * A simple Observable that only emits the complete notification. It can be used\n * for composing with other Observables, such as in a {@link mergeMap}.\n *\n * ## Examples\n *\n * Log complete notification\n *\n * ```ts\n * import { EMPTY } from 'rxjs';\n *\n * EMPTY.subscribe({\n * next: () => console.log('Next'),\n * complete: () => console.log('Complete!')\n * });\n *\n * // Outputs\n * // Complete!\n * ```\n *\n * Emit the number 7, then complete\n *\n * ```ts\n * import { EMPTY, startWith } from 'rxjs';\n *\n * const result = EMPTY.pipe(startWith(7));\n * result.subscribe(x => console.log(x));\n *\n * // Outputs\n * // 7\n * ```\n *\n * Map and flatten only odd numbers to the sequence `'a'`, `'b'`, `'c'`\n *\n * ```ts\n * import { interval, mergeMap, of, EMPTY } from 'rxjs';\n *\n * const interval$ = interval(1000);\n * const result = interval$.pipe(\n * mergeMap(x => x % 2 === 1 ? of('a', 'b', 'c') : EMPTY),\n * );\n * result.subscribe(x => console.log(x));\n *\n * // Results in the following to the console:\n * // x is equal to the count on the interval, e.g. (0, 1, 2, 3, ...)\n * // x will occur every 1000ms\n * // if x % 2 is equal to 1, print a, b, c (each on its own)\n * // if x % 2 is not equal to 1, nothing will be output\n * ```\n *\n * @see {@link Observable}\n * @see {@link NEVER}\n * @see {@link of}\n * @see {@link throwError}\n */\nexport const EMPTY = new Observable((subscriber) => subscriber.complete());\n\n/**\n * @param scheduler A {@link SchedulerLike} to use for scheduling\n * the emission of the complete notification.\n * @deprecated Replaced with the {@link EMPTY} constant or {@link scheduled} (e.g. `scheduled([], scheduler)`). Will be removed in v8.\n */\nexport function empty(scheduler?: SchedulerLike) {\n return scheduler ? emptyScheduled(scheduler) : EMPTY;\n}\n\nfunction emptyScheduled(scheduler: SchedulerLike) {\n return new Observable((subscriber) => scheduler.schedule(() => subscriber.complete()));\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport function isScheduler(value: any): value is SchedulerLike {\n return value && isFunction(value.schedule);\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\nimport { isScheduler } from './isScheduler';\n\nfunction last(arr: T[]): T | undefined {\n return arr[arr.length - 1];\n}\n\nexport function popResultSelector(args: any[]): ((...args: unknown[]) => unknown) | undefined {\n return isFunction(last(args)) ? args.pop() : undefined;\n}\n\nexport function popScheduler(args: any[]): SchedulerLike | undefined {\n return isScheduler(last(args)) ? args.pop() : undefined;\n}\n\nexport function popNumber(args: any[], defaultValue: number): number {\n return typeof last(args) === 'number' ? args.pop()! : defaultValue;\n}\n", "export const isArrayLike = ((x: any): x is ArrayLike => x && typeof x.length === 'number' && typeof x !== 'function');", "import { isFunction } from \"./isFunction\";\n\n/**\n * Tests to see if the object is \"thennable\".\n * @param value the object to test\n */\nexport function isPromise(value: any): value is PromiseLike {\n return isFunction(value?.then);\n}\n", "import { InteropObservable } from '../types';\nimport { observable as Symbol_observable } from '../symbol/observable';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being Observable (but not necessary an Rx Observable) */\nexport function isInteropObservable(input: any): input is InteropObservable {\n return isFunction(input[Symbol_observable]);\n}\n", "import { isFunction } from './isFunction';\n\nexport function isAsyncIterable(obj: any): obj is AsyncIterable {\n return Symbol.asyncIterator && isFunction(obj?.[Symbol.asyncIterator]);\n}\n", "/**\n * Creates the TypeError to throw if an invalid object is passed to `from` or `scheduled`.\n * @param input The object that was passed.\n */\nexport function createInvalidObservableTypeError(input: any) {\n // TODO: We should create error codes that can be looked up, so this can be less verbose.\n return new TypeError(\n `You provided ${\n input !== null && typeof input === 'object' ? 'an invalid object' : `'${input}'`\n } where a stream was expected. You can provide an Observable, Promise, ReadableStream, Array, AsyncIterable, or Iterable.`\n );\n}\n", "export function getSymbolIterator(): symbol {\n if (typeof Symbol !== 'function' || !Symbol.iterator) {\n return '@@iterator' as any;\n }\n\n return Symbol.iterator;\n}\n\nexport const iterator = getSymbolIterator();\n", "import { iterator as Symbol_iterator } from '../symbol/iterator';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being an Iterable */\nexport function isIterable(input: any): input is Iterable {\n return isFunction(input?.[Symbol_iterator]);\n}\n", "import { ReadableStreamLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport async function* readableStreamLikeToAsyncGenerator(readableStream: ReadableStreamLike): AsyncGenerator {\n const reader = readableStream.getReader();\n try {\n while (true) {\n const { value, done } = await reader.read();\n if (done) {\n return;\n }\n yield value!;\n }\n } finally {\n reader.releaseLock();\n }\n}\n\nexport function isReadableStreamLike(obj: any): obj is ReadableStreamLike {\n // We don't want to use instanceof checks because they would return\n // false for instances from another Realm, like an + + + + + + + + + + + + + + + + + + + + + + + + + + +

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支持识别语言

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简介

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  • 因为本项目依托于PaddleOCR，所以理论上PaddleOCR支持识别的模型，RapidOCR都是支持的。
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中英文检测和识别（可以直接使用）

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  • 因为中英文是最为常用的模型，所以在打包时，就默认将中英文识别的模型放到了rapidocr_onnxruntime和rapidocr_openvino中，直接pip安装即可使用。
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其他语种检测和识别（需要转换）

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  • PaddleOCR中已有文本检测模型列表：link
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  • PaddleOCR已有文本识别模型列表： link
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  • 除了slim量化版的模型，上面链接中的其他模型都可以转换为ONNX格式，通过RapidOCR快速部署。
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转换教程

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衍生项目(偏工程)

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RapidStructure ：版面分析

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RapidOCRServer：RapidOCR HTTP服务/win32程序/易语言编写

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PaddleOCRModelConvert： 模型自助转换

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TextDetMetric：文本检测模型评估

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RapidOCRPDF：解析PDF文件

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RapidVideOCR：基于RapidOCR，提取视频中的硬字幕

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垂直项目(偏学术)

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引言

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  • 以下几个方向，每个都是比较独立的方向，但是却和OCR有着千丝万缕的关系，关于它们的资料就像散落在天空中的星星一般，散发着微弱的光芒，这里要做的就是将这些点点光芒聚集起来。
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  • 这里将会汇总出以下几个OCR周边项目的一些文档和资源，包括学术动态和一些工程化代码。
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  • 欢迎各位小伙伴提供PR。
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Visual Text Rendering

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阅读序列抽取

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数据集：

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手写体识别

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TODO

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手写体公式识别

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TODO

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公式识别

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TODO

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公式检测

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图像中公式检测需求一般出现于文档分析和还原需求中。

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单纯公式检测任务包括对行内公式和行间公式的检测。而版面分析任务中，仅有对行间公式的标注，缺乏行内公式标注。如果想要精细化做版面还原，行内公式的检测识别就变得尤为重要。

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这一块的工作，breezedeus做得比较好，详情可以参见其博客：Pix2Text (P2T) 新版公式检测模型。

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有关数据集：IBEM 和中文 CnMFD_Dataset

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发票识别

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图像文字擦除

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文档增强

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  • DocDiff（Github）: 文档增强模型，可以用于文档去模糊、文档去噪、文档二值化、文档去水印和印章等任务。
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文档图像矫正

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版面分析

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  • 相关论文和帖子： +
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  • 相关工程： +
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    数据集汇总：

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      英文版面分析数据集：

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      • PubLayNet: IBM构建，34万张图像，分为5类：text, title list table figure。
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      • DocBank：微软亚洲研究院构建，50万英文文档图像，分为12类：摘要、作者、标题、公式、图形、页脚、列表、段落、参考、节标题、表格和文章标题。
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      • D4LA: 阿里通义实验室构建，11092张图像，12个文档种类，27个类别，手工标注。详情可参见论文Vision Grid Transformer for Document Layout Analysis
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      中文版面分析数据集：

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      • CDLA：中文文档版面分析数据集，面向中文文献类（论文）场景，总共6000张（5000训练，1000测试），分为10类：正文、标题、图片、图片标题、表格、表格标题、页眉、页脚、注释和公式。
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表格结构识别

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视频OCR

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卡证OCR

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  • 相关论文和帖子：
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  • 相关工程： +
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  • 数据集汇总：
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    • 暂无，一般这类数据较为敏感，通常都合成假数据来使用。
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印章OCR

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常见问题 (FAQ)

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Q: 为什么我的模型在ONNXRuntime GPU版上比在CPU上还要慢？

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A: 因为OCR任务中输入图像Shape是动态的。每次GPU上都需要重新清空上一次不同Shape的缓存结果。如果输入图像Shape不变的情况下，ONNXRuntime GPU版一般都要比CPU快的。该问题已经提了相关issue（issue #13198）。

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推荐CPU端推理用rapidocr_onnxruntime或者rapidocr_openvino，GPU端用rapidocr_paddle。关于rapidocr_onnxruntime和rapidocr_paddle两者之间推理，可参见：docs

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Q: 请问这个能在32位C#中用嘛?

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A: C#可以32位，要用32位的dll，但nuget上的onnxruntime不支持win7。

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Q: Windows系统下，装完环境之后，运行示例程序之后，报错OSError: [WinError 126] 找不到指定的模組

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A: 原因是Shapely库没有正确安装，如果是在Windows，可以在Shapely whl下载对应的whl包，离线安装即可；另外一种解决办法是用conda安装也可。

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Q: Linux部署python的程序时，import cv2时会报ImportError: ligGL.so.1: cannot open shared object file: No such file or directory?

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A: 解决方法 有两个(来自群友ddeef)：

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  1. 安装opencv-python-headless取代opencv-python;
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  2. 运行sudo apt-get install -y libgl1-mesa-dev
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Q: 询问下，我编译出来的进程在win7下面通过cmd调用，发生了崩溃的情况?

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A: 不支持win7 (by @如果我有時光機)

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Q: 能不能搞个openmmlab类似的那个提取信息的?

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A: 这个目前正在调研测试当中，如果mmocr中关键信息提取效果还可以，后期会考虑整合进来。

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Q: RapidOCR和PaddleOCR是什么关系呢？

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A: RapidOCR是将PaddleOCR的预训练模型转为onnx模型，不依赖paddle框架，方便各个平台部署。

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Q: onnxruntime arm32 有人编译过吗？ 我编译成功了，但是使用的时候libonnxruntime.so👎 error: file not recognized: File format not recognized 应该是版本不匹配

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A: 没遇到过。我是直接在当前平台编译的，我们用的是arm。估计是平台不兼容,建议在本身平台上编译。没遇到过问题。通常出在交叉编译方式下。

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Q: 请问一下c++ demo必须要vs2017及以上版本吗?

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A: 最好用vs2019

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Q: 可以达到百度EasyEdge Free App的效果吗？

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A: edge的模型应该没有开源。百度开源的模型里server det的识别效果可以达到，但是模型比较大。

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Q: 我用c++推理onnx貌似是cpu推理的，gpu没有反应?

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A: 如果想用GPU的话，需要安装onnxruntime-gpu版，自己在onnxruntime的代码中添加EP (execution provider)。我们的定位是通用，只用cpu推理。

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Q: 您好，我想部署下咱们的ocr识别，有提供linux版本的ocr部署包吗?

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A: linux版本的自己编译即可, 可以参考我们的action中的脚本；其实编译非常容易，安装个opencv后，在cmakelists.txt中修改一下onnxruntime的路径即可，具体参考这个： https://github.com/RapidOCR/RapidOCR/blob/main/.github/workflows/make-linux.yml

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Q: onnxruntime编译好的C++库，哪里可以下载到？

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A: 从这里：https://github.com/RapidOCR/OnnxruntimeBuilder/releases/tag/1.7.0

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Q: 目前简单测试环境是 Win10 + Cygwin + gcc + 纯C编程，可以在C程序中直接接入简单OCR功能吗？

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A: 直接使用API就行，API就是由c导出的

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Q: 模型下载地址

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A: 百度网盘 | Google Drive

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Q: onnxruntime 1.7 下出错：onnxruntime::SequentialExecutor::Execute] Non-zero status code returned while running ScatterND node. Name:'ScatterND@1' Status Message: updates

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A: 由于模型只支持onnxruntime=1.5.0导致，请更新模型,下载地址见Q3

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Q: 边缘总有一行文字无法识别，怎么办？

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A: 在 padding 参数中添加一个值 ，默认是0,你可以添加5或10, 甚至更大，直到能识别为止。注意不要添加过大，会浪费内存。

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调优尝试教程

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Note

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以下尝试情况，均已经在在线demo中实现，看完之后，可移步那里去尝试。

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引言

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  • 由于小伙伴们使用OCR的场景多种多样，单一的参数配置往往不能满足要求，这就涉及到基于现有模型，通过调节参数来达到正确识别的目的。
    • +
  • 基本的原则是尽量不去动模型内部，降低使用成本。
    • +
  • 本篇文章就来说说在识别效果不好时，如何去调优。
    • +
  • 因此博客为一家之言，难免会挂一漏万，希望小伙伴多多指出，共同维护这份教程。
    • +
+

常见错例种类

+

本地使用过程中，识别结果：

+
    +
  • 个别字丢失
    • +
  • 个别字识别错误
    • +
+

个别字丢失调优篇

+
    +
  1. +

    查看图像是否shape太小，导致文本检测丢失。

    +
      +
    • 对于长度较长，高度较小的图像，可尝试对该图像高度做上下补充，来减小文字在原始图像中比例，利于文本检测。类似下图这种，左侧一条为原始图像，右侧为上下补边的图像。 +Snipaste_2023-04-09_14-01-45
      • +
    • padding代码参考：
      • +
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    from typing import Tuple
+
+import cv2
+import numpy as np
+
+
+def padding_img(img: np.ndarray,
+                padding_value: Tuple[int, int, int, int],
+                padding_color: Tuple = (0, 0, 0)) -> np.ndarray:
+    padded_img = cv2.copyMakeBorder(img,
+                                    padding_value[0],
+                                    padding_value[1],
+                                    padding_value[2],
+                                    padding_value[3],
+                                    cv2.BORDER_CONSTANT,
+                                    value=padding_color)
+    return padded_img
+
+img = cv2.imread('xxx.jpg')
+
+# padding_value: (top, bottom, left, right)
+# 对该图像上下各补充10像素的白边
+padded_img = padding_img(img, (10, 10, 0, 0), (255, 255, 255))
+
    +
    2. +
  2. +

    将padding之后的图像再次送入RapidOCR中尝试，查看是否仍然出现上述问题。

    +
    3. +
  3. +

    将该图像上传到在线demo中，查看能否复现问题？

    +
    4. +
  4. 如不能复现，着重比对环境是否与在线demo中相关包使用版本不一致情况？
    5. +
  5. +

    在线demo所用的各个包版本情况：

    +
    Python: 3.8
+onnxruntime: 1.14.1
+rapidocr_onnxruntime: 1.2.5
+
    +
    6. +
  6. +

    如能复现，尝试调节在线demo中的三个参数，注意控制变量调节参数

    +
    7. +
  7. 首先调节box_thresh参数，该参数用来控制文本检测部分检测所得框是文本的概率。个别字丢失，一般是单独的字丢失，很大可能是文本检测模型没有检测到该独立的文字。尝试调低box_thresh值，查看是否可以检出丢失的文字。（没有找到合适的例子）
    8. +
  8. 固定box_thresh，调节text_score参数。该参数是控制识别文本结果正确的概率。尝试调低text_score值，查看是否可以识别出丢失的文字。
    9. +
  9. 固定box_thresh和text_score两个参数，调节unclip_ratio参数。该参数用来控制文本检测所得文本框的大小。尝试调大unclip_ratio值，查看是否可以识别出丢失的文字。
    10. +
  10. 如果调节三个参数也不能解决问题，只能尝试server版的文本检测和文本识别模型了。
    11. +
  11. 首先更换server版的文本检测模型，查看是否解决问题
    12. +
  12. 在第1步基础上，更换server版的文本识别模型，查看是否解决问题
    13. +
  13. 尝试更换不同版本模型，来查看效果。具体可在在线demo中尝试
    14. +
+

个别字识别错误调优篇

+

个别字错误的情况，例如：成识别为戍，这种一般是文本识别模型的问题。

+

情况一：轻量中英文模型识别对个别汉字识别错误

+
    +
  1. 尝试padding图像，再重新识别
    2. +
  2. 更换不同版本的识别模型，包括v2、v3和server版尝试
    3. +
+

情况二：轻量中英文模型对个别英文或数字识别错误

+
    +
  1. 更换不同版本的识别模型，包括v2、v3和server版尝试
    2. +
  2. 如果是只识别英文单词和数字，可以更换英文和数字专有模型（en_PP-OCRv3_rec_infer.onnx和en_number_mobile_v2.0_rec_infer.onnx）
    3. +
+ + + + + + + + + + + + + + + + + + + + + + + +

评论

+ + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/blog/2022/10/04/which-inference/index.html b/blog/2022/10/04/which-inference/index.html new file mode 100644 index 00000000..5ce546e8 --- /dev/null +++ b/blog/2022/10/04/which-inference/index.html @@ -0,0 +1,2189 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + OCR推理引擎选择指南 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
+
+ + + +
+ + + + + + +
+ + + + + + + +
+ +
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+ + + + + + + + + + + +
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+ + + +
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+ + + +
+
+
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+ + +
+
+
+
+ + + + + + + +

OCR推理引擎选择指南

+ +

介绍在CPU端和GPU端，OCR模型的推理引擎选择问题。

+ + +

CPU端推理引擎选择

+

☆ 推荐：rapidocr_onnxruntime

+

目前可用的推理库有：rapidocr_onnxruntime，rapidocr_openvino和rapid_paddle。这三个库均可在CPU上推理，除推理引擎不同外，其他接口均相同。

+

其中，因为openvino推理引擎在推理完大图后，所占用的内存不释放问题（issue #11939），不作为优先考虑。

+

paddlepaddle推理引擎，并未测试与其他两个速度差异。但是相比于其CPU版安装包较大，较为臃肿，不利于分发，因此也不作考虑。个人认为，paddlepaddle优势在于对国产机器的适配。

+ + + + + + + + + + + + + + + + + + + + + +
安装包名称大小
paddlepaddle-3.0.0b0-cp312-cp312-win_amd64.whl90.1MB
openvino-2024.2.0-15519-cp312-cp312-win_amd64.whl32.4MB
onnxruntime-1.18.1-cp312-cp312-win_amd64.whl5.6MB
+

汇总如下：

+ + + + + + + + + + + + + + + + + + + + +
推理引擎推理速度更快占用内存更少
rapidocr_onnxruntime✓
rapidocr_openvino✓
+

GPU端推理引擎选择

+

☆ 推荐：rapidocr_paddle

+ +

其他不推荐原因

+

rapidocr_openvino: 出自英特尔，只适配自家GPU，因此，肯定不支持其他家的。如果支持了，烦请留言告知。

+

rapidocr_onnxruntime: onnxruntime-gpu版对动态图支持较差，推理速度很慢。OCR中文本检测部分输入就是动态的。详细参见文档 → link

+

如果遇到内存泄露怎么办？

+

内存泄露问题是什么？

+

内存泄露问题指的是推理引擎在提取较大图像文字时，会申请较多内存。而在提取完成之后，不释放这些临时申请的内存。如果后续再遇到一张更大尺寸的图像，当前内存不够用的话，推理引擎会申请更多内存。同样，这些内存也不会被推理引擎释放。

+

这样，后续如果再遇到更大尺寸图像，则机器很容易内存溢出。

+

哪些推理引擎有这个问题？

+

已知的是OpenVino和PaddlePaddle存在这个问题，ONNXRuntime没有。

+

可能的解决方案

+

总结自群友：多进程/线程 + 定时重启

+ + + + + + + + + + + + + + + + + + + + + + + +

评论

+ + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/blog/2023/10/08/read-dict-onnx/index.html b/blog/2023/10/08/read-dict-onnx/index.html new file mode 100644 index 00000000..52ac3987 --- /dev/null +++ b/blog/2023/10/08/read-dict-onnx/index.html @@ -0,0 +1,2103 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 关于识别模型中字典的读写 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
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+ + +
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+
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+ + + + + + + +

关于识别模型中字典的读写

+ + + +

引言

+

在文本识别时，识别的每一种语言，都有一个对应的字典，用来还原识别的文本内容。例如英文识别模型的字典就是26个英文字母的大小写以及常用符号，中文识别模型的字典一般包括常用汉字、字母和符号等。

+

受启发于issue #42，目前基于ONNXRuntime的推理引擎rapidocr_onnxruntime库已经将字典写入到onnx模型中，无需额外指定字典TXT文件。

+

以下将对这一部分做详细讲解，感兴趣小伙伴，可自行取用。

+

将字典内容写入到ONNX中

+
+

Note

+

在PaddleOCRModelConvert工具中已经将上述操作写到了包中，使用该工具可自动将字典写入到ONNX中。源码位于：link

+
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import onnx
+
+model = onnx.load_model('/path/to/model.onnx')
+
+# 添加dictionary对应的值
+meta = model.metadata_props.add()
+meta.key = 'dictionary'
+meta.value = open('/path/to/ppocr_keys_v1.txt', 'r', -1, 'u8').read()
+
+# 添加shape对应的值
+meta = model.metadata_props.add()
+meta.key = 'shape'
+meta.value = '[3,48,320]'
+
+onnx.save_model(model, '/path/to/model.onnx')
+
+

获取字典内容

+
+

Note

+

该部分已经在rapidocr_onnxruntime上实现，详情参见：link

+
+
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+ 2
+ 3
+ 4
+ 5
+ 6
+ 7
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+ 9
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import json
+import onnxruntime as ort
+
+sess = ort.InferenceSession('/path/to/model.onnx')
+metamap = sess.get_modelmeta().custom_metadata_map
+
+# 读取dictionary键对应的值
+chars = metamap['dictionary'].splitlines()
+
+# 读取shape键对应的值
+input_shape = json.loads(metamap['shape'])
+
+ + + + + + + + + + + + + + + + + + + + + + + +

评论

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+ + + + + + + + + + \ No newline at end of file diff --git "a/blog/2023/10/17/\345\246\202\344\275\225\346\233\264\346\215\242\345\205\266\344\273\226\346\243\200\346\265\213\345\222\214\350\257\206\345\210\253\346\250\241\345\236\213/index.html" "b/blog/2023/10/17/\345\246\202\344\275\225\346\233\264\346\215\242\345\205\266\344\273\226\346\243\200\346\265\213\345\222\214\350\257\206\345\210\253\346\250\241\345\236\213/index.html" new file mode 100644 index 00000000..a6cb4ad9 --- /dev/null +++ "b/blog/2023/10/17/\345\246\202\344\275\225\346\233\264\346\215\242\345\205\266\344\273\226\346\243\200\346\265\213\345\222\214\350\257\206\345\210\253\346\250\241\345\236\213/index.html" @@ -0,0 +1,2091 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 如何更换其他检测和识别模型？ - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
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+ + + + + + + +

如何更换其他检测和识别模型？

+ +
+

本文详尽地给出了如何更换其他检测和识别模型的保姆级教程。

+
+ + +
+

Note

+

建议用rapidocr_onnxruntime>=1.3.x版本来加载PaddleOCR v3/v4版本训练所得模型。

+
+

引言

+

rapidocr系列库中默认打包了轻量版的中英文检测和识别模型，这种配置可以覆盖到大部分场景。但是也总会有一些其他场景，要用到其他检测和识别模型。

+

这一点在设计时已经做了考虑，留出了接口，这个博客就是以如何更换rapidocr_onnxruntime的识别模型为英文和数字的识别模型为例做讲解，其他模型同理。

+
+

Note

+

检测模型，对应模型路径参数为det_model_path
识别模型，对应模型路径参数为rec_model_path
详细说明参见：link

+
+

1. 安装rapidocr_onnxruntime

+

请先根据教程，装好rapidocr_onnxruntime库，具体可参考：link

+

2. 获得英文和数字的ONNX识别模型

+
+

Note

+

如果想用RapidOCR仓库推理其他模型，必须要用PaddleOCRModelConvert工具转换模型
在用PaddleOCRModelConvert工具转换模型时，字典会自动写入到onnx模型里。

+
+

模型地址： + 

https://paddleocr.bj.bcebos.com/PP-OCRv4/english/en_PP-OCRv4_rec_infer.tar
+

+

字典地址: + 

https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.7/ppocr/utils/en_dict.txt
+

+

在线转换: 基于PaddleOCRModelConvert工具得到en_PP-OCRv4_rec_infer.onnx模型

+

3. 使用该模型

+
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from rapidocr_onnxruntime import RapidOCR
+
+model = RapidOCR(rec_model_path="en_PP-OCRv4_rec_infer.onnx")
+
+img_path = "1.png"
+result, elapse = model(img_path)
+print(result)
+print(elapse)
+
+ + + + + + + + + + + + + + + + + + + + + + + +

评论

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+ + + + + + + + + + \ No newline at end of file diff --git "a/blog/2024/04/12/\345\267\262\346\234\211onnx\346\250\241\345\236\213\344\270\213\350\275\275/index.html" "b/blog/2024/04/12/\345\267\262\346\234\211onnx\346\250\241\345\236\213\344\270\213\350\275\275/index.html" new file mode 100644 index 00000000..5143cf0a --- /dev/null +++ "b/blog/2024/04/12/\345\267\262\346\234\211onnx\346\250\241\345\236\213\344\270\213\350\275\275/index.html" @@ -0,0 +1,2051 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 已有ONNX模型下载 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

已有ONNX模型下载

+ + + +

简介

+

该部分将已经转换好的ONNX模型做了整理，提供了Hugging Face、Google网盘和百度网盘两个下载途径。

+

Hugging Face Models

+

Google网盘

+

百度网盘

+ + + + + + + + + + + + + + + + + + + + + + + +

评论

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+ + + + + + + + + + \ No newline at end of file diff --git a/blog/2024/07/13/how-to-use-directml/index.html b/blog/2024/07/13/how-to-use-directml/index.html new file mode 100644 index 00000000..4125ffe6 --- /dev/null +++ b/blog/2024/07/13/how-to-use-directml/index.html @@ -0,0 +1,2142 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + 如何使用DirectML加速推理OCR？ - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
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+
+ + + + + + + +

如何使用DirectML加速推理OCR？

+ +

本篇文章主要介绍一下DirectML，以及它在OCR推理过程中是如何使用的。

+ + +

DirectML是什么？1

+

直接机器学习 (DirectML) 是机器学习 (ML) 的低级 API。 API 具有常见的（本机 C++、nano-COM）编程接口和 DirectX 12 样式的工作流。 可将机器学习推断工作负荷集成到游戏、引擎、中间件、后端或其他应用程序中。 所有与 DirectX 12 兼容的硬件都支持 DirectML。

+

硬件加速的机器学习基元（称为“运算符”）是 DirectML 的构建基块。 在这些构建基块中，可以开发纵向扩展、抗锯齿和样式转移等机器学习技术。 例如，使用噪声抑制和超解析度，可以实现令人印象深刻的光线跟踪效果且可以减少每个像素的光线。

+

可将机器学习推断工作负荷集成到游戏、引擎、中间件、后端或其他应用程序中。 DirectML 提供用户熟悉的（本机C++、nano-COM）DirectX 12 式编程接口和工作流，且受所有 DirectX 12 兼容硬件的支持。 有关 DirectML 示例应用程序（包括精简 DirectML 应用程序的示例），请参阅 DirectML 示例应用程序。

+

DirectML 是在 Windows 10 版本 1903 和 Windows SDK 的相应版本中引入的。

+

RapidOCR下如何使用DirectML加速呢？

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目前在rapidocr_onnxruntime>=1.3.23中，配置了使用DirectML的开关。在满足一定条件后，可以正常使用DirectML加速推理OCR。

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要想使用DirectML加速，需要满足以下条件：

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  • 设备系统要大于等于Windows 10 版本 1903
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  • 安装rapidocr_onnxruntime>=1.3.23版本
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  • 安装onnxruntime-directml包
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具体使用教程

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首先需要确定自己设备是Windows系统，且版本要大于等于Window 10 1903

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安装rapidocr_onnxruntime>=1.3.23

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pip install rapidocr_onnxruntime
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安装onnxruntime-directml

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# 首先卸载上一步默认安装的onnxruntime
+pip uninstall onnxruntime
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+# 安装onnxruntime-directml
+pip install onnxruntime-directml
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Python使用

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from rapidocr_onnxruntime import RapidOCR
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+engine = RapidOCR()
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+img_path = 'tests/test_files/ch_en_num.jpg'
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+# 默认都为False
+result, elapse = engine(img_path, det_use_dml=True, cls_use_dml=True, rec_use_dml=True)
+print(result)
+print(elapse)
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Benchmark

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由于自己手头没有Windows机器，暂时没有相关测评，可以参考下面Disscussions中评测。

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有关DirectML的讨论

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    https://learn.microsoft.com/zh-cn/windows/ai/directml/dml ↩

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OCR相关项目

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推理引擎

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模型相关

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转换PaddleOCR模型为ONNX

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该文章主要给出了几种转换PaddleOCR模型的方案，便于大家快速转换使用。

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开源OCR模型对比

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本文主要给出了常见开源文本检测和文本识别模型的对比和评测，给大家一个使用参考。

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Blog

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+
+

转换PaddleOCR模型为ONNX

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该文章主要给出了几种转换PaddleOCR模型的方案，便于大家快速转换使用。

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开源OCR模型对比

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本文主要给出了常见开源文本检测和文本识别模型的对比和评测，给大家一个使用参考。

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商业支持

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服务一：AI相关问题咨询

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  • 加入知识星球RapidAI私享群，目前星球已有C++/Rust/Go/Python以及AI大佬加入。
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  • 这里的提问会优先得到详尽回答和支持，也会享受到RapidAI组织后续持续优质的服务。
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服务二：信创CPU支持

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  • 提供信创平台多架构，包括Arm/X86/mips(龙芯)/RISC-V等信创CPU支持，同时兼容ONNXRuntime/OpenVINO/NCNN。
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  • 有意者邮件联系: znsoft@163.com, 请先邮件咨询服务项目，即时回复联系方式。
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服务三：国产操作系统OCR Docker部署

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  • 提供国产操作系统（海光、中科方德、麒麟等等）OCR Docker部署服务。
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  • 有意者 → ✉ liekkaskono@163.com
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评论

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交流群

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可通过以下方式与RapidOCR维护者SWHL进行沟通，也欢迎反馈使用过程中遇到的问题。

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知识星球RapidAI私享群

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这里的提问会优先得到回答和支持，也会享受到RapidAI组织后续持续优质的服务，欢迎大家的加入。

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微信交流群

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微信扫描以下二维码，关注RapidAI公众号，回复 OCR 即可加入RapidOCR微信交流群：

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QQ交流群

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欢迎加入我们的QQ群下载模型及测试程序。群号为：755960114

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概览

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+ + +
+ 信创级开源OCR - 为世界内容安全贡献力量 +
+
 
+ + + +Open in Colab +
+ + + + + + +PyPI + +SemVer2.0 + + +
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简介

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💖目前已知运行速度最快、支持最广，完全开源免费并支持离线快速部署的多平台多语言OCR。主打ONNXRuntime推理引擎推理，比PaddlePaddle推理引擎速度有4~5倍提升，且没有内存泄露问题。

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支持语言：默认是中英文，其他语言识别需要自助转换。具体参考这里

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缘起：因为PaddleOCR工程化尚有提升空间，为了方便在各种端上进行OCR推理，我们将PaddleOCR中的模型转换为ONNX格式，使用Python/C++/Java/C# 将它移植到各个平台，方便大家使用。

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名称来源：轻快好省并智能。基于深度学习的OCR技术，主打人工智能优势及小模型，以速度为使命，效果为导向。

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使用：

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    +
  • 如果仓库下已有模型满足要求 → RapidOCR部署使用即可。
    • +
  • 不满足要求 → 基于PaddleOCR在自己数据上微调 → RapidOCR部署。
    • +
+

如果该仓库有帮助到你，还请点个小星星⭐呗！

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整体框架

+
flowchart LR
+    subgraph Step
+    direction TB
+    C(Text Det) --> D(Text Cls) --> E(Text Rec)
+    end
+
+    A[/OurSelf Dataset/] --> B(PaddleOCR) --Train--> Step --> F(PaddleOCRModelConverter)
+    F --ONNX--> G{RapidOCR Deploy\n<b>Python/C++/Java/C#</b>}
+    G --> H(Windows x86/x64) & I(Linux) & J(Android) & K(Web) & L(Raspberry Pi)
+
+    click B "https://github.com/PaddlePaddle/PaddleOCR" _blank
+    click F "https://github.com/RapidAI/PaddleOCRModelConverter" _blank
+

效果展示（more）

+
+ Demo +
+ +

贡献者

+

+ + + +

+ +

引用

+

如果您发现该项目对您的研究有用，请考虑引用：

+
@misc{RapidOCR 2021,
+    title={{Rapid OCR}: OCR Toolbox},
+    author={RapidAI Team},
+    howpublished = {\url{https://github.com/RapidAI/RapidOCR}},
+    year={2021}
+}
+
+

Star history

+

Stargazers over time

+

开源许可证

+

OCR模型版权归百度所有，其他工程代码版权归本仓库所有者所有。

+

该项目采用 Apache 2.0 license 开源许可证。

+ + + + + + + + + + + + + + + + + + + + + + + +

评论

+ + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/api/RapidOCR/index.html b/install_usage/api/RapidOCR/index.html new file mode 100644 index 00000000..42723210 --- /dev/null +++ b/install_usage/api/RapidOCR/index.html @@ -0,0 +1,2525 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + RapidOCR - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
+
+ + + +
+ + + + + + +
+ + + + + + + +
+ +
+ + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + +
+
+
+ + + +
+
+ + + + + + + +

RapidOCR

+ +
+

Info

+

该部分以rapidocr_onnxruntime库下RapidOCR为例作讲解，其他推理引擎与这个基本类似，请移步具体源码查看。

+
+

__init__ [SOURCE]

+
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def __init__(self, text_score: float = 0.5,
+    print_verbose: bool = False,
+    min_height: int = 30,
+    width_height_ratio: float = 8,
+    det_use_cuda: bool = False,
+    det_use_dml: bool = False,
+    det_model_path: Optional[str] = None,
+    det_limit_side_len: float = 736,
+    det_limit_type: str = "min",
+    det_thresh: float = 0.3,
+    det_box_thresh: float = 0.5,
+    det_unclip_ratio: float = 1.6,
+    det_donot_use_dilation: bool = False,
+    det_score_mode: str = "fast",
+    cls_use_cuda: bool = False,
+    cls_use_dml: bool = False,
+    cls_model_path: Optional[str] = None,
+    cls_image_shape: List[int] = [3, 48, 192],
+    cls_label_list: List[str] = ["0", "180"],
+    cls_batch_num: int = 6,
+    cls_thresh: float = 0.9,
+    rec_use_cuda: bool = False,
+    rec_use_dml: bool = False,
+    rec_model_path: Optional[str] = None,
+    rec_img_shape: List[int] = [3, 48, 320],
+    rec_batch_num: int = 6,
+    intra_op_num_threads: int = -1,
+    inter_op_num_threads: int = -1,
+):
+    pass
+
+

参数

+
    +
  • text_score (float, optional): 文本识别结果置信度，值越大，把握越大。取值范围：[0, 1], 默认值是0.5。
    • +
  • print_verbose (bool, optional): 是否打印各个部分耗时信息。 默认为False。
    • +
  • min_height (int, optional): 图像最小高度（单位是像素），低于这个值，会跳过文本检测阶段，直接进行后续识别。默认值为30。min_height是用来过滤只有一行文本的图像（如下图），这类图像不会进入文本检测模块，直接进入后续过程。
    • +
+

+- width_height_ratio (float, optional): 如果输入图像的宽高比大于width_height_ratio，则会跳过文本检测，直接进行后续识别，取值为-1时：不用这个参数. 默认值为8。 +- det_use_cuda (bool, optional): 是否使用CUDA加速推理。默认值为False。 +- det_use_dml (bool, optional): 是否使用DirectML加速推理(仅限于Window10及以上)。默认值为False。详细参见 → link 。 +- det_model_path (Optional[str], optional): 文本检测模型路径，仅限于基于PaddleOCR训练所得DBNet文本检测模型。默认值为None。 +- det_limit_side_len (float, optional): 限制图像边的长度的像素值。默认值为736。 +- det_limit_type (str, optional): 限制图像的最小边长度还是最大边为limit_side_len
示例解释：当limit_type=min和limit_side_len=736时，图像最小边小于736时，
会将图像最小边拉伸到736，另一边则按图像原始比例等比缩放。 取值范围为：[min, max]，默认值为min。 +- det_thresh (float, optional): 图像中文字部分和背景部分分割阈值。值越大，文字部分会越小。取值范围：[0, 1]，默认值为0.3。 +- det_box_thresh (float, optional): 文本检测所得框是否保留的阈值，值越大，召回率越低。取值范围：[0, 1]，默认值为0.5。 +- det_unclip_ratio (float, optional): 控制文本检测框的大小，值越大，检测框整体越大。取值范围：[1.6, 2.0]，默认值为1.6。 +- det_donot_use_dilation (bool, optional): 不使用膨胀操作。默认值为False。 +- det_score_mode (str, optional): 计算文本框得分的方式。取值范围为：[slow, fast]，默认值为fast。 +- cls_use_cuda (bool, optional): 是否使用CUDA加速推理。默认值为False。 +- cls_use_dml (bool, optional): 是否使用DirectML加速推理(仅限于Window10及以上)。默认值为False。详细参见 → link 。 +- cls_model_path (Optional[str], optional): 文本行方向分类模型路径，仅限于PaddleOCR训练所得二分类分类模型。默认值为None。 +- cls_image_shape (List[int], optional): 输入方向分类模型的图像Shape(CHW)。默认值为[3, 48, 192]。 +- cls_label_list (List[str], optional): 方向分类的标签，0°或者180°，该参数不能动。默认值为["0", "180"]。 +- cls_batch_num (int, optional): 批次推理的batch大小，一般采用默认值即可，太大并没有明显提速，效果还可能会差。默认值为6。 +- cls_thresh (float, optional): 方向分类结果的置信度。取值范围：[0, 1]，默认值为0.9。 +- rec_use_cuda (bool, optional): 是否使用CUDA加速推理。默认值为False。 +- rec_use_dml (bool, optional): 是否使用DirectML加速推理(仅限于Window10及以上)。默认值为False。详细参见 → link 。 +- rec_model_path (Optional[str], optional): 文本识别模型路径，仅限于PaddleOCR训练文本识别模型。默认值为None。 +- rec_img_shape (List[int], optional): 输入文本识别模型的图像Shape(CHW)。默认值为[3, 48, 320]。 +- rec_batch_num (int, optional): 批次推理的batch大小，一般采用默认值即可，太大并没有明显提速，效果还可能会差。默认值为6。 +- intra_op_num_threads (int, optional): 参见docs。默认值为-1. +- inter_op_num_threads (int, optional): 参见docs。默认值为-1.

+

使用示例

+
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+ 2
+ 3
+ 4
+ 5
+ 6
+ 7
+ 8
+ 9
+10
from pathlib import Path
+
+from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR(text_score=0.6, det_use_cuda=False)
+
+img_path = Path('tests/test_files/ch_en_num.jpg')
+result, elapse = engine(img_path)
+print(result)
+print(elapse)
+
+

__call__ [SOURCE]

+
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+2
+3
+4
+5
+6
+7
+8
+9
def __call__(
+    self,
+    img_content: Union[str, np.ndarray, bytes, Path],
+    use_det: Optional[bool] = None,
+    use_cls: Optional[bool] = None,
+    use_rec: Optional[bool] = None,
+    **kwargs,
+) -> Tuple[Optional[List[List[Union[Any, str]]]], Optional[List[float]]]:
+    pass
+
+

参数

+
    +
  • img_content (Union[str, np.ndarray, bytes, Path]): 图像内容。
    • +
  • use_det (Optional[bool], optional): 是否使用文本检测模型，当为None时，默认使用。默认值为None。
    • +
  • use_cls (Optional[bool], optional): 是否使用文本行方向分类模型，当为None时，默认使用。默认值为None。
    • +
  • use_rec (Optional[bool], optional): 是否使用文本识别模型，当为None时，默认使用。默认值为None。
    • +
+

输入

+

确保输入模型前的图像通道顺序为BGR。当前LoadImage类内部已经对此做了处理，参考下面写法即可正常使用。支持4种输入类型：Union[str, np.ndarray, bytes, Path, PIL.Image.Image]

+
+
+
+
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from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+
+img_path = 'tests/test_files/ch_en_num.jpg'
+result, elapse = engine(img_path)
+print(result)
+print(elapse)
+
+
+
+
1
+2
+3
+4
+5
+6
+7
+8
import cv2
+from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+img = cv2.imread('tests/test_files/ch_en_num.jpg')
+result, elapse = engine(img)
+print(result)
+print(elapse)
+
+
+
+
1
+2
+3
+4
+5
+6
+7
+8
from PIL import Image
+from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+img = Image.open('tests/test_files/ch_en_num.jpg')
+result, elapse = engine(img)
+print(result)
+print(elapse)
+
+
+
+
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+ 2
+ 3
+ 4
+ 5
+ 6
+ 7
+ 8
+ 9
+10
from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+
+img_path = 'tests/test_files/ch_en_num.jpg'
+with open(img_path, 'rb') as f:
+    img = f.read()
+result, elapse = engine(img)
+print(result)
+print(elapse)
+
+
+
+
 1
+ 2
+ 3
+ 4
+ 5
+ 6
+ 7
+ 8
+ 9
+10
from pathlib import Path
+
+from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+
+img_path = Path('tests/test_files/ch_en_num.jpg')
+result, elapse = engine(img_path)
+print(result)
+print(elapse)
+
+
+
+
+

输出

+

RapidOCR在调用时，有三个参数use_det | use_cls | use_rec，可以控制是否使用检测、方向分类和识别这三部分，不同的参数决定了不同的输出。

+

如果图像中未检测到有效文字信息，则返回Tuple[None, None]。详细搭配如下：

+
+
+
+
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+2
+3
+4
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+6
+7
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from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+
+img_path = 'tests/test_files/ch_en_num.jpg'
+result, elapse = engine(img_path, use_det=True, use_cls=False, use_rec=False)
+print(result)
+print(elapse)
+
+

返回值result: List[List[float]] (每个框的坐标[左上, 右上, 右下, 左下]) +

[
+    [[5.0, 2.0], [322.0, 9.0], [319.0, 103.0], [3.0, 96.0]],
+    [[70.0, 98.0], [252.0, 97.0], [252.0, 125.0], [70.0, 126.0]],
+    ...
+]
+

+
+
+

1
+2
+3
+4
+5
+6
+7
+8
from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+
+img_path = 'tests/test_files/ch_en_num.jpg'
+result, elapse = engine(img_path, use_det=False, use_cls=True, use_rec=False)
+print(result)
+print(elapse)
+
+返回值result: List[List[str, float]] ([方向0或180, 置信度]) +
[
+    ['0', 0.9998784],
+    ...
+]
+

+
+
+
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+2
+3
+4
+5
+6
+7
+8
from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+
+img_path = 'tests/test_files/ch_en_num.jpg'
+result, elapse = engine(img_path, use_det=False, use_cls=False, use_rec=True)
+print(result)
+print(elapse)
+
+

返回值result: List[List[str, float]] ([识别的文本, 置信度]) +

1
+2
+3
+4
[
+    ['韩国小馆', 0.7992169380187988],
+    ...
+]
+

+
+
+

1
+2
+3
+4
+5
+6
+7
+8
from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+
+img_path = 'tests/test_files/ch_en_num.jpg'
+result, elapse = engine(img_path, use_det=True, use_cls=False, use_rec=True)
+print(result)
+print(elapse)
+
+返回值result: List[List[float], str, float] ([[左上, 右上, 右下, 左下], 文本内容, 置信度]) +
1
+2
+3
+4
+5
[
+    [[[9.0, 2.0], [321.0, 11.0], [318.0, 102.0], [6.0, 93.0]], '正品促销', '0.7986101984977723'],
+    [[[70.0, 98.0], [251.0, 98.0], [251.0, 125.0], [70.0, 125.0]], '大桶装更划算', '0.7368737288883754'],
+    ...
+]
+

+
+
+
1
+2
+3
+4
+5
+6
+7
+8
from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+
+img_path = 'tests/test_files/ch_en_num.jpg'
+result, elapse = engine(img_path, use_det=False, use_cls=True, use_rec=True)
+print(result)
+print(elapse)
+
+

返回值result: List[List[str, float]] ([识别的文本, 置信度]) +

1
+2
+3
+4
[
+    ['韩国小馆', 0.7992169380187988],
+    ...
+]
+

+
+
+
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+ 2
+ 3
+ 4
+ 5
+ 6
+ 7
+ 8
+ 9
+10
from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+
+img_path = 'tests/test_files/ch_en_num.jpg'
+
+# 默认都为True
+result, elapse = engine(img_path, use_det=True, use_cls=True, use_rec=True)
+print(result)
+print(elapse)
+
+

返回值result: List[List[float], str, float] ([[左上, 右上, 右下, 左下], 文本内容, 置信度]) +

1
+2
+3
+4
+5
[
+    [[[9.0, 2.0], [321.0, 11.0], [318.0, 102.0], [6.0, 93.0]], '正品促销', '0.7986101984977723'],
+    [[[70.0, 98.0], [251.0, 98.0], [251.0, 125.0], [70.0, 125.0]], '大桶装更划算', '0.7368737288883754'],
+    ...
+]
+

+
+
+
+ + + + + + + + + + + + + + + + + + + + + +

评论

+ + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/api/VisRes/index.html b/install_usage/api/VisRes/index.html new file mode 100644 index 00000000..f8ef8bbd --- /dev/null +++ b/install_usage/api/VisRes/index.html @@ -0,0 +1,2175 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + VisRes - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
+
+ + + +
+ + + + + + +
+ + + + + + + +
+ +
+ + + + +
+
+ + + +
+
+
+ + + + + + + +
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+ + + +
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+ + + +
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+ + + + + + + +

VisRes

+ +

__init__ [SOURCE]

+
1
+2
def __init__(self, text_score: float = 0.5):
+    pass
+
+

参数

+
    +
  • text_score (float, optional): 文本识别结果置信度，值越大，把握越大。取值范围：[0, 1], 默认值是0.5。
    • +
+

__call__ [SOURCE]

+
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def __call__(
+    self,
+    img_content: Union[str, np.ndarray, bytes, Path, Image.Image],
+    dt_boxes: np.ndarray,
+    txts: Optional[Union[List[str], Tuple[str]]] = None,
+    scores: Optional[Tuple[float]] = None,
+    font_path: Optional[str] = None,
+) -> np.ndarray:
+    pass
+
+

参数

+
    +
  • img_content (Union[str, np.ndarray, bytes, Path, Image.Image]): 输入图像。
    • +
  • dt_boxes (np.ndarray): 文本检测所得文本框。
    • +
  • txts (Optional[Union[List[str], Tuple[str]]], optional): 文本框对应的文本内容。默认为None。
    • +
  • scores (Optional[Tuple[float]], optional): 文本内容对应的置信度，默认为None。
    • +
  • font_path (Optional[str], optional): 字体文件路径，默认为None。
    • +
+

使用示例

+

可视化识别结果时，需要提供字体文件。下载链接：link。

+
+
+
+
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+ 4
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+ 7
+ 8
+ 9
+10
+11
+12
+13
+14
import cv2
+
+from rapidocr_onnxruntime import RapidOCR, VisRes
+
+engine = RapidOCR()
+vis = VisRes()
+
+image_path = "tests/test_files/ch_en_num.jpg"
+img = cv2.imread(image_path)
+
+result, elapse_list = engine(img)
+boxes, txts, scores = list(zip(*result))
+res = vis(img, boxes)
+cv2.imwrite("only_vis_det.png", res)
+
+
+
+
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+ 2
+ 3
+ 4
+ 5
+ 6
+ 7
+ 8
+ 9
+10
+11
+12
+13
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+15
+16
import cv2
+
+from rapidocr_onnxruntime import RapidOCR, VisRes
+
+engine = RapidOCR()
+vis = VisRes()
+
+image_path = "tests/test_files/ch_en_num.jpg"
+img = cv2.imread(image_path)
+
+result, elapse_list = engine(img)
+boxes, txts, scores = list(zip(*result))
+
+font_path="resources/fonts/FZYTK.TTF"
+res = vis(img, boxes, txts, scores, font_path)
+cv2.imwrite("vis_det_rec.png", res)
+
+
+
+
+ + + + + + + + + + + + + + + + + + + + + +

评论

+ + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/rapidocr/changelog/index.html b/install_usage/rapidocr/changelog/index.html new file mode 100644 index 00000000..748cdca8 --- /dev/null +++ b/install_usage/rapidocr/changelog/index.html @@ -0,0 +1,3321 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 更新日志 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
+
+ + + +
+ + + + + + +
+ + + + + + + +
+ +
+ + + + +
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+ + + +
+
+
+ + + + + + + +
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+ + + +
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+ + + +
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+ + + +
+
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更新日志

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rapidocr_vino

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2024-07-11 v1.3.23 update

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    +
  • 取消Shapely版本限制，对应 issue #202
    • +
+

2024-06-28 v1.3.22 update

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2024-05-18 v1.3.19 update

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对应rapidocr_onnxruntime==1.3.20

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rapidocr_onnxruntime

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Note

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2024-05-18 通知

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后续rapidocr_onnxruntime>1.3.20的更新日志不在此更新，只在Github Release处更新

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+

🛠️2024-05-15 v1.3.19 update

+
    +
  • 因为DirectML受支持设备限制，因此将DirectML作为一个选项写入配置文件，选择性调用
    • +
  • 在Windows平台仍然恢复到v1.3.18前，默认安装onnxruntime库。如DirectML可用，且显式指定时，需要手动安装。
    • +
  • 相关讨论：PR #178 Discussion #175
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🧚🏻‍♀️2024-05-12 v1.3.18 update

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    +
  • Merge PR #176
    • +
  • 支持python 3.12
    • +
+

🔥2024-04-19 v1.3.17 update

+ +

📘2024-04-07 v1.3.16 update

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修复issue #161

+

🍿2024-03-07 v1.3.15 update

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    +
  • 修复 issue #158
    • +
  • 增加三个推理引擎（onnxruntime、openvino，paddlepaddle）初始化RapidOCR类，指定线程数的参数
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+

🎂2024-03-05 v1.3.14 update

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添加可使用的CPU核心数，包括三个推理引擎，onnxruntime/OpenVINO/PaddlePaddle

+

🔖2024-02-28 v1.3.13 update

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    +
  • 优化LoadImage类，添加对输入PIL.Image.Image的支持
    • +
  • 修复不同输入类型下，图像通道顺序不同的问题
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+

🍉2024-02-27 v1.3.12 update

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可视化函数适配Pillow v9和v10两个版本，自动根据各个版本情况，来选择相应获得char大小的函数

+

♥️2024-02-04 v1.3.11 update

+

Merge PR #151 by LWQ2EDU

+
    +
  • 添加自动padding策略：当传入图像小于min_height或者>width_height_ratio时，会触发自动padding图像，后续再进入检测。
    • +
  • ⚠️注意：padding值多少？当前值是一个权衡设置，大家可根据具体使用场景，自定设置合适值。
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+

🌈2024-01-30 v1.3.10 update

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🥰2023-12-28 v1.3.9 update

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😜2023-10-25 v1.3.8 update

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📡2023-09-21 v1.3.7 update

+
    +
  • 完善VisRes类在终端情况下的使用
    • +
  • 修复auto_text_det的条件错误
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+

🧸2023-09-20 v1.3.6 update

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    +
  • 添加VisRes类，便于快速可视化结果。详情参见demo.py用法
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+

😀2023-09-20 v1.3.5 update

+
    +
  • Fixed issue #122
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⏰2023-09-18 v1.3.4 update

+
    +
  • 优化更新参数部分的函数实现
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🧸2023-09-06 v1.3.2 update

+
    +
  • 修复issue #116
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+

⭐2023-08-29 v1.3.1 update

+
    +
  • 修复issue #115
    • +
+

🎉2023-08-26 v1.3.0 update

+
    +
  • 将PaddleOCR v4版对应的文本检测和文本识别轻量模型转换为onnx，并打包到whl中。
    • +
  • 接口与v1.2.x一致，直接使用即可。
    • +
+

😉2023-07-12 v1.2.12 update

+
    +
  • 在rapidocr_onnxruntime初始化时，添加det_use_cuda、cls_use_cuda、rec_use_cuda参数
    • +
  • 兼容配置文件方式传入RapidOCR类中
    • +
  • rapidocr_openvino同理
    • +
+

🎮2023-03-11 v1.2.2 update

+
    +
  • 修复实例化python中RapidOCR类传入参数错误
    • +
+

🧢2023-03-07 v1.2.1 update

+
    +
  • rapidocr系列包更新到v1.2.0
    • +
  • 优化python下rapidocr系列包的接口传入参数，支持实例化类时，动态给定各个参数，更加灵活。
    • +
  • 如果不指定，则用config.yaml下的默认参数。
    • +
  • 具体可参见：传入参数
    • +
+

⛸2023-02-16 update

+
    +
  • 优化ocrweb部分代码，可直接pip安装，快速使用，详情参见README。
    • +
  • 优化python中各个部分的推理代码，更加紧凑，同时易于维护。
    • +
+

🎉2023-01-21 update

+
    +
  • [python] 添加含有文字的图像方向分类模块，具体参见Rapid Orientation
    • +
+

⚽2022-12-19 update

+
    +
  • [python] 添加表格结构还原模块，具体参见Rapid Table
    • +
+

🤖2022-12-14 update

+
    +
  • [python] 将配置参数和模型移到模块里面，同时将模型打到whl包内，可以直接pip安装使用，更加方便快捷。
    • +
  • 详情参见：README
    • +
+

🧻2022-11-20 update

+
    +
  • [python] 添加版面分析部分,支持中文、英文和表格三种版面的检测分析。详情参见:Rapid Structure部分。
    • +
+

🎃2022-11-01 update

+
    +
  • 添加Hugging Face Demo, 增加可以调节超参数的功能，详情可访问Hugging Face Demo
    • +
+

🚩2022-10-01 udpate

+ +

🛴2022-09-01 update

+
    +
  • 由于openvino发布了2022.2.0.dev20220829版本，该版本解决了cls部分模型推理的问题。至此，基于openvino的rapidocr完成了统一，全部由openvino推理引擎完成。
    • +
  • 详细使用方法参见：python/README
    • +
+

🧸2022-08-17 update

+
    +
  • python/ocrweb部分 v1.1.0发布，详情参见v1.1.0
    • +
+

🕶2022-08-14 update

+
    +
  • ocrweb部分增加以API方式部署调用的功能，可以通过发送POST请求，来获得OCR识别结果。
    • +
  • 详情参见：API方式调用
    • +
+

✨2022-07-07 update

+
    +
  • 修复python版中v3 rec推理bug，并将v3 rec与v2 rec合并为同一套推理代码，更加简洁和方便
    • +
  • 添加python模块下的单元测试
    • +
  • 该页面添加致谢模块，感谢为这个项目作出贡献的小伙伴。
    • +
+

😁2022-07-05 update

+
    +
  • 添加对单行文本的处理能力，对于单行文本，可自行设定阈值，不过检测模块，直接识别即可。详情参见README
    • +
  • 优化python部分代码逻辑，更优雅简洁。
    • +
+

🏝2022-06-30 update

+
    +
  • python推理部分，增加参数选择使用GPU推理的配置选项，在正确安装onnxruntime-gpu版本前提下，可以一键使用（Fix issue#30）
    • +
  • 具体基于GPU的推理情况，需要等我后续整理一下，再更新出来
    • +
  • 详情参见：onnxruntime-gpu版推理配置
    • +
+

📌2022-06-25 update

+
    +
  • 重新整理python部分推理代码，将常用调节参数全部放到yaml文件中，便于调节，更加容易使用
    • +
  • 详情参见：README
    • +
+

🍿2022-05-15 udpate

+
    +
  • 增加PaddleOCR v3 rec模型转换后的ONNX模型，直接去网盘下载替换即可。(百度网盘 | Google Drive)
    • +
  • 增加文本识别模型各个版本效果对比表格，详情点击各个版本ONNX模型效果对比。v3的文本识别模型从自己构建测试集上的指标来看不如之前的好。
    • +
+

😀2022-05-12 upadte

+
    +
  • 增加PaddleOCR v3 det模型转换的ONNX模型，直接去网盘下载，替换即可。(百度网盘 | Google Drive)
    • +
  • 增加各个版本文本检测模型效果对比表格，详情点击各个版本ONNX模型效果对比。v3的文本检测模型从指标来看是好于之前的v2的，推荐使用。
    • +
+

🎧2022-04-04 udpate

+
    +
  • 增加python下的基于OpenVINO推理引擎的支持
    • +
  • 给出OpenVINO和ONNXRuntime的性能对比表格
    • +
  • 详情参见:python/README
    • +
+

2022-02-24 udpate

+ +

2021-12-18 udpate

+ +

2021-11-28 udpate

+
    +
  • 更新ocrweb部分
    • +
  • 添加显示各个阶段处理时间
    • +
  • 更新说明文档
    • +
  • 更换文本检测模型为ch_PP-OCRv2_det_infer.onnx,推理更快，更准
    • +
+

2021-11-13 udpate

+
    +
  • 添加python版本中文本检测和识别可调节的超参数，主要有box_thresh|unclip_ratio|text_score，详情见参数调节
    • +
  • 将文本识别中字典位置以参数方式给出，便于灵活配置，详情见keys_path
    • +
+

2021-10-27 udpate

+
    +
  • 添加使用onnxruntime-gpu版推理的代码（不过gpu版本的onnxruntime不太好用，按照官方教程配置，感觉没有调用起来GPU）
    • +
  • 具体使用步骤参见: onnxruntime-gpu推理配置
    • +
+

2021-09-13 udpate

+
    +
  • 添加基于python的whl文件，便于使用，详情参见release/python_sdk
    • +
+

2021-09-11 udpate

+
    +
  • 添加PP-OCRv2新增模型onnx版本
    • +
  • 使用方法推理代码不变，直接替换对应模型即可。
    • +
  • 经过在自有测试集上评测：
    • +
  • PP-OCRv2检测模型效果有大幅度提升，模型大小没变。
    • +
  • PP-OCRv2识别模型效果无明显提升，模型大小增加了3.58M。
    • +
  • 模型上传到百度网盘 提取码：30jv
    • +
+

2021-08-07 udpate

+
    +
  • PP-Structure 表格结构和cell坐标预测 正在整理中
    • +
  • 之前做的,未完成的，欢迎提PR
    • +
  • 打Dokcer镜像
    • +
  • 尝试onnxruntime-gpu推理
    • +
+

2021-07-17 udpate

+
    +
  • 完善README文档
    • +
  • 增加英文、数字识别onnx模型，具体参见python/en_number_ppocr_mobile_v2_rec，用法同其他
    • +
  • 整理一下模型转onnx
    • +
+

2021-07-04 udpate

+
    +
  • 目前仓库下的python程序已经可以在树莓派4B上，成功运行，详细信息请进群，询问群主
    • +
  • 更新整体结构图，添加树莓派的支持
    • +
+

2021-06-20 udpate

+
    +
  • 优化ocrweb中识别结果显示，同时添加识别动图演示
    • +
  • 更新datasets目录，添加一些常用数据库链接(搬运一下-)
    • +
  • 更新FAQ
    • +
+

2021-06-10 udpate

+ +

2021-06-08 udpate

+
    +
  • 整理仓库，统一模型下载路径
    • +
  • 完善相关说明文档
    • +
+

2021-03-24 udpate

+
    +
  • 新模型已经完全兼容ONNXRuntime 1.7 或更高版本。 特别感谢：@Channingss
    • +
  • 新版onnxruntime比1.6.0 性能提升40%以上。
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评论

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+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/rapidocr/cli/index.html b/install_usage/rapidocr/cli/index.html new file mode 100644 index 00000000..f3ad2030 --- /dev/null +++ b/install_usage/rapidocr/cli/index.html @@ -0,0 +1,2156 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 命令行工具 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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命令行工具

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rapidocr_onnxruntime包含了命令行工具，安装之后，即可使用。

+

参数说明

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$ rapidocr_onnxruntime -h
+usage: rapidocr_onnxruntime [-h] -img IMG_PATH [-p] [--text_score TEXT_SCORE]
+                            [--no_det] [--no_cls] [--no_rec] [--print_verbose]
+                            [--min_height MIN_HEIGHT]
+                            [--width_height_ratio WIDTH_HEIGHT_RATIO]
+                            [--det_use_cuda] [--det_model_path DET_MODEL_PATH]
+                            [--det_limit_side_len DET_LIMIT_SIDE_LEN]
+                            [--det_limit_type {max,min}]
+                            [--det_thresh DET_THRESH]
+                            [--det_box_thresh DET_BOX_THRESH]
+                            [--det_unclip_ratio DET_UNCLIP_RATIO]
+                            [--det_donot_use_dilation]
+                            [--det_score_mode {slow,fast}] [--cls_use_cuda]
+                            [--cls_model_path CLS_MODEL_PATH]
+                            [--cls_image_shape CLS_IMAGE_SHAPE]
+                            [--cls_label_list CLS_LABEL_LIST]
+                            [--cls_batch_num CLS_BATCH_NUM]
+                            [--cls_thresh CLS_THRESH] [--rec_use_cuda]
+                            [--rec_model_path REC_MODEL_PATH]
+                            [--rec_img_shape REC_IMG_SHAPE]
+                            [--rec_batch_num REC_BATCH_NUM] [-vis]
+                            [--vis_font_path VIS_FONT_PATH]
+                            [--vis_save_path VIS_SAVE_PATH]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  -img IMG_PATH, --img_path IMG_PATH
+  -p, --print_cost
+
+Global:
+  --text_score TEXT_SCORE
+  --no_det
+  --no_cls
+  --no_rec
+  --print_verbose
+  --min_height MIN_HEIGHT
+  --width_height_ratio WIDTH_HEIGHT_RATIO
+
+Det:
+  --det_use_cuda
+  --det_model_path DET_MODEL_PATH
+  --det_limit_side_len DET_LIMIT_SIDE_LEN
+  --det_limit_type {max,min}
+  --det_thresh DET_THRESH
+  --det_box_thresh DET_BOX_THRESH
+  --det_unclip_ratio DET_UNCLIP_RATIO
+  --det_donot_use_dilation
+  --det_score_mode {slow,fast}
+
+Cls:
+  --cls_use_cuda
+  --cls_model_path CLS_MODEL_PATH
+  --cls_image_shape CLS_IMAGE_SHAPE
+  --cls_label_list CLS_LABEL_LIST
+  --cls_batch_num CLS_BATCH_NUM
+  --cls_thresh CLS_THRESH
+
+Rec:
+  --rec_use_cuda
+  --rec_model_path REC_MODEL_PATH
+  --rec_img_shape REC_IMG_SHAPE
+  --rec_batch_num REC_BATCH_NUM
+
+Visual Result:
+  -vis, --vis_res
+  --vis_font_path VIS_FONT_PATH
+                        When -vis is True, the font_path must have value.
+  --vis_save_path VIS_SAVE_PATH
+                        The directory of saving the vis image.
+
+

使用示例

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Example

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以下只给出常见用例，具体可自行探索使用

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rapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg
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rapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg -no_cls -no_rec
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rapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg -no_det -no_cls
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raprapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg -vis --vis_font_path resources/fonts/FZYTK.TTF
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+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/rapidocr/config_yaml/index.html b/install_usage/rapidocr/config_yaml/index.html new file mode 100644 index 00000000..bd939c2c --- /dev/null +++ b/install_usage/rapidocr/config_yaml/index.html @@ -0,0 +1,1915 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 参数解释 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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参数解释

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请移步API/RapidOCR查看

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评论

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安装

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简介

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rapidocr_onnxruntime和rapidocr_openvino两个包除推理引擎不同之外，其余均相同。后续说明文档均以rapidocr_onnxruntime为例

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如使用rapidocr_openvino，直接更换关键词rapidocr_onnxruntime为rapidocr_openvino即可。

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两者均是在CPU上推理的，如想在GPU上推理，可以参考rapidocr_paddle版。

+

版本情况

+

各个库的最新版本：

+ + + + + + + + + + + + + + + + + + + + + +
库pypi最新版本
rapidocr_onnxruntimePyPI
rapidocr_openvinoPyPI
rapidocr_paddlePyPI
+

pypi上各个版本的对应关系：

+ + + + + + + + + + + + + + + + + + + + +
版本内置模型版本对应PaddleOCR 分支
v1.3.xPaddleOCR v4版release/2.7
v1.2.x
v1.1.x
v1.0.x		PaddleOCR v3版release/2.6
+

安装

+

顺利的话，一行命令即可。包大小约为14M左右，包含了三个模型（文本检测、文本行方向分类和文本识别）。因为其中mobile版模型较小，因此将相关模型都已打到whl包，可直接pip安装使用。

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+

Info

+

请使用Python3.6及以上版本。
rapidocr_onnxruntime系列库目前仅在CPU上支持较好，GPU上推理很慢，这一点可参考link。因此不建议用onnxruntime-gpu版推理。
GPU端推理推荐用rapidocr_paddle

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pip install rapidocr-onnxruntime
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+# 基于OpenVINO
+pip install rapidocr_openvino
+
+

安装速度慢的话，可以指定国内的安装源，如使用清华源： +

1
pip install rapidocr_onnxruntime -i https://pypi.tuna.tsinghua.edu.cn/simple/
+

+

依赖的包如下：

+
+

Info

+

如果在安装过程中，出现某个依赖包不能正确安装时，可先单独安装某个依赖包，之后再安装rapidocr_onnxruntime即可。

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pyclipper>=1.2.1
+onnxruntime>=1.7.0
+opencv_python>=4.5.1.48
+numpy>=1.19.3
+six>=1.15.0
+Shapely>=1.7.1
+PyYAML
+Pillow
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使用说明

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请移步API/RapidOCR查看

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评论

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+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/rapidocr_api/changelog/index.html b/install_usage/rapidocr_api/changelog/index.html new file mode 100644 index 00000000..8dfa90da --- /dev/null +++ b/install_usage/rapidocr_api/changelog/index.html @@ -0,0 +1,2030 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 更新日志 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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更新日志

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+ + + PyPI + +

+ +

2024-07-11 v0.0.7 update

+ +

🥥2024-03-04 v0.0.6 update

+
    +
  • 优化图像读取部分，与rapidocr_onnxruntime>=1.3.13版本保持一致
    • +
  • 统一接口返回值类型为字典
    • +
+

🍜2023-05-22 api update

+
    +
  • 将API从ocrweb中解耦出来，作为单独模块维护，详情参见API
    • +
  • rapidocr_web>0.1.6之后，将不支持pip install rapidocr_web[api]方式安装，可直接pip install rapidocr_api安装使用。
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评论

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+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/rapidocr_api/usage/index.html b/install_usage/rapidocr_api/usage/index.html new file mode 100644 index 00000000..0ec3f60d --- /dev/null +++ b/install_usage/rapidocr_api/usage/index.html @@ -0,0 +1,2312 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 安装及使用 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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安装及使用

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+ + + PyPI + +

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+

Note

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OCR API的输出结果为最原始结果，大家可按需进一步扩展。

+
+

简介

+
    +
  • 该包是将rapidocr_onnxruntime库做了API封装，采用FastAPI + uvicorn实现。
    • +
  • 定位是一个快速调用rapidocr_onnxruntime的API接口，没有考虑多进程处理并发请求，如果有这需求的小伙伴，可以看看gunicorn等。
    • +
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安装

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pip install rapidocr_api
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+

启动服务端

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  • +

    用法:

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    $ rapidocr_api -h
+usage: rapidocr_api [-h] [-ip IP] [-p PORT]
+
+optional arguments:
+-h, --help            show this help message and exit
+-ip IP, --ip IP       IP Address
+-p PORT, --port PORT  IP port
+
    +
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    启动:

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    rapidocr_api -ip 0.0.0.0 -p 9003
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调用

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+

Info

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调用本质就是发送一个POST请求，以下给出Curl和Python的调用示例，其他编程语言同理。

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+

Curl调用

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curl -F image_file=@1.png http://0.0.0.0:9003/ocr
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+

Python调用

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import requests
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+url = 'http://localhost:9003/ocr'
+img_path = 'tests/test_files/ch_en_num.jpg'
+
+with open(img_path, 'rb') as f:
+    file_dict = {'image_file': (img_path, f, 'image/png')}
+    response = requests.post(url, files=file_dict, timeout=60)
+
+print(response.json())
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import base64
+import requests
+
+url = 'http://localhost:9003/ocr'
+img_path = 'tests/test_files/ch_en_num.jpg'
+
+with open(img_path, 'rb') as fa:
+    img_str = base64.b64encode(fa.read())
+
+payload = {'image_data': img_str}
+response = requests.post(url, data=payload, timeout=60)
+
+print(response.json())
+
+
+
+
+

API输出

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    +
  • 输出结果说明：
    • +
  • +

    如果图像中存在文字，则会输出字典格式，具体介绍如下：

    +
    ```python linenums="1"
+{
+"0": {
+    "rec_txt": "香港深圳抽血，",  # 识别的文本
+    "dt_boxes": [  # 依次为左上角 → 右上角 → 右下角 → 左下角
+        [265, 18],
+        [472, 231],
+        [431, 271],
+        [223, 59]
+    ],
+    "score": "0.8176"  # 置信度
+    }
+}
+```
+
    +
    • +
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    如果没有检测到文字，则会输出空字典({})。

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    示例结果：

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    {
+    "0": {
+        "rec_txt": "8月26日！",
+        "dt_boxes": [
+            [333.0, 72.0],
+            [545.0, 40.0],
+            [552.0, 90.0],
+            [341.0, 122.0]
+        ],
+        "score": "0.7342"
+    },
+    "1": {
+        "rec_txt": "澳洲名校招生信息",
+        "dt_boxes": [
+            [266.0, 163.0],
+            [612.0, 116.0],
+            [619.0, 163.0],
+            [272.0, 210.0]
+        ],
+        "score": "0.8262"
+    },
+    "2": {
+        "rec_txt": "解读！！",
+        "dt_boxes": [
+            [341.0, 187.0],
+            [595.0, 179.0],
+            [598.0, 288.0],
+            [344.0, 296.0]
+        ],
+        "score": "0.6152"
+    },
+    "3": {
+        "rec_txt": "Rules...",
+        "dt_boxes": [
+            [446.0, 321.0],
+            [560.0, 326.0],
+            [559.0, 352.0],
+            [445.0, 347.0]
+        ],
+        "score": "0.8704"
+    }
+}
+
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评论

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+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/rapidocr_paddle/changelog/index.html b/install_usage/rapidocr_paddle/changelog/index.html new file mode 100644 index 00000000..11491c18 --- /dev/null +++ b/install_usage/rapidocr_paddle/changelog/index.html @@ -0,0 +1,2241 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 更新日志 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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更新日志

+ +

2024-07-11 v1.3.25 update

+
    +
  • 取消Shapely版本限制，对应 issue #202
    • +
+

2024-06-28 v1.3.24 update

+ +

2024-05-18 v1.3.21 update

+
    +
  • 对应rapidocr_onnxruntime==1.3.20
    • +
+

2024-05-12 v1.3.20 update

+

同rapidocr_onnxruntime Change log

+

2024-04-19 v1.3.19 update

+

同rapidocr_onnxruntime Change log

+

2024-04-07 v1.3.18 update

+

同rapidocr_onnxruntime Change log

+

2024-03-07 v1.3.17 update

+

同rapidocr_onnxruntime Change log

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2024-03-05 v1.3.16 update

+

同rapidocr_onnxruntime Change log

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2024-02-28 v1.3.15 update

+

同rapidocr_onnxruntime Change log

+

2024-02-27 v1.3.14 update

+

同rapidocr_onnxruntime Change log

+

2024-02-04 v1.3.13 update

+

同rapidocr_onnxruntime Change log

+

2024-01-30 v1.3.12 update

+

同rapidocr_onnxrutnime Change log

+

2023-10-25 v1.3.10 update

+

修复issue #133

+

2023-10-23 v1.3.9 update

+

首次适配PaddlePaddle框架，作为GPU端推理引擎

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评论

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安装及使用

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+ + + PyPI + +

+ +

简介

+

PaddleOCR模型本身就是由PaddlePaddle框架训练而来的，PaddlePaddle框架原生支持在CPU和GPU上推理PaddleOCR相关模型。

+

rapidocr_paddle包是基于PaddlePaddle框架作为推理引擎的，支持CPU和GPU上推理，推荐GPU端使用。原因是ONNXRuntime和OpenVINO在GPU上支持较差。

+

CPU端还是以rapidocr_onnxruntime和rapidocr_openvino为主。毕竟PaddlePaddle的CPU端还是比较重的。

+

值得说明的是，这个包和PaddleOCR相比，代码基本都是一样的，只不过这个库将里面核心推理代码抽了出来，更加精简而已。

+

安装

+
    +
  1. +

    安装PaddlePaddle框架GPU版，并验证可行性，详细参见: 官方教程。验证是否安装成功代码如下：

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    import paddle
+
+print(paddle.utils.run_check())
+# 如果出现PaddlePaddle is installed successfully!，说明您已成功安装。
+
    +
    2. +
  2. +

    安装rapidocr_paddle

    +
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    pip install rapidocr_paddle
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+

使用

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import cv2
+
+from rapidocr_paddle import RapidOCR
+
+# 注意这里的参数
+engine = RapidOCR(det_use_cuda=True, cls_use_cuda=True, rec_use_cuda=True)
+
+image_path = "tests/test_files/ch_en_num.jpg"
+result, elapse_list = engine(image_path)
+
+

其他使用详情，同rapidocor_onnxruntime系列，参见: link

+

推理速度比较

+

相关测评代码，参见AI Studio，Fork可直接运行查看。不要只推理一张来测试推理速度，需要先推理一张作为预热，后续再看推理速度。

+

经过初步粗略估计，同一张图像，推理10次，耗时情况见下表：

+ + + + + + + + + + + + + + + + + + + + +
推理库平均耗时(s/img)运行环境
rapidocr_onnxruntime1.6505CPU 2 Cores RAM 16GB
rapidocr_paddle[GPU]0.0508CPU 2 Cores RAM 16GB
GPU Tesla V100 16G
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更新日志

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+ + + PyPI + +

+ +

2024-07-08 v0.1.10 update:

+
    +
  • 修复issue #197
    • +
+

❤2023-05-20 ocrweb update:

+ +

🌹2023-05-14 ocrweb v0.1.5 update:

+
    +
  • 增加界面版返回坐标框的返回值(issue #85)
    • +
  • API模式增加base64格式传入
    • +
  • 详情参见：link
    • +
+

🏸2023-04-16 ocrweb v0.1.1 update:

+
    +
  • API部署改为FastAPI库支持
    • +
  • 将API模式与Web解耦合，可通过pip install rapidocr_web[api]来选择性安装
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  • 详情参见：link
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桌面版使用教程

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引言

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  • 说明：桌面版指的是可以直接解压，双击即可运行的版本。
    • +
  • 通俗来说，对rapidocr_web做了打包，将相关依赖全部放到一个zip包中，不需要本地有额外的环境，降低使用门槛。
    • +
  • 下面会以Windows版为例，作简要说明。
    • +
+

使用步骤

+
    +
  1. +

    下载对应的zip包

    +
      +
    • +

      目前已有的zip包如下： + image

      +
      • +
    • +

      下载方式: Github | 百度网盘 | QQ群共享（群号：755960114）

      +
      • +
    +
    2. +
  2. +

    解压目录如下示例

    +
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    .
+├── api-ms-win-core-console-l1-1-0.dll
+├── api-ms-win-core-datetime-l1-1-0.dll
+├── api-ms-win-core-debug-l1-1-0.dll
+├── api-ms-win-core-errorhandling-l1-1-0.dll
+├── api-ms-win-core-file-l1-1-0.dll
+├── api-ms-win-core-file-l1-2-0.dll
+├── api-ms-win-core-file-l2-1-0.dll
+├── api-ms-win-core-handle-l1-1-0.dll
+├── api-ms-win-core-heap-l1-1-0.dll
+├── api-ms-win-core-interlocked-l1-1-0.dll
+├── api-ms-win-core-libraryloader-l1-1-0.dll
+├── api-ms-win-core-localization-l1-2-0.dll
+├── api-ms-win-core-memory-l1-1-0.dll
+├── api-ms-win-core-namedpipe-l1-1-0.dll
+├── api-ms-win-core-processenvironment-l1-1-0.dll
+├── api-ms-win-core-processthreads-l1-1-0.dll
+├── api-ms-win-core-processthreads-l1-1-1.dll
+├── api-ms-win-core-profile-l1-1-0.dll
+├── api-ms-win-core-rtlsupport-l1-1-0.dll
+├── api-ms-win-core-string-l1-1-0.dll
+├── api-ms-win-core-synch-l1-1-0.dll
+├── api-ms-win-core-synch-l1-2-0.dll
+├── api-ms-win-core-sysinfo-l1-1-0.dll
+├── api-ms-win-core-timezone-l1-1-0.dll
+├── api-ms-win-core-util-l1-1-0.dll
+├── api-ms-win-crt-conio-l1-1-0.dll
+├── api-ms-win-crt-convert-l1-1-0.dll
+├── api-ms-win-crt-environment-l1-1-0.dll
+├── api-ms-win-crt-filesystem-l1-1-0.dll
+├── api-ms-win-crt-heap-l1-1-0.dll
+├── api-ms-win-crt-locale-l1-1-0.dll
+├── api-ms-win-crt-math-l1-1-0.dll
+├── api-ms-win-crt-process-l1-1-0.dll
+├── api-ms-win-crt-runtime-l1-1-0.dll
+├── api-ms-win-crt-stdio-l1-1-0.dll
+├── api-ms-win-crt-string-l1-1-0.dll
+├── api-ms-win-crt-time-l1-1-0.dll
+├── api-ms-win-crt-utility-l1-1-0.dll
+├── _asyncio.pyd
+├── base_library.zip
+├── _bz2.pyd
+├── _ctypes.pyd
+├── cv2
+├── _decimal.pyd
+├── _hashlib.pyd
+├── importlib_metadata-6.6.0.dist-info
+├── libcrypto-1_1.dll
+├── libopenblas.XWYDX2IKJW2NMTWSFYNGFUWKQU3LYTCZ.gfortran-win_amd64.dll
+├── libssl-1_1.dll
+├── _lzma.pyd
+├── markupsafe
+├── MSVCP140.dll
+├── _multiprocessing.pyd
+├── numpy
+├── onnxruntime
+├── _overlapped.pyd
+├── PIL
+├── pyclipper
+├── pyexpat.pyd
+├── python37.dll
+├── python3.dll
+├── _queue.pyd
+├── rapidocr_onnxruntime
+├── RapidOCRWeb.exe
+├── select.pyd
+├── shapely
+├── Shapely.libs
+├── _socket.pyd
+├── _ssl.pyd
+├── static
+├── templates
+├── ucrtbase.dll
+├── unicodedata.pyd
+├── VCRUNTIME140_1.dll
+├── VCRUNTIME140.dll
+└── yaml
+
    +

    +
    3. +
  3. +

    双击RapidOCRWeb.exe运行，界面如下图所示： + image

    +
    4. +
  4. +

    浏览器中打开http://localhost:9003/，即可看到熟悉的RapidOCRWeb界面。 + image

    +
    +

    Note

    +

    如果遇到浏览器不显示界面的情况，可以尝试在黑框上按Ctrl + C

    +
    +
    5. +
+ + + + + + + + + + + + + + + + + + + + + +

评论

+ + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/rapidocr_web/nuitka_package/index.html b/install_usage/rapidocr_web/nuitka_package/index.html new file mode 100644 index 00000000..b5f9afc4 --- /dev/null +++ b/install_usage/rapidocr_web/nuitka_package/index.html @@ -0,0 +1,2060 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Nuitka打包 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
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+ + + +
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+ + + + + + + +

Nuitka打包

+ +

--by DeadWood8

+

打包环境

+
    +
  • OS: Windows11
    • +
  • Python: 3.8.10
    • +
  • rapidocr_onnxruntime: 1.2.0
    • +
  • nuitka: 1.5.3
    • +
  • onnxruntime: 1.14.0
    • +
+

打包步骤

+
    +
  1. 安装Nuitka + 
    1
    pip install nuitka
+
    + 注：第一次安装会自动下载mingw和ccache，也可以手动配置，自行某度。
    2. +
  2. +

    修改rapidocr-onnxruntime源码（修改后可以将所有依赖打包进文件） + !!! note + rapidocr_onnxruntime>=1.2.8以后不用再手动修改下面代码，已经做了修改。可以跳过该步。"

    +
    3. +
  3. +

    进入rapidocr-onnxruntime安装位置，一般在Lib\site-packages\rapidocr_onnxruntime或者你设置的虚拟环境下。

    +
    4. +
  4. 用编辑器打开rapid_ocr_api.py，对39-52行进行修改，如下图： + image
    5. +
  5. nuitka打包 + 
    1
+2
    cd rapidocr_web
+nuitka --mingw64 --standalone --show-memory --show-progress --nofollow-import-to=tkinter --output-dir=out ocrweb.py
+
    6. +
  6. 如下图所示： + image
    7. +
  7. 拷贝静态文件
      +
    • 打包后的文件位于当前位置的out\ocrweb.dist目录下，需要将web项目和rapidocr-onnxruntime相关文件拷贝到此目录。 + image
      • +
    • 拷贝rapidocr_web目录static和templates两个文件夹全部拷贝到out\ocrweb.dist下
      • +
    • 在out\ocrweb.dist创建rapidocr_onnxruntime文件夹，将Lib\site-packages\rapidocr_onnxruntime目录下的config.yaml和models文件夹拷贝到out\ocrweb.dist\rapidocr_onnxruntime文件夹内
      • +
    +
    8. +
  8. 运行程序。进入out\ocrweb.dist，直接双击ocrweb.exe运行。 + image
    9. +
  9. 打包好的exe下载：百度网盘 | Google Drive | Gitee
    10. +
+

补充

+
    +
  • 如果不想运行程序后有黑框，可以在打包命令中加入以下参数 + --windows-disable-console
    • +
  • 完整命令为： + 
    1
    nuitka --mingw64 --standalone --show-memory --show-progress --nofollow-import-to=tkinter --windows-disable-console --output-dir=out ocrweb.py
+
    • +
+ + + + + + + + + + + + + + + + + + + + + +

评论

+ + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/rapidocr_web/ocrweb_multi/index.html b/install_usage/rapidocr_web/ocrweb_multi/index.html new file mode 100644 index 00000000..214e9d13 --- /dev/null +++ b/install_usage/rapidocr_web/ocrweb_multi/index.html @@ -0,0 +1,2111 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 多语言版本部署 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
+
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+ + + +
+
+ + + + + + + +

多语言版本部署

+ +

简介

+
    +
  • 同时支持多种语言，可通过接口参数配置语言及预测过程中的其他参数
    • +
  • 调整结果展示方式为基于canvas, 减少后端处理和接口数据传输
    • +
  • 预测接口添加Token验证支持
    • +
  • 添加pyinstaller打包脚本，简化安装步骤
    • +
  • 示例打包结果：pyinstaller demo
    • +
+

安装

+
    +
  1. 克隆项目到本地 + 
    1
    git clone -b main https://github.com/RapidAI/RapidOCR.git
+
    2. +
  2. 安装运行所需环境 + 
    1
+2
    cd ocrweb_multi
+pip install -r requirements.txt -i https://pypi.douban.com/simple/
+
    3. +
+

运行步骤

+
    +
  1. 下载models文件到当前目录下
      +
    • 下载链接：百度网盘 | Google Drive
      • +
    • 最终目录结构如下： + 
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      ocr_web_multi
+    |-- README.md
+    |-- build.py
+    |-- config.yaml
+    |-- main.py
+    |-- main.spec
+    |-- models
+    |   |-- Multilingual_PP-OCRv3_det_infer.onnx
+    |   |-- ch_PP-OCRv3_det_infer.onnx
+    |   |-- ch_PP-OCRv3_rec_infer.meta.onnx
+    |   |-- ch_ppocr_mobile_v2.0_cls_infer.meta.onnx
+    |   |-- chinese_cht_PP-OCRv3_rec_infer.meta.onnx
+    |   |-- en_PP-OCRv3_det_infer.onnx
+    |   |-- en_PP-OCRv3_rec_infer.meta.onnx
+    |   `-- japan_PP-OCRv3_rec_infer.meta.onnx
+    |-- rapidocr
+    |   |-- __init__.py
+    |   |-- classify.py
+    |   |-- detect.py
+    |   |-- detect_process.py
+    |   |-- main.py
+    |   |-- rapid_ocr_api.py
+    |   `-- recognize.py
+    |-- requirements.txt
+    |-- static
+    |   |-- css
+    |   |-- favicon.ico
+    |   |-- hint.svg
+    |   |-- index.html
+    |   `-- js
+    |-- utils
+    |   |-- config.py
+    |   `-- utils.py
+    |-- wrapper.c
+    `-- wrapper.rc
+
      • +
    +
    2. +
  2. 运行main.py + 
    1
    python main.py
+
    3. +
  3. 打开 http://127.0.0.1:8001 即可， enjoy it!
    4. +
+

ocr_web_multi_demo

+ + + + + + + + + + + + + + + + + + + + + +

评论

+ + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/rapidocr_web/pyinstaller/index.html b/install_usage/rapidocr_web/pyinstaller/index.html new file mode 100644 index 00000000..c0b268f0 --- /dev/null +++ b/install_usage/rapidocr_web/pyinstaller/index.html @@ -0,0 +1,1915 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + PyInstaller打包 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + +
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+ + + + + + + +

PyInstaller打包

+ +

参考Actions中写法，详情移步：package_ocrweb.yml

+ + + + + + + + + + + + + + + + + + + + + +

评论

+ + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/install_usage/rapidocr_web/usage/index.html b/install_usage/rapidocr_web/usage/index.html new file mode 100644 index 00000000..a0b23010 --- /dev/null +++ b/install_usage/rapidocr_web/usage/index.html @@ -0,0 +1,2123 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 安装及使用 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
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+ + + +
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+ + + +
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+ + + + + + + +

安装及使用

+ +

+ + + PyPI + +

+ +

简介

+
    +
  • 该库是rapidocr_onnxruntime的web版本，依赖最新版本的rapidocr_onnxruntime库。
    • +
  • 如果想要离线部署，可以先手动下载rapidocr_onnxruntime whl包，再手动安装rapidocr_web whl包来使用。
    • +
  • +

    网页上显示的推理时间具体解释如下：

    +

    + +

    +
    • +
+

安装

+
1
pip install rapidocr_web
+
+

使用

+

用法:

+
1
+2
+3
+4
+5
+6
+7
$ rapidocr_web -h
+usage: rapidocr_web [-h] [-ip IP] [-p PORT]
+
+optional arguments:
+-h, --help            show this help message and exit
+-ip IP, --ip IP       IP Address
+-p PORT, --port PORT  IP port
+
+

运行:

+
1
rapidocr_web -ip 0.0.0.0 -p 9003
+
+

浏览器打开 http://localhost:9003/，enjoy it!

+
+

Info

+

浏览器打开的网址是http的，不是https。

+
+
+ +
+ + + + + + + + + + + + + + + + + + + + + +

评论

+ + + + + + + + + +
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+ + + + + +
+ + + +
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+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/online_demo/index.html b/online_demo/index.html new file mode 100644 index 00000000..d5809786 --- /dev/null +++ b/online_demo/index.html @@ -0,0 +1,2045 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 在线demo - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
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+ +
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+ + + + + + + + + + + + + + + +
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+ + + + + + + +

在线demo

+ +

+ + + + Open in Colab +
+

+ +

简介

+
    +
  • Hugging Face上的Demo和魔搭Demo是同一套代码，都是基于streamlit搭建而来的。
    • +
  • 两者区别在于，魔搭是国内平台，不需要科学上网即可访问使用；Hugging Face则需要科学上网。
    • +
  • 搭建demo的目的在于：
      +
    • 快速查看指定图像的识别效果和识别时长
      • +
    • 快速比较不同版本的检测和识别模型效果差异
      • +
    +
    • +
+

在线Demo

+
    +
  • Hugging Face:
    • +
  • 阿里魔搭社区：
    • +
  • 百度星河社区：
    • +
+

Demo源码

+ +
+ +
+ + + + + + + + + + + + + + + + + + + + + + + +

评论

+ + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/quickstart/index.html b/quickstart/index.html new file mode 100644 index 00000000..06cecf15 --- /dev/null +++ b/quickstart/index.html @@ -0,0 +1,2148 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 快速开始 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
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+ + + + + + +
+ + + + + + + +
+ +
+ + + + +
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+ + + + + + + + + + + + + + + +
+
+ + + + + + + +

快速开始

+ +

1. 安装

+
1
pip install rapidocr_onnxruntime
+
+

2. 使用

+
+
+
+
1
rapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg
+
+
+
+
1
+2
+3
+4
+5
+6
+7
from rapidocr_onnxruntime import RapidOCR
+
+engine = RapidOCR()
+
+img_path = 'tests/test_files/ch_en_num.jpg'
+result, elapse = engine(img_path)
+print(result)
+
+
+
+
+

3. 查看效果

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[
+    [[[9.0, 2.0], [321.0, 11.0], [318.0, 102.0], [6.0, 93.0]], '正品促销', '0.7986101984977723'],
+    [[[70.0, 98.0], [251.0, 98.0], [251.0, 125.0], [70.0, 125.0]], '大桶装更划算', '0.7368737288883754'],
+    [[[69.0, 144.0], [255.0, 144.0], [255.0, 164.0], [69.0, 164.0]], '强力去污符合国标', '0.8172478278477987'],
+    [[[107.0, 170.0], [219.0, 170.0], [219.0, 182.0], [107.0, 182.0]], '-40深度防冻不结冰', '0.8655969283797524'],
+    [[[35.0, 227.0], [63.0, 227.0], [63.0, 236.0], [35.0, 236.0]], '日常价?', '0.6502826035022735'],
+    [[[141.0, 223.0], [187.0, 225.0], [185.0, 249.0], [139.0, 247.0]], '直击', '0.596031109491984'],
+    [[[34.0, 234.0], [81.0, 236.0], [80.0, 254.0], [33.0, 252.0]], '10.0起', '0.8231529593467712'],
+    [[[257.0, 234.0], [304.0, 236.0], [303.0, 253.0], [256.0, 251.0]], '10.0起', '0.8304102122783661'],
+    [[[258.0, 227.0], [287.0, 226.0], [287.0, 236.0], [258.0, 237.0]], '日常价?', '0.5725070595741272'],
+    [[[140.0, 245.0], [186.0, 246.0], [186.0, 272.0], [139.0, 271.0]], '底价', '0.5142453710238138'],
+    [[[129.0, 290.0], [207.0, 292.0], [206.0, 339.0], [128.0, 337.0]], '5.8', '0.6341951936483383'],
+    [[[98.0, 320.0], [129.0, 320.0], [129.0, 331.0], [98.0, 331.0]], '券后价?', '0.6209247708320618'],
+    [[[114.0, 343.0], [210.0, 343.0], [210.0, 355.0], [114.0, 355.0]], '惊喜福利不容错过', '0.8640043867958916'],
+    [[[69.0, 363.0], [151.0, 363.0], [151.0, 383.0], [69.0, 383.0]], '极速发货', '0.7552512288093567'],
+    [[[201.0, 363.0], [285.0, 363.0], [285.0, 383.0], [201.0, 383.0]], '冰点标准', '0.7194759607315063'],
+    [[[68.0, 392.0], [151.0, 392.0], [151.0, 412.0], [68.0, 412.0]], '破损就赔', '0.7711991906166077'],
+    [[[202.0, 391.0], [285.0, 391.0], [285.0, 413.0], [202.0, 413.0]], '假一赔十', '0.6546663284301758']
+]
+
+

推荐阅读

+

API

+

其他编程语言支持

+ + + + + + + + + + + + + + + + + + + + + + + +

评论

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+
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+ + + + + + + + + + \ No newline at end of file diff --git a/related_projects/index.html b/related_projects/index.html new file mode 100644 index 00000000..5f9e5763 --- /dev/null +++ b/related_projects/index.html @@ -0,0 +1,2228 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 周边项目 - RapidOCR 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + 跳转至 + + +
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周边项目

+ +

推理部署

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
编程语言对应项目
PythonRapidOCR
C++RapidOcrOnnx
C++RapidOcrNcnn
JavaRapidOcr—Java
JavaRapidOcrOnnxJvm
JavaRapidOcrNcnnJvm
C#RapidOCRCSharp
AndroidRapidOcrAndroidOnnx
AndroidRapidOcrAndroidOnnxCompose
易语言RapidOCRServer
+

智能文档

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
项目名称功能
RapidStructure文档结构化仓库，包括文档方向分类、版面分析和表格识别
RapidLaTexOCR公式识别
TableStructureRec表格识别
RapidLayout版面分析
RapidOCRPDFPDF提取
ExtractOfficeContentOffice内容提取
+

转换工具

+ + + + + + + + + + + + + + + + + +
项目名称功能
PaddleOCRModelConvertPaddleOCR模型转换工具
LabelConvert目标检测数据集格式转换
+

评测工具

+ + + + + + + + + + + + + + + + + +
项目名称功能
TextDetMetric计算文本检测算法评测指标
TableRecognitionMetric计算表格识别算法评测指标
+

测评集

+ + + + + + + + + + + + + + + + + + + + + +
项目名称功能
text_det_test_dataset文本测试集
text_rec_test_dataset文本识别测试集
table_rec_test_dataset表格识别测试集
+

场景应用

+ + + + + + + + + + + + + +
项目名称功能
RapidVideOCR视频硬字幕提取工具
+ + + + + + + + + + + + + + + + + + + + + + + +

评论

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+ + + + + + + + + + \ No newline at end of file diff --git a/search/search_index.json b/search/search_index.json new file mode 100644 index 00000000..3228a48c --- /dev/null +++ b/search/search_index.json @@ -0,0 +1 @@ +{"config":{"lang":["en"],"separator":"[\\s\\u200b\\-_,:!=\\[\\]()\"`/]+|\\.(?!\\d)|&[lg]t;|(?!\\b)(?=[A-Z][a-z])","pipeline":["stemmer"]},"docs":[{"location":"","title":"\u6982\u89c8","text":"\u4fe1\u200b\u521b\u7ea7\u200b\u5f00\u6e90\u200bOCR - \u200b\u4e3a\u200b\u4e16\u754c\u200b\u5185\u5bb9\u200b\u5b89\u5168\u200b\u8d21\u732e\u529b\u91cf"},{"location":"#_1","title":"\u7b80\u4ecb","text":"

\ud83d\udc96\u200b\u76ee\u524d\u200b\u5df2\u77e5\u200b\u8fd0\u884c\u200b\u901f\u5ea6\u200b\u6700\u5feb\u200b\u3001\u200b\u652f\u6301\u200b\u6700\u5e7f\u200b\uff0c\u200b\u5b8c\u5168\u200b\u5f00\u6e90\u200b\u514d\u8d39\u200b\u5e76\u200b\u652f\u6301\u200b\u79bb\u7ebf\u200b\u5feb\u901f\u200b\u90e8\u7f72\u200b\u7684\u200b\u591a\u200b\u5e73\u53f0\u200b\u591a\u200b\u8bed\u8a00\u200bOCR\u3002\u200b\u4e3b\u6253\u200bONNXRuntime\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u63a8\u7406\u200b\uff0c\u200b\u6bd4\u200bPaddlePaddle\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u901f\u5ea6\u200b\u6709\u200b4~5\u200b\u500d\u200b\u63d0\u5347\u200b\uff0c\u200b\u4e14\u200b\u6ca1\u6709\u200b\u5185\u5b58\u200b\u6cc4\u9732\u200b\u95ee\u9898\u200b\u3002

\u200b\u652f\u6301\u200b\u8bed\u8a00\u200b\uff1a\u200b\u9ed8\u8ba4\u200b\u662f\u200b\u4e2d\u82f1\u6587\u200b\uff0c\u200b\u5176\u4ed6\u200b\u8bed\u8a00\u200b\u8bc6\u522b\u200b\u9700\u8981\u200b\u81ea\u52a9\u200b\u8f6c\u6362\u200b\u3002\u200b\u5177\u4f53\u200b\u53c2\u8003\u200b\u8fd9\u91cc\u200b

\u200b\u7f18\u8d77\u200b\uff1a\u200b\u56e0\u4e3a\u200bPaddleOCR\u200b\u5de5\u7a0b\u5316\u200b\u5c1a\u6709\u200b\u63d0\u5347\u200b\u7a7a\u95f4\u200b\uff0c\u200b\u4e3a\u4e86\u200b\u65b9\u4fbf\u200b\u5728\u200b\u5404\u79cd\u200b\u7aef\u200b\u4e0a\u200b\u8fdb\u884c\u200bOCR\u200b\u63a8\u7406\u200b\uff0c\u200b\u6211\u4eec\u200b\u5c06\u200bPaddleOCR\u200b\u4e2d\u200b\u7684\u200b\u6a21\u578b\u200b\u8f6c\u6362\u200b\u4e3a\u200bONNX\u200b\u683c\u5f0f\u200b\uff0c\u200b\u4f7f\u7528\u200bPython/C++/Java/C# \u200b\u5c06\u200b\u5b83\u200b\u79fb\u690d\u200b\u5230\u200b\u5404\u4e2a\u200b\u5e73\u53f0\u200b\uff0c\u200b\u65b9\u4fbf\u200b\u5927\u5bb6\u200b\u4f7f\u7528\u200b\u3002

\u200b\u540d\u79f0\u200b\u6765\u6e90\u200b\uff1a\u200b\u8f7b\u5feb\u200b\u597d\u7701\u200b\u5e76\u200b\u667a\u80fd\u200b\u3002\u200b\u57fa\u4e8e\u200b\u6df1\u5ea6\u200b\u5b66\u4e60\u200b\u7684\u200bOCR\u200b\u6280\u672f\u200b\uff0c\u200b\u4e3b\u6253\u200b\u4eba\u5de5\u667a\u80fd\u200b\u4f18\u52bf\u200b\u53ca\u200b\u5c0f\u200b\u6a21\u578b\u200b\uff0c\u200b\u4ee5\u200b\u901f\u5ea6\u200b\u4e3a\u200b\u4f7f\u547d\u200b\uff0c\u200b\u6548\u679c\u200b\u4e3a\u200b\u5bfc\u5411\u200b\u3002

\u200b\u4f7f\u7528\u200b\uff1a

  • \u200b\u5982\u679c\u200b\u4ed3\u5e93\u200b\u4e0b\u200b\u5df2\u6709\u200b\u6a21\u578b\u200b\u6ee1\u8db3\u8981\u6c42\u200b \u2192 RapidOCR\u200b\u90e8\u7f72\u200b\u4f7f\u7528\u200b\u5373\u53ef\u200b\u3002
  • \u200b\u4e0d\u200b\u6ee1\u8db3\u8981\u6c42\u200b \u2192 \u200b\u57fa\u4e8e\u200bPaddleOCR\u200b\u5728\u200b\u81ea\u5df1\u200b\u6570\u636e\u200b\u4e0a\u200b\u5fae\u8c03\u200b \u2192 RapidOCR\u200b\u90e8\u7f72\u200b\u3002

\u200b\u5982\u679c\u200b\u8be5\u200b\u4ed3\u5e93\u200b\u6709\u200b\u5e2e\u52a9\u200b\u5230\u200b\u4f60\u200b\uff0c\u200b\u8fd8\u200b\u8bf7\u200b\u70b9\u4e2a\u200b\u5c0f\u661f\u661f\u200b\u2b50\u200b\u5457\u200b\uff01

"},{"location":"#_2","title":"\u6574\u4f53\u200b\u6846\u67b6","text":"
flowchart LR\n    subgraph Step\n    direction TB\n    C(Text Det) --> D(Text Cls) --> E(Text Rec)\n    end\n\n    A[/OurSelf Dataset/] --> B(PaddleOCR) --Train--> Step --> F(PaddleOCRModelConverter)\n    F --ONNX--> G{RapidOCR Deploy\\n<b>Python/C++/Java/C#</b>}\n    G --> H(Windows x86/x64) & I(Linux) & J(Android) & K(Web) & L(Raspberry Pi)\n\n    click B \"https://github.com/PaddlePaddle/PaddleOCR\" _blank\n    click F \"https://github.com/RapidAI/PaddleOCRModelConverter\" _blank
"},{"location":"#more","title":"\u6548\u679c\u200b\u5c55\u793a\u200b\uff08more\uff09","text":""},{"location":"#_3","title":"\u8d21\u732e\u8005","text":""},{"location":"#_4","title":"\u5f15\u7528","text":"

\u200b\u5982\u679c\u200b\u60a8\u200b\u53d1\u73b0\u200b\u8be5\u200b\u9879\u76ee\u200b\u5bf9\u200b\u60a8\u200b\u7684\u200b\u7814\u7a76\u200b\u6709\u7528\u200b\uff0c\u200b\u8bf7\u200b\u8003\u8651\u200b\u5f15\u7528\u200b\uff1a

@misc{RapidOCR 2021,\n    title={{Rapid OCR}: OCR Toolbox},\n    author={RapidAI Team},\n    howpublished = {\\url{https://github.com/RapidAI/RapidOCR}},\n    year={2021}\n}\n
"},{"location":"#star-history","title":"Star history","text":""},{"location":"#_5","title":"\u5f00\u6e90\u200b\u8bb8\u53ef\u8bc1","text":"

OCR\u200b\u6a21\u578b\u200b\u7248\u6743\u200b\u5f52\u200b\u767e\u5ea6\u200b\u6240\u6709\u200b\uff0c\u200b\u5176\u4ed6\u200b\u5de5\u7a0b\u200b\u4ee3\u7801\u200b\u7248\u6743\u200b\u5f52\u672c\u200b\u4ed3\u5e93\u200b\u6240\u6709\u8005\u200b\u6240\u6709\u200b\u3002

\u200b\u8be5\u200b\u9879\u76ee\u200b\u91c7\u7528\u200b Apache 2.0 license \u200b\u5f00\u6e90\u200b\u8bb8\u53ef\u8bc1\u200b\u3002

"},{"location":"business_support/","title":"\u5546\u4e1a\u200b\u652f\u6301","text":""},{"location":"business_support/#ai","title":"\u670d\u52a1\u200b\u4e00\u200b\uff1aAI\u200b\u76f8\u5173\u200b\u95ee\u9898\u200b\u54a8\u8be2","text":"
  • \u200b\u52a0\u5165\u200b\u77e5\u8bc6\u200b\u661f\u7403\u200bRapidAI\u200b\u79c1\u4eab\u200b\u7fa4\u200b\uff0c\u200b\u76ee\u524d\u200b\u661f\u7403\u200b\u5df2\u6709\u200bC++/Rust/Go/Python\u200b\u4ee5\u53ca\u200bAI\u200b\u5927\u4f6c\u200b\u52a0\u5165\u200b\u3002
  • \u200b\u8fd9\u91cc\u200b\u7684\u200b\u63d0\u95ee\u200b\u4f1a\u200b\u4f18\u5148\u200b\u5f97\u5230\u200b\u8be6\u5c3d\u200b\u56de\u7b54\u200b\u548c\u200b\u652f\u6301\u200b\uff0c\u200b\u4e5f\u200b\u4f1a\u200b\u4eab\u53d7\u200b\u5230\u200bRapidAI\u200b\u7ec4\u7ec7\u200b\u540e\u7eed\u200b\u6301\u7eed\u200b\u4f18\u8d28\u200b\u7684\u200b\u670d\u52a1\u200b\u3002
  • \u200b\u6b22\u8fce\u200b\u52a0\u5165\u200b\u3002
"},{"location":"business_support/#cpu","title":"\u670d\u52a1\u200b\u4e8c\u200b\uff1a\u200b\u4fe1\u521b\u200bCPU\u200b\u652f\u6301","text":"
  • \u200b\u63d0\u4f9b\u200b\u4fe1\u521b\u200b\u5e73\u53f0\u200b\u591a\u200b\u67b6\u6784\u200b\uff0c\u200b\u5305\u62ec\u200bArm/X86/mips(\u200b\u9f99\u82af\u200b)/RISC-V\u200b\u7b49\u200b\u4fe1\u521b\u200bCPU\u200b\u652f\u6301\u200b\uff0c\u200b\u540c\u65f6\u200b\u517c\u5bb9\u200bONNXRuntime/OpenVINO/NCNN\u3002
  • \u200b\u6709\u610f\u8005\u200b\u90ae\u4ef6\u200b\u8054\u7cfb\u200b: znsoft@163.com, \u200b\u8bf7\u200b\u5148\u200b\u90ae\u4ef6\u200b\u54a8\u8be2\u670d\u52a1\u200b\u9879\u76ee\u200b\uff0c\u200b\u5373\u65f6\u200b\u56de\u590d\u200b\u8054\u7cfb\u65b9\u5f0f\u200b\u3002
"},{"location":"business_support/#ocr-docker","title":"\u670d\u52a1\u200b\u4e09\u200b\uff1a\u200b\u56fd\u4ea7\u200b\u64cd\u4f5c\u7cfb\u7edf\u200bOCR Docker\u200b\u90e8\u7f72","text":"
  • \u200b\u63d0\u4f9b\u200b\u56fd\u4ea7\u200b\u64cd\u4f5c\u7cfb\u7edf\u200b\uff08\u200b\u6d77\u5149\u200b\u3001\u200b\u4e2d\u79d1\u200b\u65b9\u5fb7\u200b\u3001\u200b\u9e92\u9e9f\u200b\u7b49\u7b49\u200b\uff09OCR Docker\u200b\u90e8\u7f72\u200b\u670d\u52a1\u200b\u3002
  • \u200b\u6709\u610f\u8005\u200b \u2192 \u2709 liekkaskono@163.com
"},{"location":"communicate/","title":"\u4ea4\u6d41\u200b\u7fa4","text":"

\u200b\u53ef\u200b\u901a\u8fc7\u200b\u4ee5\u4e0b\u200b\u65b9\u5f0f\u200b\u4e0e\u200bRapidOCR\u200b\u7ef4\u62a4\u8005\u200bSWHL\u200b\u8fdb\u884c\u200b\u6c9f\u901a\u200b\uff0c\u200b\u4e5f\u200b\u6b22\u8fce\u200b\u53cd\u9988\u200b\u4f7f\u7528\u200b\u8fc7\u7a0b\u200b\u4e2d\u200b\u9047\u5230\u200b\u7684\u200b\u95ee\u9898\u200b\u3002

"},{"location":"communicate/#rapidai","title":"\u77e5\u8bc6\u200b\u661f\u7403\u200bRapidAI\u200b\u79c1\u4eab\u200b\u7fa4","text":"

\u200b\u8fd9\u91cc\u200b\u7684\u200b\u63d0\u95ee\u200b\u4f1a\u200b\u4f18\u5148\u200b\u5f97\u5230\u200b\u56de\u7b54\u200b\u548c\u200b\u652f\u6301\u200b\uff0c\u200b\u4e5f\u200b\u4f1a\u200b\u4eab\u53d7\u200b\u5230\u200bRapidAI\u200b\u7ec4\u7ec7\u200b\u540e\u7eed\u200b\u6301\u7eed\u200b\u4f18\u8d28\u200b\u7684\u200b\u670d\u52a1\u200b\uff0c\u200b\u6b22\u8fce\u200b\u5927\u5bb6\u200b\u7684\u200b\u52a0\u5165\u200b\u3002

"},{"location":"communicate/#_1","title":"\u5fae\u4fe1\u200b\u4ea4\u6d41\u200b\u7fa4","text":"

\u200b\u5fae\u4fe1\u200b\u626b\u63cf\u200b\u4ee5\u4e0b\u200b\u4e8c\u7ef4\u7801\u200b\uff0c\u200b\u5173\u6ce8\u200bRapidAI\u200b\u516c\u4f17\u200b\u53f7\u200b\uff0c\u200b\u56de\u590d\u200b OCR \u200b\u5373\u53ef\u200b\u52a0\u5165\u200bRapidOCR\u200b\u5fae\u4fe1\u200b\u4ea4\u6d41\u200b\u7fa4\u200b\uff1a

"},{"location":"communicate/#qq","title":"QQ\u200b\u4ea4\u6d41\u200b\u7fa4","text":"

\u200b\u6b22\u8fce\u200b\u52a0\u5165\u200b\u6211\u4eec\u200b\u7684\u200bQQ\u200b\u7fa4\u200b\u4e0b\u8f7d\u200b\u6a21\u578b\u200b\u53ca\u200b\u6d4b\u8bd5\u7a0b\u5e8f\u200b\u3002\u200b\u7fa4\u53f7\u200b\u4e3a\u200b\uff1a755960114

"},{"location":"online_demo/","title":"\u5728\u7ebf\u200bdemo","text":""},{"location":"online_demo/#_1","title":"\u7b80\u4ecb","text":"
  • Hugging Face\u200b\u4e0a\u200b\u7684\u200bDemo\u200b\u548c\u200b\u9b54\u200b\u642d\u200bDemo\u200b\u662f\u200b\u540c\u200b\u4e00\u5957\u200b\u4ee3\u7801\u200b\uff0c\u200b\u90fd\u200b\u662f\u200b\u57fa\u4e8e\u200bstreamlit\u200b\u642d\u5efa\u200b\u800c\u6765\u200b\u7684\u200b\u3002
  • \u200b\u4e24\u8005\u200b\u533a\u522b\u200b\u5728\u4e8e\u200b\uff0c\u200b\u9b54\u200b\u642d\u200b\u662f\u200b\u56fd\u5185\u200b\u5e73\u53f0\u200b\uff0c\u200b\u4e0d\u200b\u9700\u8981\u200b\u79d1\u5b66\u200b\u4e0a\u7f51\u200b\u5373\u53ef\u200b\u8bbf\u95ee\u200b\u4f7f\u7528\u200b\uff1bHugging Face\u200b\u5219\u200b\u9700\u8981\u200b\u79d1\u5b66\u200b\u4e0a\u7f51\u200b\u3002
  • \u200b\u642d\u5efa\u200bdemo\u200b\u7684\u200b\u76ee\u7684\u200b\u5728\u4e8e\u200b\uff1a
    • \u200b\u5feb\u901f\u200b\u67e5\u770b\u200b\u6307\u5b9a\u200b\u56fe\u50cf\u200b\u7684\u200b\u8bc6\u522b\u200b\u6548\u679c\u200b\u548c\u200b\u8bc6\u522b\u200b\u65f6\u200b\u957f\u200b
    • \u200b\u5feb\u901f\u200b\u6bd4\u8f83\u200b\u4e0d\u540c\u200b\u7248\u672c\u200b\u7684\u200b\u68c0\u6d4b\u200b\u548c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u6548\u679c\u200b\u5dee\u5f02\u200b
"},{"location":"online_demo/#demo","title":"\u5728\u7ebf\u200bDemo","text":"
  • Hugging Face:
  • \u200b\u963f\u91cc\u200b\u9b54\u200b\u642d\u200b\u793e\u533a\u200b\uff1a
  • \u200b\u767e\u5ea6\u200b\u661f\u6cb3\u200b\u793e\u533a\u200b\uff1a
"},{"location":"online_demo/#demo_1","title":"Demo\u200b\u6e90\u7801","text":"
  • Hugging Face: https://huggingface.co/spaces/SWHL/RapidOCRDemo/tree/main
  • \u200b\u9b54\u200b\u642d\u200b\u793e\u533a\u200b: https://www.modelscope.cn/studios/liekkas/RapidOCRDemo/files
  • \u200b\u767e\u5ea6\u200b\u661f\u6cb3\u200b\u793e\u533a\u200b\uff1a https://aistudio.baidu.com/app/highcode/33121/files
"},{"location":"quickstart/","title":"\u5feb\u901f\u200b\u5f00\u59cb","text":""},{"location":"quickstart/#1","title":"1. \u200b\u5b89\u88c5","text":"
pip install rapidocr_onnxruntime\n
"},{"location":"quickstart/#2","title":"2. \u200b\u4f7f\u7528","text":"\u547d\u4ee4\u884c\u200b\u4f7f\u7528\u200bPython\u200b\u4f7f\u7528\u200b 
rapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg\n
from rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\n\nimg_path = 'tests/test_files/ch_en_num.jpg'\nresult, elapse = engine(img_path)\nprint(result)\n
"},{"location":"quickstart/#3","title":"3. \u200b\u67e5\u770b\u200b\u6548\u679c","text":"
[\n    [[[9.0, 2.0], [321.0, 11.0], [318.0, 102.0], [6.0, 93.0]], '\u200b\u6b63\u54c1\u200b\u4fc3\u9500\u200b', '0.7986101984977723'],\n    [[[70.0, 98.0], [251.0, 98.0], [251.0, 125.0], [70.0, 125.0]], '\u200b\u5927\u200b\u6876\u88c5\u200b\u66f4\u200b\u5212\u7b97\u200b', '0.7368737288883754'],\n    [[[69.0, 144.0], [255.0, 144.0], [255.0, 164.0], [69.0, 164.0]], '\u200b\u5f3a\u529b\u200b\u53bb\u6c61\u200b\u7b26\u5408\u200b\u56fd\u6807\u200b', '0.8172478278477987'],\n    [[[107.0, 170.0], [219.0, 170.0], [219.0, 182.0], [107.0, 182.0]], '-40\u200b\u6df1\u5ea6\u200b\u9632\u51bb\u200b\u4e0d\u200b\u7ed3\u51b0\u200b', '0.8655969283797524'],\n    [[[35.0, 227.0], [63.0, 227.0], [63.0, 236.0], [35.0, 236.0]], '\u200b\u65e5\u5e38\u200b\u4ef7\u200b?', '0.6502826035022735'],\n    [[[141.0, 223.0], [187.0, 225.0], [185.0, 249.0], [139.0, 247.0]], '\u200b\u76f4\u51fb\u200b', '0.596031109491984'],\n    [[[34.0, 234.0], [81.0, 236.0], [80.0, 254.0], [33.0, 252.0]], '10.0\u200b\u8d77\u200b', '0.8231529593467712'],\n    [[[257.0, 234.0], [304.0, 236.0], [303.0, 253.0], [256.0, 251.0]], '10.0\u200b\u8d77\u200b', '0.8304102122783661'],\n    [[[258.0, 227.0], [287.0, 226.0], [287.0, 236.0], [258.0, 237.0]], '\u200b\u65e5\u5e38\u200b\u4ef7\u200b?', '0.5725070595741272'],\n    [[[140.0, 245.0], [186.0, 246.0], [186.0, 272.0], [139.0, 271.0]], '\u200b\u5e95\u4ef7\u200b', '0.5142453710238138'],\n    [[[129.0, 290.0], [207.0, 292.0], [206.0, 339.0], [128.0, 337.0]], '5.8', '0.6341951936483383'],\n    [[[98.0, 320.0], [129.0, 320.0], [129.0, 331.0], [98.0, 331.0]], '\u200b\u5238\u540e\u200b\u4ef7\u200b?', '0.6209247708320618'],\n    [[[114.0, 343.0], [210.0, 343.0], [210.0, 355.0], [114.0, 355.0]], '\u200b\u60ca\u559c\u200b\u798f\u5229\u200b\u4e0d\u200b\u5bb9\u9519\u8fc7\u200b', '0.8640043867958916'],\n    [[[69.0, 363.0], [151.0, 363.0], [151.0, 383.0], [69.0, 383.0]], '\u200b\u6781\u901f\u200b\u53d1\u8d27\u200b', '0.7552512288093567'],\n    [[[201.0, 363.0], [285.0, 363.0], [285.0, 383.0], [201.0, 383.0]], '\u200b\u51b0\u70b9\u200b\u6807\u51c6\u200b', '0.7194759607315063'],\n    [[[68.0, 392.0], [151.0, 392.0], [151.0, 412.0], [68.0, 412.0]], '\u200b\u7834\u635f\u200b\u5c31\u200b\u8d54\u200b', '0.7711991906166077'],\n    [[[202.0, 391.0], [285.0, 391.0], [285.0, 413.0], [202.0, 413.0]], '\u200b\u5047\u4e00\u200b\u8d54\u5341\u200b', '0.6546663284301758']\n]\n
"},{"location":"quickstart/#_1","title":"\u63a8\u8350\u200b\u9605\u8bfb","text":""},{"location":"quickstart/#api","title":"API","text":""},{"location":"quickstart/#_2","title":"\u5176\u4ed6\u200b\u7f16\u7a0b\u8bed\u8a00\u200b\u652f\u6301","text":""},{"location":"related_projects/","title":"\u5468\u8fb9\u200b\u9879\u76ee","text":""},{"location":"related_projects/#_1","title":"\u63a8\u7406\u200b\u90e8\u7f72","text":"\u7f16\u7a0b\u8bed\u8a00\u200b \u200b\u5bf9\u5e94\u200b\u9879\u76ee\u200b Python RapidOCR C++ RapidOcrOnnx C++ RapidOcrNcnn Java RapidOcr\u2014Java Java RapidOcrOnnxJvm Java RapidOcrNcnnJvm C# RapidOCRCSharp Android RapidOcrAndroidOnnx Android RapidOcrAndroidOnnxCompose \u200b\u6613\u8bed\u8a00\u200b RapidOCRServer"},{"location":"related_projects/#_2","title":"\u667a\u80fd\u200b\u6587\u6863","text":"\u9879\u76ee\u540d\u79f0\u200b \u200b\u529f\u80fd\u200b RapidStructure \u200b\u6587\u6863\u200b\u7ed3\u6784\u5316\u200b\u4ed3\u5e93\u200b\uff0c\u200b\u5305\u62ec\u200b\u6587\u6863\u200b\u65b9\u5411\u200b\u5206\u7c7b\u200b\u3001\u200b\u7248\u9762\u200b\u5206\u6790\u200b\u548c\u200b\u8868\u683c\u200b\u8bc6\u522b\u200b RapidLaTexOCR \u200b\u516c\u5f0f\u200b\u8bc6\u522b\u200b TableStructureRec \u200b\u8868\u683c\u200b\u8bc6\u522b\u200b RapidLayout \u200b\u7248\u9762\u200b\u5206\u6790\u200b RapidOCRPDF PDF\u200b\u63d0\u53d6\u200b ExtractOfficeContent Office\u200b\u5185\u5bb9\u200b\u63d0\u53d6"},{"location":"related_projects/#_3","title":"\u8f6c\u6362\u200b\u5de5\u5177","text":"\u9879\u76ee\u540d\u79f0\u200b \u200b\u529f\u80fd\u200b PaddleOCRModelConvert PaddleOCR\u200b\u6a21\u578b\u200b\u8f6c\u6362\u200b\u5de5\u5177\u200b LabelConvert \u200b\u76ee\u6807\u200b\u68c0\u6d4b\u200b\u6570\u636e\u200b\u96c6\u200b\u683c\u5f0f\u200b\u8f6c\u6362"},{"location":"related_projects/#_4","title":"\u8bc4\u6d4b\u200b\u5de5\u5177","text":"\u9879\u76ee\u540d\u79f0\u200b \u200b\u529f\u80fd\u200b TextDetMetric \u200b\u8ba1\u7b97\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u7b97\u6cd5\u200b\u8bc4\u6d4b\u200b\u6307\u6807\u200b TableRecognitionMetric \u200b\u8ba1\u7b97\u200b\u8868\u683c\u200b\u8bc6\u522b\u200b\u7b97\u6cd5\u200b\u8bc4\u6d4b\u200b\u6307\u6807"},{"location":"related_projects/#_5","title":"\u6d4b\u8bc4\u200b\u96c6","text":"\u9879\u76ee\u540d\u79f0\u200b \u200b\u529f\u80fd\u200b text_det_test_dataset \u200b\u6587\u672c\u200b\u6d4b\u8bd5\u200b\u96c6\u200b text_rec_test_dataset \u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6d4b\u8bd5\u200b\u96c6\u200b table_rec_test_dataset \u200b\u8868\u683c\u200b\u8bc6\u522b\u200b\u6d4b\u8bd5\u200b\u96c6"},{"location":"related_projects/#_6","title":"\u573a\u666f\u200b\u5e94\u7528","text":"\u9879\u76ee\u540d\u79f0\u200b \u200b\u529f\u80fd\u200b RapidVideOCR \u200b\u89c6\u9891\u200b\u786c\u200b\u5b57\u5e55\u200b\u63d0\u53d6\u200b\u5de5\u5177"},{"location":"sponsor/","title":"\u8d5e\u52a9","text":""},{"location":"sponsor/#_1","title":"\u5199\u200b\u5728\u200b\u524d\u9762","text":"

\u200b\u6211\u200b\u559c\u6b22\u200b\u5f00\u6e90\u200b\uff0c\u200b\u559c\u6b22\u200bAI\u200b\u6280\u672f\u200b\uff0c\u200b\u56e0\u4e3a\u200b\u6211\u200b\u8ba4\u4e3a\u200b\u5f00\u6e90\u200b\u548c\u200bAI\u200b\u4f1a\u4e3a\u200b\u6709\u200b\u9700\u8981\u200b\u7684\u200b\u4eba\u200b\u5e26\u6765\u200b\u65b9\u4fbf\u200b\u548c\u200b\u5e2e\u52a9\u200b\uff0c\u200b\u4e5f\u200b\u4f1a\u200b\u8ba9\u200b\u8fd9\u4e2a\u200b\u4e16\u754c\u200b\u53d8\u5f97\u200b\u66f4\u597d\u200b\u3002\u200b\u901a\u8fc7\u200b\u5bf9\u200b\u8fd9\u4e9b\u200b\u9879\u76ee\u200b\u7684\u200b\u6350\u8d60\u200b\uff0c\u200b\u60a8\u200b\u53ef\u4ee5\u200b\u548c\u200b\u6211\u200b\u4e00\u9053\u200b\u8ba9\u200bAI\u200b\u4e3a\u200b\u66f4\u200b\u591a\u200b\u4eba\u200b\u5e26\u6765\u200b\u6e29\u6696\u200b\u548c\u200b\u7f8e\u597d\u200b\u3002

I like open source and AI technology because I think open source and AI will bring convenience and help to people in need, and will also make the world a better place. By donating to these projects, you can join me in making AI bring warmth and beauty to more people.

"},{"location":"sponsor/#alipay-reward-or-wechat-reward","title":"\u652f\u4ed8\u5b9d\u200b\u6216\u200b\u5fae\u4fe1\u200b\u6253\u8d4f\u200b (Alipay reward or WeChat reward)","text":"

\u200b\u901a\u8fc7\u200b\u652f\u4ed8\u5b9d\u200b\u6216\u8005\u200b\u5fae\u4fe1\u200b\u7ed9\u200b\u4f5c\u8005\u200b\u6253\u8d4f\u200b\uff0c\u200b\u8bf7\u200b\u5199\u200b\u597d\u200b\u5907\u6ce8\u200b\u3002 Give the me a reward through Alipay or WeChat.

"},{"location":"sponsor/#buy-me-a-coffee","title":"Buy me a Coffee","text":"

If you are not in mainland China, you can also support the me through:

"},{"location":"visualization/","title":"\u6548\u679c\u200b\u5c55\u793a","text":""},{"location":"blog/","title":"Blog","text":""},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/","title":"\u5e38\u89c1\u95ee\u9898\u200b (FAQ)","text":""},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-onnxruntime-gpucpu","title":"Q: \u200b\u4e3a\u4ec0\u4e48\u200b\u6211\u200b\u7684\u200b\u6a21\u578b\u200b\u5728\u200bONNXRuntime GPU\u200b\u7248\u4e0a\u200b\u6bd4\u200b\u5728\u200bCPU\u200b\u4e0a\u200b\u8fd8\u8981\u200b\u6162\u200b\uff1f","text":"

A: \u200b\u56e0\u4e3a\u200bOCR\u200b\u4efb\u52a1\u200b\u4e2d\u200b\u8f93\u5165\u200b\u56fe\u50cf\u200bShape\u200b\u662f\u200b\u52a8\u6001\u200b\u7684\u200b\u3002\u200b\u6bcf\u6b21\u200bGPU\u200b\u4e0a\u200b\u90fd\u200b\u9700\u8981\u200b\u91cd\u65b0\u200b\u6e05\u7a7a\u200b\u4e0a\u200b\u4e00\u6b21\u200b\u4e0d\u540c\u200bShape\u200b\u7684\u200b\u7f13\u5b58\u200b\u7ed3\u679c\u200b\u3002\u200b\u5982\u679c\u200b\u8f93\u5165\u200b\u56fe\u50cf\u200bShape\u200b\u4e0d\u53d8\u200b\u7684\u200b\u60c5\u51b5\u200b\u4e0b\u200b\uff0cONNXRuntime GPU\u200b\u7248\u200b\u4e00\u822c\u200b\u90fd\u200b\u8981\u200b\u6bd4\u200bCPU\u200b\u5feb\u200b\u7684\u200b\u3002\u200b\u8be5\u200b\u95ee\u9898\u200b\u5df2\u7ecf\u200b\u63d0\u4e86\u200b\u76f8\u5173\u200bissue\uff08issue #13198\uff09\u3002

\u200b\u63a8\u8350\u200bCPU\u200b\u7aef\u200b\u63a8\u7406\u200b\u7528\u200brapidocr_onnxruntime\u200b\u6216\u8005\u200brapidocr_openvino\uff0cGPU\u200b\u7aef\u7528\u200brapidocr_paddle\u3002\u200b\u5173\u4e8e\u200brapidocr_onnxruntime\u200b\u548c\u200brapidocr_paddle\u200b\u4e24\u8005\u4e4b\u95f4\u200b\u63a8\u7406\u200b\uff0c\u200b\u53ef\u200b\u53c2\u89c1\u200b\uff1adocs

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-32c","title":"Q: \u200b\u8bf7\u95ee\u200b\u8fd9\u4e2a\u200b\u80fd\u200b\u5728\u200b32\u200b\u4f4d\u200bC#\u200b\u4e2d\u7528\u200b\u561b\u200b?","text":"

A: C#\u200b\u53ef\u4ee5\u200b32\u200b\u4f4d\u200b\uff0c\u200b\u8981\u200b\u7528\u200b32\u200b\u4f4d\u200b\u7684\u200bdll\uff0c\u200b\u4f46\u200bnuget\u200b\u4e0a\u200b\u7684\u200bonnxruntime\u200b\u4e0d\u200b\u652f\u6301\u200bwin7\u3002

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-windowsoserror-winerror-126","title":"Q: Windows\u200b\u7cfb\u7edf\u200b\u4e0b\u200b\uff0c\u200b\u88c5\u5b8c\u200b\u73af\u5883\u200b\u4e4b\u540e\u200b\uff0c\u200b\u8fd0\u884c\u200b\u793a\u4f8b\u200b\u7a0b\u5e8f\u200b\u4e4b\u540e\u200b\uff0c\u200b\u62a5\u9519\u200bOSError: [WinError 126] \u200b\u627e\u200b\u4e0d\u5230\u200b\u6307\u5b9a\u200b\u7684\u200b\u6a21\u7d44","text":"

A: \u200b\u539f\u56e0\u200b\u662f\u200bShapely\u200b\u5e93\u200b\u6ca1\u6709\u200b\u6b63\u786e\u200b\u5b89\u88c5\u200b\uff0c\u200b\u5982\u679c\u200b\u662f\u200b\u5728\u200bWindows\uff0c\u200b\u53ef\u4ee5\u200b\u5728\u200bShapely whl\u200b\u4e0b\u8f7d\u200b\u5bf9\u5e94\u200b\u7684\u200bwhl\u200b\u5305\u200b\uff0c\u200b\u79bb\u7ebf\u200b\u5b89\u88c5\u200b\u5373\u53ef\u200b\uff1b\u200b\u53e6\u5916\u200b\u4e00\u79cd\u200b\u89e3\u51b3\u529e\u6cd5\u200b\u662f\u200b\u7528\u200bconda\u200b\u5b89\u88c5\u200b\u4e5f\u200b\u53ef\u200b\u3002

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-linuxpythonimport-cv2importerror-ligglso1-cannot-open-shared-object-file-no-such-file-or-directory","title":"Q: Linux\u200b\u90e8\u7f72\u200bpython\u200b\u7684\u200b\u7a0b\u5e8f\u200b\u65f6\u200b\uff0cimport cv2\u200b\u65f6\u4f1a\u200b\u62a5\u200bImportError: ligGL.so.1: cannot open shared object file: No such file or directory?","text":"

A: \u200b\u89e3\u51b3\u200b\u65b9\u6cd5\u200b \u200b\u6709\u200b\u4e24\u4e2a\u200b(\u200b\u6765\u81ea\u200b\u7fa4\u53cb\u200bddeef)\uff1a

  1. \u200b\u5b89\u88c5\u200bopencv-python-headless\u200b\u53d6\u4ee3\u200bopencv-python;
  2. \u200b\u8fd0\u884c\u200bsudo apt-get install -y libgl1-mesa-dev
"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-win7cmd","title":"Q: \u200b\u8be2\u95ee\u200b\u4e0b\u200b\uff0c\u200b\u6211\u200b\u7f16\u8bd1\u200b\u51fa\u6765\u200b\u7684\u200b\u8fdb\u7a0b\u200b\u5728\u200bwin7\u200b\u4e0b\u9762\u200b\u901a\u8fc7\u200bcmd\u200b\u8c03\u7528\u200b\uff0c\u200b\u53d1\u751f\u200b\u4e86\u200b\u5d29\u6e83\u200b\u7684\u200b\u60c5\u51b5\u200b?","text":"

A: \u200b\u4e0d\u200b\u652f\u6301\u200bwin7 (by @\u200b\u5982\u679c\u200b\u6211\u200b\u6709\u200b\u6642\u5149\u6a5f\u200b)

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-openmmlab","title":"Q: \u200b\u80fd\u200b\u4e0d\u80fd\u200b\u641e\u4e2a\u200bopenmmlab\u200b\u7c7b\u4f3c\u200b\u7684\u200b\u90a3\u4e2a\u200b\u63d0\u53d6\u200b\u4fe1\u606f\u200b\u7684\u200b?","text":"

A: \u200b\u8fd9\u4e2a\u200b\u76ee\u524d\u200b\u6b63\u5728\u200b\u8c03\u7814\u200b\u6d4b\u8bd5\u200b\u5f53\u4e2d\u200b\uff0c\u200b\u5982\u679c\u200bmmocr\u200b\u4e2d\u200b\u5173\u952e\u200b\u4fe1\u606f\u63d0\u53d6\u200b\u6548\u679c\u200b\u8fd8\u200b\u53ef\u4ee5\u200b\uff0c\u200b\u540e\u671f\u200b\u4f1a\u200b\u8003\u8651\u200b\u6574\u5408\u200b\u8fdb\u6765\u200b\u3002

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-rapidocrpaddleocr","title":"Q: RapidOCR\u200b\u548c\u200bPaddleOCR\u200b\u662f\u200b\u4ec0\u4e48\u200b\u5173\u7cfb\u200b\u5462\u200b\uff1f","text":"

A: RapidOCR\u200b\u662f\u200b\u5c06\u200bPaddleOCR\u200b\u7684\u200b\u9884\u200b\u8bad\u7ec3\u200b\u6a21\u578b\u200b\u8f6c\u4e3a\u200bonnx\u200b\u6a21\u578b\u200b\uff0c\u200b\u4e0d\u200b\u4f9d\u8d56\u200bpaddle\u200b\u6846\u67b6\u200b\uff0c\u200b\u65b9\u4fbf\u200b\u5404\u4e2a\u200b\u5e73\u53f0\u200b\u90e8\u7f72\u200b\u3002

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-onnxruntime-arm32-libonnxruntimeso-error-file-not-recognized-file-format-not-recognized","title":"Q: onnxruntime arm32 \u200b\u6709\u4eba\u200b\u7f16\u8bd1\u200b\u8fc7\u200b\u5417\u200b\uff1f \u200b\u6211\u200b\u7f16\u8bd1\u200b\u6210\u529f\u200b\u4e86\u200b\uff0c\u200b\u4f46\u662f\u200b\u4f7f\u7528\u200b\u7684\u200b\u65f6\u5019\u200blibonnxruntime.so error: file not recognized: File format not recognized \u200b\u5e94\u8be5\u200b\u662f\u200b\u7248\u672c\u200b\u4e0d\u200b\u5339\u914d","text":"

A: \u200b\u6ca1\u200b\u9047\u5230\u200b\u8fc7\u200b\u3002\u200b\u6211\u200b\u662f\u200b\u76f4\u63a5\u200b\u5728\u200b\u5f53\u524d\u200b\u5e73\u53f0\u200b\u7f16\u8bd1\u200b\u7684\u200b\uff0c\u200b\u6211\u4eec\u200b\u7528\u200b\u7684\u200b\u662f\u200barm\u3002\u200b\u4f30\u8ba1\u200b\u662f\u200b\u5e73\u53f0\u200b\u4e0d\u200b\u517c\u5bb9\u200b,\u200b\u5efa\u8bae\u200b\u5728\u200b\u672c\u8eab\u200b\u5e73\u53f0\u200b\u4e0a\u200b\u7f16\u8bd1\u200b\u3002\u200b\u6ca1\u200b\u9047\u5230\u200b\u8fc7\u200b\u95ee\u9898\u200b\u3002\u200b\u901a\u5e38\u200b\u51fa\u200b\u5728\u200b\u4ea4\u53c9\u200b\u7f16\u8bd1\u200b\u65b9\u5f0f\u200b\u4e0b\u200b\u3002

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-c-demovs2017","title":"Q: \u200b\u8bf7\u95ee\u200b\u4e00\u4e0b\u200bc++ demo\u200b\u5fc5\u987b\u200b\u8981\u200bvs2017\u200b\u53ca\u200b\u4ee5\u4e0a\u200b\u7248\u672c\u200b\u5417\u200b?","text":"

A: \u200b\u6700\u597d\u200b\u7528\u200bvs2019

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-easyedge-free-app","title":"Q: \u200b\u53ef\u4ee5\u200b\u8fbe\u5230\u200b\u767e\u5ea6\u200bEasyEdge Free App\u200b\u7684\u200b\u6548\u679c\u200b\u5417\u200b\uff1f","text":"

A: edge\u200b\u7684\u200b\u6a21\u578b\u200b\u5e94\u8be5\u200b\u6ca1\u6709\u200b\u5f00\u6e90\u200b\u3002\u200b\u767e\u5ea6\u200b\u5f00\u6e90\u200b\u7684\u200b\u6a21\u578b\u200b\u91cc\u200bserver det\u200b\u7684\u200b\u8bc6\u522b\u200b\u6548\u679c\u200b\u53ef\u4ee5\u200b\u8fbe\u5230\u200b\uff0c\u200b\u4f46\u662f\u200b\u6a21\u578b\u200b\u6bd4\u8f83\u200b\u5927\u200b\u3002

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-connxcpugpu","title":"Q: \u200b\u6211\u7528\u200bc++\u200b\u63a8\u7406\u200bonnx\u200b\u8c8c\u4f3c\u200b\u662f\u200bcpu\u200b\u63a8\u7406\u200b\u7684\u200b\uff0cgpu\u200b\u6ca1\u6709\u200b\u53cd\u5e94\u200b?","text":"

A: \u200b\u5982\u679c\u200b\u60f3\u200b\u7528\u200bGPU\u200b\u7684\u8bdd\u200b\uff0c\u200b\u9700\u8981\u200b\u5b89\u88c5\u200bonnxruntime-gpu\u200b\u7248\u200b\uff0c\u200b\u81ea\u5df1\u200b\u5728\u200bonnxruntime\u200b\u7684\u200b\u4ee3\u7801\u200b\u4e2d\u200b\u6dfb\u52a0\u200bEP (execution provider)\u3002\u200b\u6211\u4eec\u200b\u7684\u200b\u5b9a\u4f4d\u200b\u662f\u200b\u901a\u7528\u200b\uff0c\u200b\u53ea\u7528\u200bcpu\u200b\u63a8\u7406\u200b\u3002

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-ocrlinuxocr","title":"Q: \u200b\u60a8\u597d\u200b\uff0c\u200b\u6211\u200b\u60f3\u200b\u90e8\u7f72\u200b\u4e0b\u200b\u54b1\u4eec\u200b\u7684\u200bocr\u200b\u8bc6\u522b\u200b\uff0c\u200b\u6709\u200b\u63d0\u4f9b\u200blinux\u200b\u7248\u672c\u200b\u7684\u200bocr\u200b\u90e8\u7f72\u200b\u5305\u200b\u5417\u200b?","text":"

A: linux\u200b\u7248\u672c\u200b\u7684\u200b\u81ea\u5df1\u200b\u7f16\u8bd1\u200b\u5373\u53ef\u200b, \u200b\u53ef\u4ee5\u200b\u53c2\u8003\u200b\u6211\u4eec\u200b\u7684\u200baction\u200b\u4e2d\u200b\u7684\u200b\u811a\u672c\u200b\uff1b\u200b\u5176\u5b9e\u200b\u7f16\u8bd1\u200b\u975e\u5e38\u5bb9\u6613\u200b\uff0c\u200b\u5b89\u88c5\u200b\u4e2a\u200bopencv\u200b\u540e\u200b\uff0c\u200b\u5728\u200bcmakelists.txt\u200b\u4e2d\u200b\u4fee\u6539\u200b\u4e00\u4e0b\u200bonnxruntime\u200b\u7684\u200b\u8def\u5f84\u200b\u5373\u53ef\u200b\uff0c\u200b\u5177\u4f53\u200b\u53c2\u8003\u200b\u8fd9\u4e2a\u200b\uff1a https://github.com/RapidOCR/RapidOCR/blob/main/.github/workflows/make-linux.yml

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-onnxruntimec","title":"Q: onnxruntime\u200b\u7f16\u8bd1\u200b\u597d\u200b\u7684\u200bC++\u200b\u5e93\u200b\uff0c\u200b\u54ea\u91cc\u200b\u53ef\u4ee5\u200b\u4e0b\u8f7d\u200b\u5230\u200b\uff1f","text":"

A: \u200b\u4ece\u200b\u8fd9\u91cc\u200b\uff1ahttps://github.com/RapidOCR/OnnxruntimeBuilder/releases/tag/1.7.0

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-win10-cygwin-gcc-ccocr","title":"Q: \u200b\u76ee\u524d\u200b\u7b80\u5355\u200b\u6d4b\u8bd5\u73af\u5883\u200b\u662f\u200b Win10 + Cygwin + gcc + \u200b\u7eaf\u200bC\u200b\u7f16\u7a0b\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u5728\u200bC\u200b\u7a0b\u5e8f\u200b\u4e2d\u200b\u76f4\u63a5\u200b\u63a5\u5165\u200b\u7b80\u5355\u200bOCR\u200b\u529f\u80fd\u200b\u5417\u200b\uff1f","text":"

A: \u200b\u76f4\u63a5\u200b\u4f7f\u7528\u200bAPI\u200b\u5c31\u884c\u200b\uff0cAPI\u200b\u5c31\u662f\u200b\u7531\u200bc\u200b\u5bfc\u51fa\u200b\u7684\u200b

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q","title":"Q: \u200b\u6a21\u578b\u200b\u4e0b\u8f7d\u200b\u5730\u5740","text":"

A: \u200b\u767e\u5ea6\u7f51\u200b\u76d8\u200b | Google Drive

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q-onnxruntime-17-onnxruntimesequentialexecutorexecute-non-zero-status-code-returned-while-running-scatternd-node-namescatternd1-status-message-updates","title":"Q: onnxruntime 1.7 \u200b\u4e0b\u200b\u51fa\u9519\u200b\uff1aonnxruntime::SequentialExecutor::Execute] Non-zero status code returned while running ScatterND node. Name:'ScatterND@1' Status Message: updates","text":"

A: \u200b\u7531\u4e8e\u200b\u6a21\u578b\u200b\u53ea\u200b\u652f\u6301\u200bonnxruntime=1.5.0\u200b\u5bfc\u81f4\u200b\uff0c\u200b\u8bf7\u200b\u66f4\u65b0\u200b\u6a21\u578b\u200b,\u200b\u4e0b\u8f7d\u200b\u5730\u5740\u200b\u89c1\u200bQ3

"},{"location":"blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/#q_1","title":"Q: \u200b\u8fb9\u7f18\u200b\u603b\u6709\u200b\u4e00\u884c\u200b\u6587\u5b57\u200b\u65e0\u6cd5\u200b\u8bc6\u522b\u200b\uff0c\u200b\u600e\u4e48\u529e\u200b\uff1f","text":"

A: \u200b\u5728\u200b padding \u200b\u53c2\u6570\u200b\u4e2d\u200b\u6dfb\u52a0\u200b\u4e00\u4e2a\u200b\u503c\u200b \uff0c\u200b\u9ed8\u8ba4\u200b\u662f\u200b0,\u200b\u4f60\u200b\u53ef\u4ee5\u200b\u6dfb\u52a0\u200b5\u200b\u6216\u200b10, \u200b\u751a\u81f3\u200b\u66f4\u5927\u200b\uff0c\u200b\u76f4\u5230\u200b\u80fd\u200b\u8bc6\u522b\u200b\u4e3a\u6b62\u200b\u3002\u200b\u6ce8\u610f\u200b\u4e0d\u8981\u200b\u6dfb\u52a0\u200b\u8fc7\u5927\u200b\uff0c\u200b\u4f1a\u200b\u6d6a\u8d39\u200b\u5185\u5b58\u200b\u3002

"},{"location":"blog/2024/07/13/how-to-use-directml/","title":"\u5982\u4f55\u200b\u4f7f\u7528\u200bDirectML\u200b\u52a0\u901f\u200b\u63a8\u7406\u200bOCR\uff1f","text":"

\u200b\u672c\u7bc7\u200b\u6587\u7ae0\u200b\u4e3b\u8981\u200b\u4ecb\u7ecd\u200b\u4e00\u4e0b\u200bDirectML\uff0c\u200b\u4ee5\u53ca\u200b\u5b83\u200b\u5728\u200bOCR\u200b\u63a8\u7406\u200b\u8fc7\u7a0b\u200b\u4e2d\u662f\u200b\u5982\u4f55\u200b\u4f7f\u7528\u200b\u7684\u200b\u3002

"},{"location":"blog/2024/07/13/how-to-use-directml/#directml","title":"DirectML\u200b\u662f\u200b\u4ec0\u4e48\u200b\uff1f1","text":"

\u200b\u76f4\u63a5\u200b\u673a\u5668\u200b\u5b66\u4e60\u200b (DirectML) \u200b\u662f\u200b\u673a\u5668\u200b\u5b66\u4e60\u200b (ML) \u200b\u7684\u200b\u4f4e\u7ea7\u200b API\u3002 API \u200b\u5177\u6709\u200b\u5e38\u89c1\u200b\u7684\u200b\uff08\u200b\u672c\u200b\u673a\u200b C++\u3001nano-COM\uff09\u200b\u7f16\u7a0b\u200b\u63a5\u53e3\u200b\u548c\u200b DirectX 12 \u200b\u6837\u5f0f\u200b\u7684\u200b\u5de5\u4f5c\u200b\u6d41\u200b\u3002 \u200b\u53ef\u200b\u5c06\u200b\u673a\u5668\u200b\u5b66\u4e60\u200b\u63a8\u65ad\u200b\u5de5\u4f5c\u200b\u8d1f\u8377\u200b\u96c6\u6210\u200b\u5230\u200b\u6e38\u620f\u200b\u3001\u200b\u5f15\u64ce\u200b\u3001\u200b\u4e2d\u95f4\u4ef6\u200b\u3001\u200b\u540e\u7aef\u200b\u6216\u200b\u5176\u4ed6\u200b\u5e94\u7528\u7a0b\u5e8f\u200b\u4e2d\u200b\u3002 \u200b\u6240\u6709\u200b\u4e0e\u200b DirectX 12 \u200b\u517c\u5bb9\u200b\u7684\u200b\u786c\u4ef6\u200b\u90fd\u200b\u652f\u6301\u200b DirectML\u3002

\u200b\u786c\u4ef6\u52a0\u901f\u200b\u7684\u200b\u673a\u5668\u200b\u5b66\u4e60\u200b\u57fa\u5143\u200b\uff08\u200b\u79f0\u4e3a\u200b\u201c\u200b\u8fd0\u7b97\u7b26\u200b\u201d\uff09\u200b\u662f\u200b DirectML \u200b\u7684\u200b\u6784\u5efa\u200b\u57fa\u5757\u200b\u3002 \u200b\u5728\u200b\u8fd9\u4e9b\u200b\u6784\u5efa\u200b\u57fa\u5757\u200b\u4e2d\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u5f00\u53d1\u200b\u7eb5\u5411\u200b\u6269\u5c55\u200b\u3001\u200b\u6297\u952f\u9f7f\u200b\u548c\u200b\u6837\u5f0f\u200b\u8f6c\u79fb\u200b\u7b49\u200b\u673a\u5668\u200b\u5b66\u4e60\u200b\u6280\u672f\u200b\u3002 \u200b\u4f8b\u5982\u200b\uff0c\u200b\u4f7f\u7528\u200b\u566a\u58f0\u200b\u6291\u5236\u200b\u548c\u200b\u8d85\u200b\u89e3\u6790\u5ea6\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u5b9e\u73b0\u200b\u4ee4\u4eba\u200b\u5370\u8c61\u200b\u6df1\u523b\u200b\u7684\u200b\u5149\u7ebf\u200b\u8ddf\u8e2a\u200b\u6548\u679c\u200b\u4e14\u200b\u53ef\u4ee5\u200b\u51cf\u5c11\u200b\u6bcf\u4e2a\u200b\u50cf\u7d20\u200b\u7684\u200b\u5149\u7ebf\u200b\u3002

\u200b\u53ef\u200b\u5c06\u200b\u673a\u5668\u200b\u5b66\u4e60\u200b\u63a8\u65ad\u200b\u5de5\u4f5c\u200b\u8d1f\u8377\u200b\u96c6\u6210\u200b\u5230\u200b\u6e38\u620f\u200b\u3001\u200b\u5f15\u64ce\u200b\u3001\u200b\u4e2d\u95f4\u4ef6\u200b\u3001\u200b\u540e\u7aef\u200b\u6216\u200b\u5176\u4ed6\u200b\u5e94\u7528\u7a0b\u5e8f\u200b\u4e2d\u200b\u3002 DirectML \u200b\u63d0\u4f9b\u200b\u7528\u6237\u200b\u719f\u6089\u200b\u7684\u200b\uff08\u200b\u672c\u200b\u673a\u200bC++\u3001nano-COM\uff09DirectX 12 \u200b\u5f0f\u200b\u7f16\u7a0b\u200b\u63a5\u53e3\u200b\u548c\u200b\u5de5\u4f5c\u200b\u6d41\u200b\uff0c\u200b\u4e14\u200b\u53d7\u200b\u6240\u6709\u200b DirectX 12 \u200b\u517c\u5bb9\u200b\u786c\u4ef6\u200b\u7684\u200b\u652f\u6301\u200b\u3002 \u200b\u6709\u5173\u200b DirectML \u200b\u793a\u4f8b\u200b\u5e94\u7528\u7a0b\u5e8f\u200b\uff08\u200b\u5305\u62ec\u200b\u7cbe\u7b80\u200b DirectML \u200b\u5e94\u7528\u7a0b\u5e8f\u200b\u7684\u200b\u793a\u4f8b\u200b\uff09\uff0c\u200b\u8bf7\u53c2\u9605\u200b DirectML \u200b\u793a\u4f8b\u200b\u5e94\u7528\u7a0b\u5e8f\u200b\u3002

DirectML \u200b\u662f\u200b\u5728\u200b Windows 10 \u200b\u7248\u672c\u200b 1903 \u200b\u548c\u200b Windows SDK \u200b\u7684\u200b\u76f8\u5e94\u200b\u7248\u672c\u200b\u4e2d\u200b\u5f15\u5165\u200b\u7684\u200b\u3002

"},{"location":"blog/2024/07/13/how-to-use-directml/#rapidocrdirectml","title":"RapidOCR\u200b\u4e0b\u200b\u5982\u4f55\u200b\u4f7f\u7528\u200bDirectML\u200b\u52a0\u901f\u200b\u5462\u200b\uff1f","text":"

\u200b\u76ee\u524d\u200b\u5728\u200brapidocr_onnxruntime>=1.3.23\u200b\u4e2d\u200b\uff0c\u200b\u914d\u7f6e\u200b\u4e86\u200b\u4f7f\u7528\u200bDirectML\u200b\u7684\u200b\u5f00\u5173\u200b\u3002\u200b\u5728\u200b\u6ee1\u8db3\u200b\u4e00\u5b9a\u200b\u6761\u4ef6\u200b\u540e\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u6b63\u5e38\u200b\u4f7f\u7528\u200bDirectML\u200b\u52a0\u901f\u200b\u63a8\u7406\u200bOCR\u3002

\u200b\u8981\u200b\u60f3\u200b\u4f7f\u7528\u200bDirectML\u200b\u52a0\u901f\u200b\uff0c\u200b\u9700\u8981\u200b\u6ee1\u8db3\u200b\u4ee5\u4e0b\u200b\u6761\u4ef6\u200b\uff1a

  • \u200b\u8bbe\u5907\u200b\u7cfb\u7edf\u200b\u8981\u200b\u5927\u4e8e\u200b\u7b49\u4e8e\u200bWindows 10 \u200b\u7248\u672c\u200b 1903
  • \u200b\u5b89\u88c5\u200brapidocr_onnxruntime>=1.3.23\u200b\u7248\u672c\u200b
  • \u200b\u5b89\u88c5\u200bonnxruntime-directml\u200b\u5305\u200b
"},{"location":"blog/2024/07/13/how-to-use-directml/#_1","title":"\u5177\u4f53\u200b\u4f7f\u7528\u200b\u6559\u7a0b","text":"

\u200b\u9996\u5148\u200b\u9700\u8981\u200b\u786e\u5b9a\u200b\u81ea\u5df1\u200b\u8bbe\u5907\u200b\u662f\u200bWindows\u200b\u7cfb\u7edf\u200b\uff0c\u200b\u4e14\u200b\u7248\u672c\u200b\u8981\u200b\u5927\u4e8e\u200b\u7b49\u4e8e\u200bWindow 10 1903

"},{"location":"blog/2024/07/13/how-to-use-directml/#rapidocr_onnxruntime1323","title":"\u5b89\u88c5\u200brapidocr_onnxruntime>=1.3.23","text":"
pip install rapidocr_onnxruntime\n
"},{"location":"blog/2024/07/13/how-to-use-directml/#onnxruntime-directml","title":"\u5b89\u88c5\u200bonnxruntime-directml","text":"
# \u200b\u9996\u5148\u200b\u5378\u8f7d\u200b\u4e0a\u200b\u4e00\u6b65\u200b\u9ed8\u8ba4\u200b\u5b89\u88c5\u200b\u7684\u200bonnxruntime\npip uninstall onnxruntime\n\n# \u200b\u5b89\u88c5\u200bonnxruntime-directml\npip install onnxruntime-directml\n
"},{"location":"blog/2024/07/13/how-to-use-directml/#python","title":"Python\u200b\u4f7f\u7528","text":"
from rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\n\nimg_path = 'tests/test_files/ch_en_num.jpg'\n\n# \u200b\u9ed8\u8ba4\u200b\u90fd\u200b\u4e3a\u200bFalse\nresult, elapse = engine(img_path, det_use_dml=True, cls_use_dml=True, rec_use_dml=True)\nprint(result)\nprint(elapse)\n
"},{"location":"blog/2024/07/13/how-to-use-directml/#benchmark","title":"Benchmark","text":"

\u200b\u7531\u4e8e\u200b\u81ea\u5df1\u200b\u624b\u5934\u200b\u6ca1\u6709\u200bWindows\u200b\u673a\u5668\u200b\uff0c\u200b\u6682\u65f6\u200b\u6ca1\u6709\u200b\u76f8\u5173\u200b\u6d4b\u8bc4\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u53c2\u8003\u200b\u4e0b\u9762\u200bDisscussions\u200b\u4e2d\u200b\u8bc4\u6d4b\u200b\u3002

"},{"location":"blog/2024/07/13/how-to-use-directml/#directml_1","title":"\u6709\u5173\u200bDirectML\u200b\u7684\u200b\u8ba8\u8bba","text":"
  • Discussions #175

  1. https://learn.microsoft.com/zh-cn/windows/ai/directml/dml \u21a9

"},{"location":"blog/2022/10/03/optim-tutorial/","title":"\u8c03\u4f18\u200b\u5c1d\u8bd5\u200b\u6559\u7a0b","text":"

Note

\u200b\u4ee5\u4e0b\u200b\u5c1d\u8bd5\u200b\u60c5\u51b5\u200b\uff0c\u200b\u5747\u200b\u5df2\u7ecf\u200b\u5728\u200b\u5728\u7ebf\u200bdemo\u200b\u4e2d\u200b\u5b9e\u73b0\u200b\uff0c\u200b\u770b\u200b\u5b8c\u200b\u4e4b\u540e\u200b\uff0c\u200b\u53ef\u200b\u79fb\u6b65\u200b\u90a3\u91cc\u200b\u53bb\u200b\u5c1d\u8bd5\u200b\u3002

"},{"location":"blog/2022/10/03/optim-tutorial/#_1","title":"\u5f15\u8a00","text":"
  • \u200b\u7531\u4e8e\u200b\u5c0f\u4f19\u4f34\u200b\u4eec\u200b\u4f7f\u7528\u200bOCR\u200b\u7684\u200b\u573a\u666f\u200b\u591a\u79cd\u591a\u6837\u200b\uff0c\u200b\u5355\u4e00\u200b\u7684\u200b\u53c2\u6570\u200b\u914d\u7f6e\u200b\u5f80\u5f80\u200b\u4e0d\u80fd\u200b\u6ee1\u8db3\u8981\u6c42\u200b\uff0c\u200b\u8fd9\u200b\u5c31\u200b\u6d89\u53ca\u200b\u5230\u200b\u57fa\u4e8e\u200b\u73b0\u6709\u200b\u6a21\u578b\u200b\uff0c\u200b\u901a\u8fc7\u200b\u8c03\u8282\u200b\u53c2\u6570\u200b\u6765\u200b\u8fbe\u5230\u200b\u6b63\u786e\u200b\u8bc6\u522b\u200b\u7684\u200b\u76ee\u7684\u200b\u3002
  • \u200b\u57fa\u672c\u200b\u7684\u200b\u539f\u5219\u200b\u662f\u200b\u5c3d\u91cf\u200b\u4e0d\u53bb\u200b\u52a8\u200b\u6a21\u578b\u200b\u5185\u90e8\u200b\uff0c\u200b\u964d\u4f4e\u200b\u4f7f\u7528\u200b\u6210\u672c\u200b\u3002
  • \u200b\u672c\u7bc7\u200b\u6587\u7ae0\u200b\u5c31\u200b\u6765\u8bf4\u200b\u8bf4\u200b\u5728\u200b\u8bc6\u522b\u200b\u6548\u679c\u200b\u4e0d\u597d\u200b\u65f6\u200b\uff0c\u200b\u5982\u4f55\u200b\u53bb\u200b\u8c03\u4f18\u200b\u3002
  • \u200b\u56e0\u6b64\u200b\u535a\u5ba2\u200b\u4e3a\u200b\u4e00\u5bb6\u4e4b\u8a00\u200b\uff0c\u200b\u96be\u514d\u4f1a\u200b\u6302\u4e00\u6f0f\u4e07\u200b\uff0c\u200b\u5e0c\u671b\u200b\u5c0f\u4f19\u4f34\u200b\u591a\u591a\u200b\u6307\u51fa\u200b\uff0c\u200b\u5171\u540c\u200b\u7ef4\u62a4\u200b\u8fd9\u4efd\u200b\u6559\u7a0b\u200b\u3002
"},{"location":"blog/2022/10/03/optim-tutorial/#_2","title":"\u5e38\u89c1\u200b\u9519\u4f8b\u200b\u79cd\u7c7b","text":"

\u200b\u672c\u5730\u200b\u4f7f\u7528\u200b\u8fc7\u7a0b\u200b\u4e2d\u200b\uff0c\u200b\u8bc6\u522b\u200b\u7ed3\u679c\u200b\uff1a

  • \u200b\u4e2a\u522b\u200b\u5b57\u200b\u4e22\u5931\u200b
  • \u200b\u4e2a\u522b\u200b\u5b57\u200b\u8bc6\u522b\u200b\u9519\u8bef\u200b
"},{"location":"blog/2022/10/03/optim-tutorial/#_3","title":"\u4e2a\u522b\u200b\u5b57\u200b\u4e22\u5931\u200b\u8c03\u4f18\u7bc7","text":"

  1. \u200b\u67e5\u770b\u200b\u56fe\u50cf\u200b\u662f\u5426\u200bshape\u200b\u592a\u5c0f\u200b\uff0c\u200b\u5bfc\u81f4\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u4e22\u5931\u200b\u3002

    • \u200b\u5bf9\u4e8e\u200b\u957f\u5ea6\u200b\u8f83\u957f\u200b\uff0c\u200b\u9ad8\u5ea6\u200b\u8f83\u200b\u5c0f\u200b\u7684\u200b\u56fe\u50cf\u200b\uff0c\u200b\u53ef\u200b\u5c1d\u8bd5\u200b\u5bf9\u200b\u8be5\u200b\u56fe\u50cf\u200b\u9ad8\u5ea6\u200b\u505a\u200b\u4e0a\u4e0b\u200b\u8865\u5145\u200b\uff0c\u200b\u6765\u200b\u51cf\u5c0f\u200b\u6587\u5b57\u200b\u5728\u200b\u539f\u59cb\u200b\u56fe\u50cf\u200b\u4e2d\u200b\u6bd4\u4f8b\u200b\uff0c\u200b\u5229\u4e8e\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u3002\u200b\u7c7b\u4f3c\u200b\u4e0b\u56fe\u200b\u8fd9\u79cd\u200b\uff0c\u200b\u5de6\u4fa7\u200b\u4e00\u6761\u200b\u4e3a\u200b\u539f\u59cb\u200b\u56fe\u50cf\u200b\uff0c\u200b\u53f3\u4fa7\u200b\u4e3a\u200b\u4e0a\u4e0b\u200b\u8865\u8fb9\u200b\u7684\u200b\u56fe\u50cf\u200b\u3002
    • padding\u200b\u4ee3\u7801\u200b\u53c2\u8003\u200b\uff1a
    from typing import Tuple\n\nimport cv2\nimport numpy as np\n\n\ndef padding_img(img: np.ndarray,\n                padding_value: Tuple[int, int, int, int],\n                padding_color: Tuple = (0, 0, 0)) -> np.ndarray:\n    padded_img = cv2.copyMakeBorder(img,\n                                    padding_value[0],\n                                    padding_value[1],\n                                    padding_value[2],\n                                    padding_value[3],\n                                    cv2.BORDER_CONSTANT,\n                                    value=padding_color)\n    return padded_img\n\nimg = cv2.imread('xxx.jpg')\n\n# padding_value: (top, bottom, left, right)\n# \u200b\u5bf9\u200b\u8be5\u200b\u56fe\u50cf\u200b\u4e0a\u4e0b\u200b\u5404\u200b\u8865\u5145\u200b10\u200b\u50cf\u7d20\u200b\u7684\u200b\u767d\u8fb9\u200b\npadded_img = padding_img(img, (10, 10, 0, 0), (255, 255, 255))\n

  2. \u200b\u5c06\u200bpadding\u200b\u4e4b\u540e\u200b\u7684\u200b\u56fe\u50cf\u200b\u518d\u6b21\u200b\u9001\u5165\u200bRapidOCR\u200b\u4e2d\u200b\u5c1d\u8bd5\u200b\uff0c\u200b\u67e5\u770b\u200b\u662f\u5426\u200b\u4ecd\u7136\u200b\u51fa\u73b0\u200b\u4e0a\u8ff0\u200b\u95ee\u9898\u200b\u3002

  3. \u200b\u5c06\u200b\u8be5\u200b\u56fe\u50cf\u200b\u4e0a\u200b\u4f20\u5230\u200b\u5728\u7ebf\u200bdemo\u200b\u4e2d\u200b\uff0c\u200b\u67e5\u770b\u200b\u80fd\u5426\u200b\u590d\u73b0\u200b\u95ee\u9898\u200b\uff1f

  4. \u200b\u5982\u200b\u4e0d\u80fd\u200b\u590d\u73b0\u200b\uff0c\u200b\u7740\u91cd\u200b\u6bd4\u200b\u5bf9\u200b\u73af\u5883\u200b\u662f\u5426\u200b\u4e0e\u200b\u5728\u7ebf\u200bdemo\u200b\u4e2d\u200b\u76f8\u5173\u200b\u5305\u200b\u4f7f\u7528\u200b\u7248\u672c\u200b\u4e0d\u200b\u4e00\u81f4\u200b\u60c5\u51b5\u200b\uff1f

  5. \u200b\u5728\u7ebf\u200bdemo\u200b\u6240\u7528\u200b\u7684\u200b\u5404\u4e2a\u200b\u5305\u200b\u7248\u672c\u200b\u60c5\u51b5\u200b\uff1a

    Python: 3.8\nonnxruntime: 1.14.1\nrapidocr_onnxruntime: 1.2.5\n

  6. \u200b\u5982\u80fd\u200b\u590d\u73b0\u200b\uff0c\u200b\u5c1d\u8bd5\u200b\u8c03\u8282\u200b\u5728\u7ebf\u200bdemo\u200b\u4e2d\u200b\u7684\u200b\u4e09\u4e2a\u200b\u53c2\u6570\u200b\uff0c\u200b\u6ce8\u610f\u200b\u63a7\u5236\u53d8\u91cf\u200b\u8c03\u8282\u200b\u53c2\u6570\u200b

  7. \u200b\u9996\u5148\u200b\u8c03\u8282\u200bbox_thresh\u200b\u53c2\u6570\u200b\uff0c\u200b\u8be5\u200b\u53c2\u6570\u200b\u7528\u6765\u200b\u63a7\u5236\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u90e8\u5206\u200b\u68c0\u6d4b\u200b\u6240\u5f97\u200b\u6846\u662f\u200b\u6587\u672c\u200b\u7684\u200b\u6982\u7387\u200b\u3002\u200b\u4e2a\u522b\u200b\u5b57\u200b\u4e22\u5931\u200b\uff0c\u200b\u4e00\u822c\u200b\u662f\u200b\u5355\u72ec\u200b\u7684\u200b\u5b57\u200b\u4e22\u5931\u200b\uff0c\u200b\u5f88\u5927\u200b\u53ef\u80fd\u200b\u662f\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\u6ca1\u6709\u200b\u68c0\u6d4b\u200b\u5230\u200b\u8be5\u200b\u72ec\u7acb\u200b\u7684\u200b\u6587\u5b57\u200b\u3002\u200b\u5c1d\u8bd5\u200b\u8c03\u4f4e\u200bbox_thresh\u200b\u503c\u200b\uff0c\u200b\u67e5\u770b\u200b\u662f\u5426\u200b\u53ef\u4ee5\u200b\u68c0\u51fa\u200b\u4e22\u5931\u200b\u7684\u200b\u6587\u5b57\u200b\u3002\uff08\u200b\u6ca1\u6709\u200b\u627e\u5230\u200b\u5408\u9002\u200b\u7684\u200b\u4f8b\u5b50\u200b\uff09
  8. \u200b\u56fa\u5b9a\u200bbox_thresh\uff0c\u200b\u8c03\u8282\u200btext_score\u200b\u53c2\u6570\u200b\u3002\u200b\u8be5\u200b\u53c2\u6570\u200b\u662f\u200b\u63a7\u5236\u200b\u8bc6\u522b\u200b\u6587\u672c\u200b\u7ed3\u679c\u200b\u6b63\u786e\u200b\u7684\u200b\u6982\u7387\u200b\u3002\u200b\u5c1d\u8bd5\u200b\u8c03\u4f4e\u200btext_score\u200b\u503c\u200b\uff0c\u200b\u67e5\u770b\u200b\u662f\u5426\u200b\u53ef\u4ee5\u200b\u8bc6\u522b\u200b\u51fa\u200b\u4e22\u5931\u200b\u7684\u200b\u6587\u5b57\u200b\u3002
  9. \u200b\u56fa\u5b9a\u200bbox_thresh\u200b\u548c\u200btext_score\u200b\u4e24\u4e2a\u200b\u53c2\u6570\u200b\uff0c\u200b\u8c03\u8282\u200bunclip_ratio\u200b\u53c2\u6570\u200b\u3002\u200b\u8be5\u200b\u53c2\u6570\u200b\u7528\u6765\u200b\u63a7\u5236\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6240\u5f97\u200b\u6587\u672c\u6846\u200b\u7684\u200b\u5927\u5c0f\u200b\u3002\u200b\u5c1d\u8bd5\u200b\u8c03\u5927\u200bunclip_ratio\u200b\u503c\u200b\uff0c\u200b\u67e5\u770b\u200b\u662f\u5426\u200b\u53ef\u4ee5\u200b\u8bc6\u522b\u200b\u51fa\u200b\u4e22\u5931\u200b\u7684\u200b\u6587\u5b57\u200b\u3002
  10. \u200b\u5982\u679c\u200b\u8c03\u8282\u200b\u4e09\u4e2a\u200b\u53c2\u6570\u200b\u4e5f\u200b\u4e0d\u80fd\u200b\u89e3\u51b3\u95ee\u9898\u200b\uff0c\u200b\u53ea\u80fd\u200b\u5c1d\u8bd5\u200bserver\u200b\u7248\u200b\u7684\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u548c\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u4e86\u200b\u3002
  11. \u200b\u9996\u5148\u200b\u66f4\u6362\u200bserver\u200b\u7248\u200b\u7684\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\uff0c\u200b\u67e5\u770b\u200b\u662f\u5426\u200b\u89e3\u51b3\u95ee\u9898\u200b
  12. \u200b\u5728\u200b\u7b2c\u200b1\u200b\u6b65\u200b\u57fa\u7840\u200b\u4e0a\u200b\uff0c\u200b\u66f4\u6362\u200bserver\u200b\u7248\u200b\u7684\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\uff0c\u200b\u67e5\u770b\u200b\u662f\u5426\u200b\u89e3\u51b3\u95ee\u9898\u200b
  13. \u200b\u5c1d\u8bd5\u200b\u66f4\u6362\u200b\u4e0d\u540c\u200b\u7248\u672c\u200b\u6a21\u578b\u200b\uff0c\u200b\u6765\u200b\u67e5\u770b\u200b\u6548\u679c\u200b\u3002\u200b\u5177\u4f53\u200b\u53ef\u200b\u5728\u200b\u5728\u7ebf\u200bdemo\u200b\u4e2d\u200b\u5c1d\u8bd5\u200b
"},{"location":"blog/2022/10/03/optim-tutorial/#_4","title":"\u4e2a\u522b\u200b\u5b57\u200b\u8bc6\u522b\u200b\u9519\u8bef\u200b\u8c03\u4f18\u7bc7","text":"

\u200b\u4e2a\u522b\u200b\u5b57\u200b\u9519\u8bef\u200b\u7684\u200b\u60c5\u51b5\u200b\uff0c\u200b\u4f8b\u5982\u200b\uff1a\u200b\u6210\u200b\u8bc6\u522b\u200b\u4e3a\u200b\u620d\u200b\uff0c\u200b\u8fd9\u79cd\u200b\u4e00\u822c\u200b\u662f\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u7684\u200b\u95ee\u9898\u200b\u3002

"},{"location":"blog/2022/10/03/optim-tutorial/#_5","title":"\u60c5\u51b5\u200b\u4e00\u200b\uff1a\u200b\u8f7b\u91cf\u200b\u4e2d\u82f1\u6587\u200b\u6a21\u578b\u200b\u8bc6\u522b\u200b\u5bf9\u200b\u4e2a\u522b\u200b\u6c49\u5b57\u200b\u8bc6\u522b\u200b\u9519\u8bef","text":"
  1. \u200b\u5c1d\u8bd5\u200bpadding\u200b\u56fe\u50cf\u200b\uff0c\u200b\u518d\u200b\u91cd\u65b0\u200b\u8bc6\u522b\u200b
  2. \u200b\u66f4\u6362\u200b\u4e0d\u540c\u200b\u7248\u672c\u200b\u7684\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\uff0c\u200b\u5305\u62ec\u200bv2\u3001v3\u200b\u548c\u200bserver\u200b\u7248\u200b\u5c1d\u8bd5\u200b
"},{"location":"blog/2022/10/03/optim-tutorial/#_6","title":"\u60c5\u51b5\u200b\u4e8c\u200b\uff1a\u200b\u8f7b\u91cf\u200b\u4e2d\u82f1\u6587\u200b\u6a21\u578b\u200b\u5bf9\u200b\u4e2a\u522b\u200b\u82f1\u6587\u200b\u6216\u200b\u6570\u5b57\u200b\u8bc6\u522b\u200b\u9519\u8bef","text":"
  1. \u200b\u66f4\u6362\u200b\u4e0d\u540c\u200b\u7248\u672c\u200b\u7684\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\uff0c\u200b\u5305\u62ec\u200bv2\u3001v3\u200b\u548c\u200bserver\u200b\u7248\u200b\u5c1d\u8bd5\u200b
  2. \u200b\u5982\u679c\u200b\u662f\u200b\u53ea\u200b\u8bc6\u522b\u200b\u82f1\u6587\u5355\u8bcd\u200b\u548c\u200b\u6570\u5b57\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u66f4\u6362\u200b\u82f1\u6587\u200b\u548c\u200b\u6570\u5b57\u200b\u4e13\u6709\u200b\u6a21\u578b\u200b\uff08en_PP-OCRv3_rec_infer.onnx\u200b\u548c\u200ben_number_mobile_v2.0_rec_infer.onnx\uff09
"},{"location":"blog/2022/08/20/%E5%85%B6%E4%BB%96%E7%BC%96%E7%A8%8B%E8%AF%AD%E8%A8%80%E6%94%AF%E6%8C%81/","title":"\u5176\u4ed6\u200b\u7f16\u7a0b\u8bed\u8a00\u200b\u652f\u6301","text":"

Note

\u200b\u4ee5\u4e0b\u200b\u9879\u76ee\u200b\u4e0d\u200b\u786e\u5b9a\u200b\u662f\u5426\u200b\u652f\u6301\u200b\u6700\u65b0\u200b\u7684\u200b\u63a8\u7406\u200b\u4ee3\u7801\u200b\uff0cPython\u200b\u7248\u4e3a\u200b\u6700\u65b0\u200b\u7684\u200b\u3002

"},{"location":"blog/2022/08/20/%E5%85%B6%E4%BB%96%E7%BC%96%E7%A8%8B%E8%AF%AD%E8%A8%80%E6%94%AF%E6%8C%81/#cwindowslinuxmacos","title":"C++\u200b\u8303\u4f8b\u200b(Windows/Linux/macOS)","text":"
  • RapidOcrOnnx
  • RapidOcrNcnn
"},{"location":"blog/2022/08/20/%E5%85%B6%E4%BB%96%E7%BC%96%E7%A8%8B%E8%AF%AD%E8%A8%80%E6%94%AF%E6%8C%81/#jvmjavakotlin","title":"JVM\u200b\u8303\u4f8b\u200b(Java/Kotlin)","text":"
  • \ud83d\udd25RapidOcr-Java
  • RapidOcrOnnxJvm
  • RapidOcrNcnnJvm
"},{"location":"blog/2022/08/20/%E5%85%B6%E4%BB%96%E7%BC%96%E7%A8%8B%E8%AF%AD%E8%A8%80%E6%94%AF%E6%8C%81/#netc","title":".Net\u200b\u8303\u4f8b\u200b(C#)","text":""},{"location":"blog/2022/08/20/%E5%85%B6%E4%BB%96%E7%BC%96%E7%A8%8B%E8%AF%AD%E8%A8%80%E6%94%AF%E6%8C%81/#android","title":"Android\u200b\u8303\u4f8b","text":""},{"location":"blog/2022/08/20/%E5%85%B6%E4%BB%96%E7%BC%96%E7%A8%8B%E8%AF%AD%E8%A8%80%E6%94%AF%E6%8C%81/#_1","title":"\u6613\u8bed\u8a00","text":""},{"location":"blog/2023/10/08/read-dict-onnx/","title":"\u5173\u4e8e\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u4e2d\u200b\u5b57\u5178\u200b\u7684\u200b\u8bfb\u5199","text":""},{"location":"blog/2023/10/08/read-dict-onnx/#_1","title":"\u5f15\u8a00","text":"

\u200b\u5728\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u65f6\u200b\uff0c\u200b\u8bc6\u522b\u200b\u7684\u200b\u6bcf\u200b\u4e00\u79cd\u200b\u8bed\u8a00\u200b\uff0c\u200b\u90fd\u200b\u6709\u200b\u4e00\u4e2a\u200b\u5bf9\u5e94\u200b\u7684\u200b\u5b57\u5178\u200b\uff0c\u200b\u7528\u6765\u200b\u8fd8\u539f\u200b\u8bc6\u522b\u200b\u7684\u200b\u6587\u672c\u200b\u5185\u5bb9\u200b\u3002\u200b\u4f8b\u5982\u200b\u82f1\u6587\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u7684\u200b\u5b57\u5178\u200b\u5c31\u662f\u200b26\u200b\u4e2a\u200b\u82f1\u6587\u5b57\u6bcd\u200b\u7684\u200b\u5927\u5c0f\u5199\u200b\u4ee5\u53ca\u200b\u5e38\u7528\u200b\u7b26\u53f7\u200b\uff0c\u200b\u4e2d\u6587\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u7684\u200b\u5b57\u5178\u200b\u4e00\u822c\u200b\u5305\u62ec\u200b\u5e38\u7528\u200b\u6c49\u5b57\u200b\u3001\u200b\u5b57\u6bcd\u200b\u548c\u200b\u7b26\u53f7\u200b\u7b49\u200b\u3002

\u200b\u53d7\u200b\u542f\u53d1\u200b\u4e8e\u200bissue #42\uff0c\u200b\u76ee\u524d\u200b\u57fa\u4e8e\u200bONNXRuntime\u200b\u7684\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200brapidocr_onnxruntime\u200b\u5e93\u200b\u5df2\u7ecf\u200b\u5c06\u200b\u5b57\u5178\u200b\u5199\u5165\u200b\u5230\u200bonnx\u200b\u6a21\u578b\u200b\u4e2d\u200b\uff0c\u200b\u65e0\u9700\u200b\u989d\u5916\u200b\u6307\u5b9a\u200b\u5b57\u5178\u200bTXT\u200b\u6587\u4ef6\u200b\u3002

\u200b\u4ee5\u4e0b\u200b\u5c06\u200b\u5bf9\u200b\u8fd9\u200b\u4e00\u90e8\u5206\u200b\u505a\u200b\u8be6\u7ec6\u200b\u8bb2\u89e3\u200b\uff0c\u200b\u611f\u5174\u8da3\u200b\u5c0f\u4f19\u4f34\u200b\uff0c\u200b\u53ef\u200b\u81ea\u884c\u200b\u53d6\u7528\u200b\u3002

"},{"location":"blog/2023/10/08/read-dict-onnx/#onnx","title":"\u5c06\u200b\u5b57\u5178\u200b\u5185\u5bb9\u200b\u5199\u5165\u200b\u5230\u200bONNX\u200b\u4e2d","text":"

Note

\u200b\u5728\u200bPaddleOCRModelConvert\u200b\u5de5\u5177\u200b\u4e2d\u200b\u5df2\u7ecf\u200b\u5c06\u200b\u4e0a\u8ff0\u200b\u64cd\u4f5c\u200b\u5199\u200b\u5230\u200b\u4e86\u200b\u5305\u4e2d\u200b\uff0c\u200b\u4f7f\u7528\u200b\u8be5\u200b\u5de5\u5177\u200b\u53ef\u200b\u81ea\u52a8\u200b\u5c06\u200b\u5b57\u5178\u200b\u5199\u5165\u200b\u5230\u200bONNX\u200b\u4e2d\u200b\u3002\u200b\u6e90\u7801\u200b\u4f4d\u4e8e\u200b\uff1alink

import onnx\n\nmodel = onnx.load_model('/path/to/model.onnx')\n\n# \u200b\u6dfb\u52a0\u200bdictionary\u200b\u5bf9\u5e94\u200b\u7684\u200b\u503c\u200b\nmeta = model.metadata_props.add()\nmeta.key = 'dictionary'\nmeta.value = open('/path/to/ppocr_keys_v1.txt', 'r', -1, 'u8').read()\n\n# \u200b\u6dfb\u52a0\u200bshape\u200b\u5bf9\u5e94\u200b\u7684\u200b\u503c\u200b\nmeta = model.metadata_props.add()\nmeta.key = 'shape'\nmeta.value = '[3,48,320]'\n\nonnx.save_model(model, '/path/to/model.onnx')\n
"},{"location":"blog/2023/10/08/read-dict-onnx/#_2","title":"\u83b7\u53d6\u200b\u5b57\u5178\u200b\u5185\u5bb9","text":"

Note

\u200b\u8be5\u200b\u90e8\u5206\u200b\u5df2\u7ecf\u200b\u5728\u200brapidocr_onnxruntime\u200b\u4e0a\u200b\u5b9e\u73b0\u200b\uff0c\u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b\uff1alink

import json\nimport onnxruntime as ort\n\nsess = ort.InferenceSession('/path/to/model.onnx')\nmetamap = sess.get_modelmeta().custom_metadata_map\n\n# \u200b\u8bfb\u53d6\u200bdictionary\u200b\u952e\u200b\u5bf9\u5e94\u200b\u7684\u200b\u503c\u200b\nchars = metamap['dictionary'].splitlines()\n\n# \u200b\u8bfb\u53d6\u200bshape\u200b\u952e\u200b\u5bf9\u5e94\u200b\u7684\u200b\u503c\u200b\ninput_shape = json.loads(metamap['shape'])\n
"},{"location":"blog/2022/09/27/%E8%BD%AC%E6%8D%A2paddleocr%E6%A8%A1%E5%9E%8B%E4%B8%BAonnx/","title":"\u8f6c\u6362\u200bPaddleOCR\u200b\u6a21\u578b\u200b\u4e3a\u200bONNX","text":"

\u200b\u8be5\u200b\u6587\u7ae0\u200b\u4e3b\u8981\u200b\u7ed9\u51fa\u200b\u4e86\u200b\u51e0\u79cd\u200b\u8f6c\u6362\u200bPaddleOCR\u200b\u6a21\u578b\u200b\u7684\u200b\u65b9\u6848\u200b\uff0c\u200b\u4fbf\u4e8e\u200b\u5927\u5bb6\u200b\u5feb\u901f\u200b\u8f6c\u6362\u200b\u4f7f\u7528\u200b\u3002

Info

\u200b\u4e0d\u200b\u652f\u6301\u200bslim\u200b\u91cf\u5316\u200b\u7248\u200b\u7684\u200b\u6a21\u578b\u200b\u8f6c\u6362\u200b

"},{"location":"blog/2022/09/27/%E8%BD%AC%E6%8D%A2paddleocr%E6%A8%A1%E5%9E%8B%E4%B8%BAonnx/#_1","title":"\u7b80\u4ecb","text":"
  • PaddleOCR\u200b\u9879\u76ee\u200b\u6a21\u578b\u200b\u8f6c\u6362\u200b\uff0c\u200b\u4e3b\u8981\u200b\u501f\u52a9\u200bpaddle2onnx\u200b\u5e93\u200b\u5b9e\u73b0\u200b\u3002\u200b\u9488\u5bf9\u200bPaddleOCR\u200b\u4e2d\u200b\u6d89\u53ca\u200b\u5230\u200b\u7684\u200b\u76f8\u5173\u200b\u6a21\u578b\u200b\uff0c\u200b\u76f4\u63a5\u200b\u8f6c\u6362\u200b\u5e76\u200b\u4e0d\u200b\u592a\u200b\u65b9\u4fbf\u200b\u3002\u200b\u56e0\u6b64\u200b\uff0c\u200b\u63a8\u51fa\u200b\u4e86\u200bPaddleOCRModelConverter\u200b\u8f6c\u6362\u200b\u5de5\u5177\u200b\u3002
"},{"location":"blog/2022/09/27/%E8%BD%AC%E6%8D%A2paddleocr%E6%A8%A1%E5%9E%8B%E4%B8%BAonnx/#_2","title":"\u5728\u7ebf\u200b\u8f6c\u6362","text":"
  • \u200b\u9b54\u200b\u642d\u200b
  • Hugging Face
"},{"location":"blog/2022/09/27/%E8%BD%AC%E6%8D%A2paddleocr%E6%A8%A1%E5%9E%8B%E4%B8%BAonnx/#_3","title":"\u79bb\u7ebf\u200b\u8f6c\u6362","text":""},{"location":"blog/2023/10/17/%E5%A6%82%E4%BD%95%E6%9B%B4%E6%8D%A2%E5%85%B6%E4%BB%96%E6%A3%80%E6%B5%8B%E5%92%8C%E8%AF%86%E5%88%AB%E6%A8%A1%E5%9E%8B/","title":"\u5982\u4f55\u200b\u66f4\u6362\u200b\u5176\u4ed6\u200b\u68c0\u6d4b\u200b\u548c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\uff1f","text":"

\u200b\u672c\u6587\u200b\u8be6\u5c3d\u200b\u5730\u200b\u7ed9\u51fa\u200b\u4e86\u200b\u5982\u4f55\u200b\u66f4\u6362\u200b\u5176\u4ed6\u200b\u68c0\u6d4b\u200b\u548c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u7684\u200b\u4fdd\u59c6\u200b\u7ea7\u200b\u6559\u7a0b\u200b\u3002

Note

\u200b\u5efa\u8bae\u200b\u7528\u200brapidocr_onnxruntime>=1.3.x\u200b\u7248\u672c\u200b\u6765\u200b\u52a0\u8f7d\u200bPaddleOCR v3/v4\u200b\u7248\u672c\u200b\u8bad\u7ec3\u200b\u6240\u5f97\u200b\u6a21\u578b\u200b\u3002

"},{"location":"blog/2023/10/17/%E5%A6%82%E4%BD%95%E6%9B%B4%E6%8D%A2%E5%85%B6%E4%BB%96%E6%A3%80%E6%B5%8B%E5%92%8C%E8%AF%86%E5%88%AB%E6%A8%A1%E5%9E%8B/#_1","title":"\u5f15\u8a00","text":"

rapidocr\u200b\u7cfb\u5217\u200b\u5e93\u4e2d\u200b\u9ed8\u8ba4\u200b\u6253\u5305\u200b\u4e86\u200b\u8f7b\u91cf\u200b\u7248\u200b\u7684\u200b\u4e2d\u82f1\u6587\u200b\u68c0\u6d4b\u200b\u548c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\uff0c\u200b\u8fd9\u79cd\u200b\u914d\u7f6e\u200b\u53ef\u4ee5\u200b\u8986\u76d6\u200b\u5230\u200b\u5927\u90e8\u5206\u200b\u573a\u666f\u200b\u3002\u200b\u4f46\u662f\u200b\u4e5f\u200b\u603b\u4f1a\u200b\u6709\u200b\u4e00\u4e9b\u200b\u5176\u4ed6\u200b\u573a\u666f\u200b\uff0c\u200b\u8981\u200b\u7528\u5230\u200b\u5176\u4ed6\u200b\u68c0\u6d4b\u200b\u548c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u3002

\u200b\u8fd9\u200b\u4e00\u70b9\u200b\u5728\u200b\u8bbe\u8ba1\u200b\u65f6\u200b\u5df2\u7ecf\u200b\u505a\u200b\u4e86\u200b\u8003\u8651\u200b\uff0c\u200b\u7559\u51fa\u200b\u4e86\u200b\u63a5\u53e3\u200b\uff0c\u200b\u8fd9\u4e2a\u200b\u535a\u5ba2\u200b\u5c31\u662f\u200b\u4ee5\u200b\u5982\u4f55\u200b\u66f4\u6362\u200brapidocr_onnxruntime\u200b\u7684\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u4e3a\u200b\u82f1\u6587\u200b\u548c\u200b\u6570\u5b57\u200b\u7684\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u4e3a\u4f8b\u200b\u505a\u200b\u8bb2\u89e3\u200b\uff0c\u200b\u5176\u4ed6\u200b\u6a21\u578b\u200b\u540c\u7406\u200b\u3002

Note

\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\uff0c\u200b\u5bf9\u5e94\u200b\u6a21\u578b\u200b\u8def\u5f84\u200b\u53c2\u6570\u200b\u4e3a\u200bdet_model_path\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\uff0c\u200b\u5bf9\u5e94\u200b\u6a21\u578b\u200b\u8def\u5f84\u200b\u53c2\u6570\u200b\u4e3a\u200brec_model_path \u200b\u8be6\u7ec6\u200b\u8bf4\u660e\u200b\u53c2\u89c1\u200b\uff1alink

"},{"location":"blog/2023/10/17/%E5%A6%82%E4%BD%95%E6%9B%B4%E6%8D%A2%E5%85%B6%E4%BB%96%E6%A3%80%E6%B5%8B%E5%92%8C%E8%AF%86%E5%88%AB%E6%A8%A1%E5%9E%8B/#1-rapidocr_onnxruntime","title":"1. \u200b\u5b89\u88c5\u200brapidocr_onnxruntime","text":"

\u200b\u8bf7\u200b\u5148\u200b\u6839\u636e\u200b\u6559\u7a0b\u200b\uff0c\u200b\u88c5\u200b\u597d\u200brapidocr_onnxruntime\u200b\u5e93\u200b\uff0c\u200b\u5177\u4f53\u200b\u53ef\u200b\u53c2\u8003\u200b\uff1alink

"},{"location":"blog/2023/10/17/%E5%A6%82%E4%BD%95%E6%9B%B4%E6%8D%A2%E5%85%B6%E4%BB%96%E6%A3%80%E6%B5%8B%E5%92%8C%E8%AF%86%E5%88%AB%E6%A8%A1%E5%9E%8B/#2-onnx","title":"2. \u200b\u83b7\u5f97\u200b\u82f1\u6587\u200b\u548c\u200b\u6570\u5b57\u200b\u7684\u200bONNX\u200b\u8bc6\u522b\u200b\u6a21\u578b","text":"

Note

\u200b\u5982\u679c\u200b\u60f3\u200b\u7528\u200bRapidOCR\u200b\u4ed3\u5e93\u200b\u63a8\u7406\u200b\u5176\u4ed6\u200b\u6a21\u578b\u200b\uff0c\u200b\u5fc5\u987b\u200b\u8981\u200b\u7528\u200bPaddleOCRModelConvert\u200b\u5de5\u5177\u200b\u8f6c\u6362\u200b\u6a21\u578b\u200b \u200b\u5728\u200b\u7528\u200bPaddleOCRModelConvert\u200b\u5de5\u5177\u200b\u8f6c\u6362\u200b\u6a21\u578b\u200b\u65f6\u200b\uff0c\u200b\u5b57\u5178\u200b\u4f1a\u200b\u81ea\u52a8\u200b\u5199\u5165\u200b\u5230\u200bonnx\u200b\u6a21\u578b\u200b\u91cc\u200b\u3002

\u200b\u6a21\u578b\u200b\u5730\u5740\u200b\uff1a 

https://paddleocr.bj.bcebos.com/PP-OCRv4/english/en_PP-OCRv4_rec_infer.tar\n

\u200b\u5b57\u5178\u200b\u5730\u5740\u200b: 

https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.7/ppocr/utils/en_dict.txt\n

\u200b\u5728\u7ebf\u200b\u8f6c\u6362\u200b: \u200b\u57fa\u4e8e\u200bPaddleOCRModelConvert\u200b\u5de5\u5177\u200b\u5f97\u5230\u200ben_PP-OCRv4_rec_infer.onnx\u200b\u6a21\u578b\u200b

"},{"location":"blog/2023/10/17/%E5%A6%82%E4%BD%95%E6%9B%B4%E6%8D%A2%E5%85%B6%E4%BB%96%E6%A3%80%E6%B5%8B%E5%92%8C%E8%AF%86%E5%88%AB%E6%A8%A1%E5%9E%8B/#3","title":"3. \u200b\u4f7f\u7528\u200b\u8be5\u200b\u6a21\u578b","text":"
from rapidocr_onnxruntime import RapidOCR\n\nmodel = RapidOCR(rec_model_path=\"en_PP-OCRv4_rec_infer.onnx\")\n\nimg_path = \"1.png\"\nresult, elapse = model(img_path)\nprint(result)\nprint(elapse)\n
"},{"location":"blog/2024/04/12/%E5%B7%B2%E6%9C%89onnx%E6%A8%A1%E5%9E%8B%E4%B8%8B%E8%BD%BD/","title":"\u5df2\u6709\u200bONNX\u200b\u6a21\u578b\u200b\u4e0b\u8f7d","text":""},{"location":"blog/2024/04/12/%E5%B7%B2%E6%9C%89onnx%E6%A8%A1%E5%9E%8B%E4%B8%8B%E8%BD%BD/#_1","title":"\u7b80\u4ecb","text":"

\u200b\u8be5\u200b\u90e8\u5206\u200b\u5c06\u200b\u5df2\u7ecf\u200b\u8f6c\u6362\u200b\u597d\u200b\u7684\u200bONNX\u200b\u6a21\u578b\u200b\u505a\u200b\u4e86\u200b\u6574\u7406\u200b\uff0c\u200b\u63d0\u4f9b\u200b\u4e86\u200bHugging Face\u3001Google\u200b\u7f51\u76d8\u200b\u548c\u200b\u767e\u5ea6\u7f51\u200b\u76d8\u200b\u4e24\u4e2a\u200b\u4e0b\u8f7d\u200b\u9014\u5f84\u200b\u3002

"},{"location":"blog/2024/04/12/%E5%B7%B2%E6%9C%89onnx%E6%A8%A1%E5%9E%8B%E4%B8%8B%E8%BD%BD/#hugging-face-models","title":"Hugging Face Models","text":""},{"location":"blog/2024/04/12/%E5%B7%B2%E6%9C%89onnx%E6%A8%A1%E5%9E%8B%E4%B8%8B%E8%BD%BD/#google","title":"Google\u200b\u7f51\u76d8","text":""},{"location":"blog/2024/04/12/%E5%B7%B2%E6%9C%89onnx%E6%A8%A1%E5%9E%8B%E4%B8%8B%E8%BD%BD/#_2","title":"\u767e\u5ea6\u7f51\u200b\u76d8","text":""},{"location":"blog/2022/04/16/%E5%BC%80%E6%BA%90ocr%E6%A8%A1%E5%9E%8B%E5%AF%B9%E6%AF%94/","title":"\u5f00\u6e90\u200bOCR\u200b\u6a21\u578b\u200b\u5bf9\u6bd4","text":"

\u200b\u672c\u6587\u200b\u4e3b\u8981\u200b\u7ed9\u51fa\u200b\u4e86\u200b\u5e38\u89c1\u200b\u5f00\u6e90\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u548c\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u7684\u200b\u5bf9\u6bd4\u200b\u548c\u200b\u8bc4\u6d4b\u200b\uff0c\u200b\u7ed9\u200b\u5927\u5bb6\u200b\u4e00\u4e2a\u200b\u4f7f\u7528\u200b\u53c2\u8003\u200b\u3002

"},{"location":"blog/2022/04/16/%E5%BC%80%E6%BA%90ocr%E6%A8%A1%E5%9E%8B%E5%AF%B9%E6%AF%94/#_1","title":"\u5f15\u8a00","text":"

\u200b\u76ee\u524d\u200b\uff0c\u200b\u5f00\u6e90\u200b\u7684\u200b\u9879\u76ee\u200b\u4e2d\u6709\u200b\u5f88\u591a\u200bOCR\u200b\u6a21\u578b\u200b\uff0c\u200b\u4f46\u662f\u200b\u6ca1\u6709\u200b\u4e00\u4e2a\u200b\u7edf\u4e00\u200b\u7684\u200b\u57fa\u51c6\u200b\u6765\u200b\u8861\u91cf\u200b\u54ea\u4e2a\u200b\u662f\u200b\u66f4\u597d\u200b\u4e00\u4e9b\u200b\u7684\u200b\u3002

\u200b\u9762\u5bf9\u200b\u8fd9\u4e48\u200b\u591a\u200b\u7684\u200b\u6a21\u578b\u200b\uff0c\u200b\u8ba9\u200b\u6211\u4eec\u200b\u6709\u4e9b\u200b\u4e0d\u77e5\u6240\u63aa\u200b\u3002\u200b\u4e3a\u6b64\u200b\uff0c\u200b\u6700\u8fd1\u200b\u4e00\u6bb5\u65f6\u95f4\u200b\u4ee5\u6765\u200b\uff0c\u200b\u6211\u200b\u4e00\u76f4\u200b\u60f3\u8981\u200b\u6784\u5efa\u200b\u8fd9\u6837\u200b\u4e00\u4e2a\u200b\u57fa\u51c6\u200b\u3002\u200b\u73b0\u5728\u200b\u6765\u770b\u200b\uff0c\u200b\u5df2\u7ecf\u200b\u521d\u6b65\u200b\u5177\u6709\u200b\u96cf\u5f62\u200b\u3002

\u200b\u4e3a\u4e86\u200b\u80fd\u200b\u66f4\u597d\u200b\u5730\u200b\u8bc4\u6d4b\u200b\u5404\u4e2a\u200b\u6a21\u578b\u200b\u6548\u679c\u200b\uff0c\u200b\u6536\u96c6\u200b\u6807\u6ce8\u200b\u4e86\u200b\u4e24\u4e2a\u200b\u5f00\u6e90\u200b\u8bc4\u6d4b\u200b\u96c6\u200b\uff1a

  • text_det_test_dataset
  • text_rec_test_dataset

\u200b\u4e3a\u4e86\u200b\u80fd\u591f\u200b\u65b9\u4fbf\u200b\u8ba1\u7b97\u200b\u5404\u4e2a\u200b\u6a21\u578b\u200b\u6307\u6807\u200b\uff0c\u200b\u6574\u7406\u200b\u5f00\u6e90\u200b\u4e86\u200b\u4e24\u4e2a\u200b\u8ba1\u7b97\u200b\u5e38\u7528\u200b\u6307\u6807\u200b\u7684\u200b\u5e93\u200b\uff1a

  • TextDetMetric
  • TextRecMetric

\u200b\u4ee5\u4e0b\u200b\u7ed3\u679c\u200b\u5747\u200b\u662f\u200b\u57fa\u4e8e\u200b\u4ee5\u4e0a\u200b4\u200b\u4e2a\u5e93\u200b\u6765\u200b\u7684\u200b\uff0c\u200b\u5176\u200b\u6307\u6807\u200b\u7ed3\u679c\u200b\u4ec5\u4ec5\u200b\u4ee3\u8868\u200b\u5728\u200b\u6307\u5b9a\u200b\u8bc4\u6d4b\u200b\u96c6\u4e0a\u200b\u6548\u679c\u200b\uff0c\u200b\u4e0d\u200b\u4ee3\u8868\u200b\u5728\u200b\u5176\u4ed6\u200b\u6d4b\u8bd5\u200b\u96c6\u4e0a\u200b\u7ed3\u679c\u200b\u4e5f\u200b\u662f\u200b\u5982\u6b64\u200b\uff0c\u200b\u4ec5\u4f9b\u53c2\u8003\u200b\u3002

\u200b\u4ee5\u4e0b\u200b\u8868\u683c\u200b\u4e2d\u200b\u63a8\u7406\u200b\u65f6\u95f4\u200b\u662f\u200b\u57fa\u4e8e\u200bMacBook Pro M2\u200b\u8fd0\u884c\u200b\u6240\u5f97\u200b\uff0c\u200b\u4e0d\u540c\u200b\u673a\u5668\u200b\u4f1a\u200b\u6709\u200b\u5dee\u522b\u200b\uff0c\u200b\u8bf7\u200b\u4fa7\u91cd\u200b\u67e5\u770b\u200b\u5f7c\u6b64\u4e4b\u95f4\u200b\u7684\u200b\u6bd4\u8f83\u200b\u3002

\u200b\u6307\u6807\u200b\u8ba1\u7b97\u200b\u90fd\u200b\u662f\u200b\u5728\u200b\u76f8\u540c\u200b\u53c2\u6570\u200b\u4e0b\u200b\u8ba1\u7b97\u200b\u5f97\u6765\u200b\uff0c\u200b\u5dee\u522b\u200b\u4ec5\u200b\u5728\u4e8e\u200b\u6a21\u578b\u200b\u6587\u4ef6\u200b\u4e0d\u540c\u200b\u3002

\u200b\u5bf9\u5e94\u200b\u6a21\u578b\u200b\u4e0b\u8f7d\u200b\u5730\u5740\u200b\uff0c\u200b\u53c2\u89c1\u200b\uff1alink\u3002

"},{"location":"blog/2022/04/16/%E5%BC%80%E6%BA%90ocr%E6%A8%A1%E5%9E%8B%E5%AF%B9%E6%AF%94/#ocr","title":"\u5df2\u77e5\u200b\u5f00\u6e90\u200bOCR\u200b\u9879\u76ee","text":"
  • PaddleOCR
  • EasyOCR
  • MMOCR
  • CnOCR
  • DAVAR-Lab-OCR
  • mindocr
  • surya
"},{"location":"blog/2022/04/16/%E5%BC%80%E6%BA%90ocr%E6%A8%A1%E5%9E%8B%E5%AF%B9%E6%AF%94/#_2","title":"\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u578b","text":"

\u200b\u8bc4\u6d4b\u200b\u4f9d\u8d56\u200b\u4ed3\u5e93\u200b\uff1a

  • rapidocr_onnxruntime==1.3.16: link
  • \u200b\u8ba1\u7b97\u200b\u6307\u6807\u200b\u5e93\u200b TextDetMetric: link
  • \u200b\u6d4b\u8bd5\u200b\u96c6\u200b text_det_test_dataset: link

\u200b\u8be6\u60c5\u200b\u53ef\u4ee5\u200b\u79fb\u6b65\u200bAI Studio\u200b\u8fd0\u884c\u200b\u67e5\u770b\u200b\u3002

\u200b\u6a21\u578b\u200b \u200b\u6a21\u578b\u200b\u5927\u5c0f\u200b Precision Recall H-mean Speed(s/img) ch_PP-OCRv4_det_infer.onnx 4.5M 0.8301 0.8659 0.8476 0.2256 ch_PP-OCRv3_det_infer.onnx 2.3M 0.8021 0.8457 0.8234 0.1660 ch_PP-OCRv2_det_infer.onnx 2.2M 0.7579 0.8010 0.7788 0.1570 ch_PP-OCRv4_det_server_infer.onnx 108M 0.7922 0.8533 0.8216 3.9093 ch_ppocr_server_v2.0_det_infer.onnx 47M 0.7298 0.8128 0.7691 0.7419 \u200b\u8bfb\u5149\u200b-\u200b\u6587\u5b57\u200b\u68c0\u6d4b\u200b-\u200b\u8f7b\u91cf\u5316\u200b\u7aef\u4fa7\u200bDBNet\u200b\u884c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b-\u200b\u4e2d\u200b\u82f1\u200b-\u200b\u901a\u7528\u200b\u9886\u57df\u200b 5.8M 0.7666 0.8128 0.7890 0.6636 \u200b\u8bfb\u5149\u200b-\u200b\u6587\u5b57\u200b\u68c0\u6d4b\u200b-DBNet\u200b\u884c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b-\u200b\u4e2d\u200b\u82f1\u200b-\u200b\u901a\u7528\u200b\u9886\u57df\u200b 47.2M 0.7749 0.8167 0.7952 0.4121 \u200b\u8bfb\u5149\u200b-\u200b\u6587\u5b57\u200b\u68c0\u6d4b\u200b-\u200b\u884c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b-\u200b\u4e2d\u200b\u82f1\u200b-\u200b\u901a\u7528\u200b\u9886\u57df\u200b \u200b\u672a\u200b\u8dd1\u200b\u901a\u200b 312M - - - -

\u200b\u4e0d\u540c\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u4e0b\u200b\uff0c\u200b\u6548\u679c\u200b\u6bd4\u8f83\u200b\uff1a

\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b \u200b\u6a21\u578b\u200b \u200b\u6a21\u578b\u200b\u5927\u5c0f\u200b Precision Recall H-mean Speed(s/img) rapidocr_onnxruntime==1.3.16 ch_PP-OCRv4_det_infer.onnx 4.5M 0.8301 0.8659 0.8476 0.2256 rapidocr_openvino==1.3.16 ch_PP-OCRv4_det_infer.onnx 4.5M 0.8339 0.8629 0.8481 0.6447 rapidocr_paddle==1.3.18 ch_PP-OCRv4_det_infer.onnx 4.5M 0.8301 0.8659 0.8476 0.9924"},{"location":"blog/2022/04/16/%E5%BC%80%E6%BA%90ocr%E6%A8%A1%E5%9E%8B%E5%AF%B9%E6%AF%94/#_3","title":"\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b","text":"

\u200b\u8bc4\u6d4b\u200b\u4f9d\u8d56\u200b\u4ed3\u5e93\u200b\uff1a

  • rapidocr_onnxruntime==1.3.16: link
  • \u200b\u8ba1\u7b97\u200b\u6307\u6807\u200b\u5e93\u200b TextRecMetric: link
  • \u200b\u6d4b\u8bd5\u200b\u96c6\u200b text_rec_test_dataset: link
\u200b\u6a21\u578b\u200b \u200b\u5bf9\u5e94\u200bPaddleOCR\u200b\u5206\u652f\u200b \u200b\u6a21\u578b\u200b\u5927\u5c0f\u200b Exact Match Char Match Speed(s/img) ch_PP-OCRv4_rec_infer.onnx release/v2.7 10M 0.8323 0.9355 0.6836 ch_PP-OCRv3_rec_infer.onnx release/v2.6 11M 0.7097 0.8919 0.6362 ch_PP-OCRv4_rec_server_infer.onnx release/v2.7 86M 0.7968 0.9381 0.6967 ch_PP-OCRv2_rec_infer.onnx release/v2.3 8.0M 0.6387 0.8398 0.6138 ch_ppocr_mobile_v2.0_rec_infer.onnx release/v2.0 4.3M 0.5323 0.7823 0.5575 \u200b\u8bfb\u5149\u200b-\u200b\u6587\u5b57\u200b\u8bc6\u522b\u200b-\u200b\u884c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b-\u200b\u4e2d\u200b\u82f1\u200b-\u200b\u6587\u6863\u200b\u5370\u5237\u4f53\u200b\u6587\u672c\u200b\u9886\u57df\u200b - 73M 0.5968 0.7705 - \u200b\u8bfb\u5149\u200b-\u200b\u6587\u5b57\u200b\u8bc6\u522b\u200b-\u200b\u884c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b-\u200b\u4e2d\u200b\u82f1\u200b-\u200b\u901a\u7528\u200b\u9886\u57df\u200b - 73M 0.5839 0.7615 - \u200b\u8bfb\u5149\u200b-\u200b\u6587\u5b57\u200b\u8bc6\u522b\u200b-\u200b\u884c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b-\u200b\u4e2d\u200b\u82f1\u200b-\u200b\u81ea\u7136\u200b\u573a\u666f\u200b\u6587\u672c\u200b\u9886\u57df\u200b - 73M 0.5903 0.7779 - \u200b\u8bfb\u5149\u200b-\u200b\u6587\u5b57\u200b\u8bc6\u522b\u200b-\u200b\u8f7b\u91cf\u5316\u200b\u7aef\u4fa7\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b-\u200b\u4e2d\u200b\u82f1\u200b-\u200b\u901a\u7528\u200b\u9886\u57df\u200b - 7.4M 0.5484 0.7515 - \u200b\u8bfb\u5149\u200b-\u200b\u6587\u5b57\u200b\u8bc6\u522b\u200b-CRNN\u200b\u6a21\u578b\u200b-\u200b\u4e2d\u200b\u82f1\u200b-\u200b\u901a\u7528\u200b\u9886\u57df\u200b - 46M 0.5935 0.7671 - OFA\u200b\u6587\u5b57\u200b\u8bc6\u522b\u200b-\u200b\u4e2d\u6587\u200b-\u200b\u901a\u7528\u200b\u573a\u666f\u200b-base \u200b\u672a\u200b\u8dd1\u200b\u901a\u200b - - - - -

\u200b\u4e0d\u540c\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u4e0b\u200b\uff0c\u200b\u6548\u679c\u200b\u6bd4\u8f83\u200b\uff1a

\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b \u200b\u6a21\u578b\u200b \u200b\u6a21\u578b\u200b\u5927\u5c0f\u200b Exact Match Char Match Speed(s/img) rapidocr_onnxruntime==1.3.16 ch_PP-OCRv4_rec_infer.onnx 10M 0.8323 0.9355 0.6836 rapidocr_openvino==1.3.16 ch_PP-OCRv4_rec_infer.onnx 10M 0.8323 0.9355 0.6836 rapidocr_paddle==1.3.18 ch_PP-OCRv4_rec_infer.onnx 10M 0.8323 0.9355 0.6836

  • \u200b\u8f93\u5165\u200bShape:

    • v2: [3, 32, 320]
    • v3~v4: [3, 48, 320]

  • \u200b\u4e0d\u540c\u200b\u6a21\u578b\u200b\uff0c\u200b\u5b9e\u4f8b\u200b\u5316\u200b\u793a\u4f8b\u200b\u5982\u4e0b\u200b\uff1a

from rapidocr_onnxruntime import RapidOCR\n\n# v3 or v4\nengine = RapidOCR(\n  rec_model_path=\"models/ch_PP-OCRv3_rec_infer.onnx\",\n)\n\n# v2\nengine = RapidOCR(\n  rec_model_path=\"models/ch_ppocr_mobile_v2.0_rec_infer.onnx\",\n  rec_img_shape=[3, 32, 320],\n)\n
"},{"location":"blog/2022/09/28/%E6%94%AF%E6%8C%81%E8%AF%86%E5%88%AB%E8%AF%AD%E8%A8%80/","title":"\u652f\u6301\u200b\u8bc6\u522b\u200b\u8bed\u8a00","text":""},{"location":"blog/2022/09/28/%E6%94%AF%E6%8C%81%E8%AF%86%E5%88%AB%E8%AF%AD%E8%A8%80/#_1","title":"\u7b80\u4ecb","text":"
  • \u200b\u56e0\u4e3a\u200b\u672c\u200b\u9879\u76ee\u200b\u4f9d\u6258\u200b\u4e8e\u200bPaddleOCR\uff0c\u200b\u6240\u4ee5\u200b\u7406\u8bba\u200b\u4e0a\u200bPaddleOCR\u200b\u652f\u6301\u200b\u8bc6\u522b\u200b\u7684\u200b\u6a21\u578b\u200b\uff0cRapidOCR\u200b\u90fd\u200b\u662f\u200b\u652f\u6301\u200b\u7684\u200b\u3002
"},{"location":"blog/2022/09/28/%E6%94%AF%E6%8C%81%E8%AF%86%E5%88%AB%E8%AF%AD%E8%A8%80/#_2","title":"\u4e2d\u82f1\u6587\u200b\u68c0\u6d4b\u200b\u548c\u200b\u8bc6\u522b\u200b\uff08\u200b\u53ef\u4ee5\u200b\u76f4\u63a5\u200b\u4f7f\u7528\u200b\uff09","text":"
  • \u200b\u56e0\u4e3a\u200b\u4e2d\u82f1\u6587\u200b\u662f\u200b\u6700\u4e3a\u200b\u5e38\u7528\u200b\u7684\u200b\u6a21\u578b\u200b\uff0c\u200b\u6240\u4ee5\u200b\u5728\u200b\u6253\u5305\u200b\u65f6\u200b\uff0c\u200b\u5c31\u200b\u9ed8\u8ba4\u200b\u5c06\u200b\u4e2d\u82f1\u6587\u200b\u8bc6\u522b\u200b\u7684\u200b\u6a21\u578b\u200b\u653e\u5230\u200b\u4e86\u200brapidocr_onnxruntime\u200b\u548c\u200brapidocr_openvino\u200b\u4e2d\u200b\uff0c\u200b\u76f4\u63a5\u200bpip\u200b\u5b89\u88c5\u200b\u5373\u53ef\u200b\u4f7f\u7528\u200b\u3002
"},{"location":"blog/2022/09/28/%E6%94%AF%E6%8C%81%E8%AF%86%E5%88%AB%E8%AF%AD%E8%A8%80/#_3","title":"\u5176\u4ed6\u200b\u8bed\u79cd\u200b\u68c0\u6d4b\u200b\u548c\u200b\u8bc6\u522b\u200b\uff08\u200b\u9700\u8981\u200b\u8f6c\u6362\u200b\uff09","text":"
  • PaddleOCR\u200b\u4e2d\u200b\u5df2\u6709\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\u5217\u8868\u200b\uff1alink
  • PaddleOCR\u200b\u5df2\u6709\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u5217\u8868\u200b\uff1a link
  • \u200b\u9664\u4e86\u200bslim\u200b\u91cf\u5316\u200b\u7248\u200b\u7684\u200b\u6a21\u578b\u200b\uff0c\u200b\u4e0a\u9762\u200b\u94fe\u63a5\u200b\u4e2d\u200b\u7684\u200b\u5176\u4ed6\u200b\u6a21\u578b\u200b\u90fd\u200b\u53ef\u4ee5\u200b\u8f6c\u6362\u200b\u4e3a\u200bONNX\u200b\u683c\u5f0f\u200b\uff0c\u200b\u901a\u8fc7\u200bRapidOCR\u200b\u5feb\u901f\u200b\u90e8\u7f72\u200b\u3002
"},{"location":"blog/2022/09/28/%E6%94%AF%E6%8C%81%E8%AF%86%E5%88%AB%E8%AF%AD%E8%A8%80/#_4","title":"\u8f6c\u6362\u200b\u6559\u7a0b","text":""},{"location":"blog/2022/09/22/inference-summary/","title":"\u63a8\u7406\u200b\u5f15\u64ce\u200b\u6c47\u603b","text":"

Warning

This documentation is in progress

"},{"location":"blog/2022/09/22/inference-summary/#_1","title":"\u5f15\u8a00","text":"
  • \u200b\u5173\u4e8e\u200b\u6a21\u578b\u200b\u7684\u200b\u63a8\u7406\u200b\u6846\u67b6\u200b\u6709\u200b\u5f88\u591a\u200b\uff0c\u200b\u5305\u62ec\u200bPC/\u200b\u79fb\u52a8\u200b\u7aef\u200b\u7b49\u7b49\u200b\u3002\u200b\u4e4b\u524d\u200b\u5728\u200b\u8001\u200b\u6f58\u200b\u7684\u200b\u4e2a\u4eba\u200b\u535a\u5ba2\u200b\u91cc\u200b\u770b\u5230\u200b\u8fc7\u200b\u76f8\u5173\u200b\u4ecb\u7ecd\u200b
  • \u200b\u6211\u200b\u5728\u200b\u8fd9\u91cc\u200b\u505a\u200b\u4e00\u4e2a\u200b\u7b80\u5355\u200b\u6c47\u603b\u200b\u3002\u200b\u4f46\u200b\u66f4\u200b\u4fa7\u91cd\u4e8e\u200b\u5bfb\u627e\u200b\u4e00\u4e2a\u200b\u5728\u200bGPU\u200b\u4e0a\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u652f\u6301\u200b\u52a8\u6001\u200b\u8f93\u5165\u200b\u4e14\u200b\u5728\u200bGPU\u200b\u4e0a\u200b\u66f4\u200b\u5feb\u200b\uff0c\u200b\u8f7b\u91cf\u200b\u7684\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u3002
"},{"location":"blog/2022/09/22/inference-summary/#_2","title":"\u76ee\u524d\u200b\u5df2\u77e5\u200b\u63a8\u7406\u200b\u5f15\u64ce","text":"
  • CPU\u200b\u7aef\u200b\uff1aONNXruntime\u3001OpenVINO\u3001libtorch\u3001Caffe\u3001PaddleInference
  • GPU\u200b\u7aef\u200b\uff1aTensorRT\u3001OpenPPL\u3001AITemplate
  • \u200b\u79fb\u52a8\u200b\u7aef\u200b\uff1aNCNN\uff0cMNN, Paddle-Lite
  • \u200b\u901a\u5403\u200b\uff1aTVM\u3001OpenPPL
"},{"location":"blog/2022/09/22/inference-summary/#onnxruntime","title":"ONNXRuntime\uff08\u200b\u5fae\u8f6f\u200b\uff09","text":"
  • \u200b\u76ee\u524d\u200b\u4ed3\u5e93\u200b\u4e2d\u200b\u5df2\u7ecf\u200b\u5728\u200b\u4f7f\u7528\u200b\u7684\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\uff0cCPU\u200b\u7aef\u200b\u6700\u597d\u200b\u7528\u200b\u7684\u200b\u8f7b\u91cf\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u3002\u200b\u652f\u6301\u200b\u52a8\u6001\u200b\u8f93\u5165\u200b\u3002
  • \u200b\u76ee\u524d\u200b\u5728\u200bGPU\u200b\u7aef\u200b\uff0c\u200b\u52a8\u6001\u200b\u8f93\u5165\u200b\u7684\u200b\u60c5\u51b5\u200b\u4e0b\u200b\uff0c\u200b\u901f\u5ea6\u200b\u6bd4\u200bCPU\u200b\u4e0a\u200b\u8fd8\u8981\u200b\u6162\u200b\u4e00\u4e9b\u200b\uff0c\u200b\u6682\u65f6\u200b\u5c1a\u672a\u200b\u89e3\u51b3\u200b\u3002
  • ONNXRuntime + TensorRT\u200b\u7ed3\u5408\u200b \u2192 \u200b\u5c1d\u8bd5\u200b\u4f46\u200b\u672a\u200b\u8dd1\u200b\u901a\u200b
"},{"location":"blog/2022/09/22/inference-summary/#openvino","title":"OpenVINO\uff08\u200b\u82f1\u7279\u5c14\u200b\uff09","text":"
  • CPU\u200b\u7aef\u200b\u63a8\u7406\u200b\u901f\u5ea6\u200b\u66f4\u200b\u5feb\u200b\uff0c\u200b\u652f\u6301\u200b\u52a8\u6001\u200b\u8f93\u5165\u200b\u3002\u200b\u4f46\u662f\u200b\u5360\u7528\u200b\u5185\u5b58\u200b\u8f83\u5927\u200b\uff0c\u200b\u62ff\u200b\u7a7a\u95f4\u200b\u6362\u200b\u4e86\u200b\u65f6\u95f4\u200b\u3002
  • \u200b\u5f53\u200b\u81ea\u5df1\u200b\u8d44\u6e90\u200b\u4e0d\u200b\u5403\u7d27\u200b\u65f6\u200b\uff0c\u200b\u4f46\u200b\u8981\u6c42\u200b\u66f4\u5feb\u200b\u5730\u200b\u63a8\u7406\u200b\u901f\u5ea6\u200b\u65f6\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u8003\u8651\u200b\u7528\u200b\u8fd9\u4e2a\u200b\u3002
  • GPU\u200b\u7aef\u4ec5\u200b\u652f\u6301\u200b\u81ea\u5bb6\u200b\u663e\u5361\u200b\uff0c\u200b\u6682\u65f6\u200b\u7528\u200b\u4e0d\u5230\u200b\u3002
"},{"location":"blog/2022/09/22/inference-summary/#mnn","title":"MNN\uff08\u200b\u963f\u91cc\u200b\uff09","text":"
  • GPU\u200b\u7aef\u200b\u6ca1\u6709\u200b\u627e\u5230\u200b\u5bb9\u6613\u200b\u7684\u200b\u4f7f\u7528\u200b\u65b9\u5f0f\u200b\uff0c\u200b\u9700\u8981\u200b\u81ea\u884c\u200b\u7f16\u8bd1\u200b\uff0c\u200b\u95e8\u69db\u200b\u592a\u9ad8\u200b\u3002\u200b\u7406\u60f3\u200b\u60c5\u51b5\u200b\u662f\u200b\u50cf\u200bonnxruntime-gpu\u200b\u8fd9\u79cd\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u5feb\u901f\u200b\u5b89\u88c5\u200b\u4f7f\u7528\u200b\u3002
  • \u200b\u8bf4\u200b\u662f\u200b\u652f\u6301\u200b\u52a8\u6001\u200b\u8f93\u5165\u200b\uff0c\u200b\u4f46\u662f\u200b\u5c1a\u672a\u200b\u627e\u5230\u200b\u6709\u6548\u200b\u9a8c\u8bc1\u200b\u65b9\u6cd5\u200b\u3002
"},{"location":"blog/2022/09/22/inference-summary/#tensorrt","title":"TensorRT\uff08\u200b\u82f1\u200b\u4f1f\u8fbe\u200b\uff09","text":"
  • GPU\u200b\u7aef\u200b\u5feb\u901f\u200b\u63a8\u7406\u200b\uff0c\u200b\u5360\u5751\u200b
  • \u200b\u636e\u8bf4\u200b\u5b58\u5728\u200b\u5185\u5b58\u200b\u6cc4\u6f0f\u200b\u7684\u200bbug\uff0c\u200b\u6682\u65f6\u200b\u6ca1\u6709\u200b\u5c1d\u8bd5\u200b\u3002
"},{"location":"blog/2022/09/22/inference-summary/#ncnn","title":"NCNN\uff08\u200b\u817e\u8baf\u200b\uff09","text":"
  • \u200b\u79fb\u52a8\u200b\u7aef\u200b\u6bd4\u8f83\u200b\u597d\u7528\u200b\u7684\u200b
  • \u200b\u5b58\u5728\u200b\u4e00\u4e2a\u200b\u95ee\u9898\u200b\uff1a\u200b\u5df2\u6709\u200b\u6a21\u578b\u200b\u8f6c\u6362\u200b\u4e3a\u200bNCNN\u200b\u683c\u5f0f\u200b\uff0c\u200b\u4f1a\u200b\u9047\u5230\u200b\u67d0\u4e9b\u200b\u7b97\u5b50\u200b\u4e0d\u200b\u652f\u6301\u200b\u60c5\u51b5\u200b
"},{"location":"blog/2022/09/22/inference-summary/#paddle-inference","title":"Paddle Inference\uff08\u200b\u767e\u5ea6\u200b\uff09","text":"
  • \u200b\u5b9a\u4f4d\u200b\u662f\u200b\u670d\u52a1\u7aef\u200b\u63a8\u7406\u200b\u6846\u67b6\u200b
  • \u200b\u4f9d\u8d56\u200bPaddle\u200b\u6846\u67b6\u200b\uff0c\u200b\u6709\u4e9b\u200b\u91cd\u200b\uff0c\u200b\u4f46\u662f\u200b\u4e0d\u5931\u4e3a\u200bGPU\u200b\u4e0a\u200b\u63a8\u7406\u6a21\u578b\u200b\u7684\u200b\u4e00\u4e2a\u200b\u9009\u62e9\u200b\u3002
  • \u200b\u76ee\u524d\u200b\u5df2\u7ecf\u200b\u91c7\u7528\u200b\uff0c\u200b\u5bf9\u5e94\u200brapidocr_paddle\u200b\u5e93\u200b\uff0c\u200b\u7528\u4ee5\u200b\u5f25\u8865\u200bGPU\u200b\u63a8\u7406\u200b\u7684\u200b\u77ed\u677f\u200b\u3002
"},{"location":"blog/2022/09/22/inference-summary/#paddle-lite","title":"Paddle Lite","text":"
  • Paddle Lite \u200b\u662f\u200b\u4e00\u7ec4\u200b\u5de5\u5177\u200b\uff0c\u200b\u53ef\u200b\u5e2e\u52a9\u200b\u5f00\u53d1\u8005\u200b\u5728\u200b\u79fb\u52a8\u200b\u8bbe\u5907\u200b\u3001\u200b\u5d4c\u5165\u5f0f\u200b\u8bbe\u5907\u200b\u548c\u200b loT \u200b\u8bbe\u5907\u200b\u4e0a\u200b\u8fd0\u884c\u200b\u6a21\u578b\u200b\uff0c\u200b\u4ee5\u4fbf\u200b\u5b9e\u73b0\u200b\u8bbe\u5907\u200b\u7aef\u200b\u673a\u5668\u200b\u5b66\u4e60\u200b\u3002
  • \u200b\u5b9a\u4f4d\u200b\u662f\u200b\u79fb\u52a8\u200b\u7aef\u200b\u548c\u200b\u8fb9\u7f18\u200b\u7aef\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b
"},{"location":"blog/2022/09/22/inference-summary/#paddlejs","title":"Paddle.js","text":"

\u200b\u7f51\u9875\u200b\u524d\u7aef\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b

"},{"location":"blog/2022/09/22/inference-summary/#fastdeploy","title":"FastDeploy\uff08\u200b\u767e\u5ea6\u200b\uff09","text":"

FastDeploy\u200b\u662f\u200b\u4e00\u6b3e\u200b\u5168\u200b\u573a\u666f\u200b\u3001\u200b\u6613\u7528\u200b\u7075\u6d3b\u200b\u3001\u200b\u6781\u81f4\u200b\u9ad8\u6548\u200b\u7684\u200bAI\u200b\u63a8\u7406\u200b\u90e8\u7f72\u200b\u5de5\u5177\u200b\uff0c \u200b\u652f\u6301\u200b\u4e91\u8fb9\u200b\u7aef\u200b\u90e8\u7f72\u200b\u3002\u200b\u63d0\u4f9b\u200b\u8d85\u8fc7\u200b \ud83d\udd25160+ Text\uff0cVision\uff0c Speech\u200b\u548c\u200b\u8de8\u200b\u6a21\u6001\u200b\u6a21\u578b\u200b\ud83d\udce6\u200b\u5f00\u7bb1\u200b\u5373\u7528\u200b\u7684\u200b\u90e8\u7f72\u200b\u4f53\u9a8c\u200b\uff0c\u200b\u5e76\u200b\u5b9e\u73b0\u200b\ud83d\udd1a\u200b\u7aef\u5230\u200b\u7aef\u7684\u200b\u63a8\u7406\u200b\u6027\u80fd\u200b\u4f18\u5316\u200b\u3002\u200b\u5305\u62ec\u200b \u200b\u7269\u4f53\u200b\u68c0\u6d4b\u200b\u3001\u200b\u5b57\u7b26\u8bc6\u522b\u200b\uff08OCR\uff09\u3001\u200b\u4eba\u8138\u200b\u3001\u200b\u4eba\u50cf\u200b\u6263\u56fe\u200b\u3001\u200b\u591a\u200b\u76ee\u6807\u200b\u8ddf\u8e2a\u200b\u7cfb\u7edf\u200b\u3001NLP\u3001Stable Diffusion\u200b\u6587\u56fe\u200b\u751f\u6210\u200b\u3001TTS \u200b\u7b49\u200b\u51e0\u5341\u79cd\u200b\u4efb\u52a1\u200b\u573a\u666f\u200b\uff0c\u200b\u6ee1\u8db3\u200b\u5f00\u53d1\u8005\u200b\u591a\u200b\u573a\u666f\u200b\u3001\u200b\u591a\u200b\u786c\u4ef6\u200b\u3001\u200b\u591a\u200b\u5e73\u53f0\u200b\u7684\u200b\u4ea7\u4e1a\u200b\u90e8\u7f72\u200b\u9700\u6c42\u200b\u3002

\u200b\u603b\u7ed3\u200b\u6765\u8bf4\u200b\u5c31\u662f\u200b\uff0c\u200b\u5c06\u200b\u5404\u4e2a\u200b\u573a\u666f\u200b\u4e0b\u200b\u7684\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u505a\u200b\u4e86\u200b\u96c6\u6210\u200b\uff0c\u200b\u66f4\u52a0\u200b\u65b9\u4fbf\u200b\u6613\u7528\u200b\uff0c\u200b\u5927\u800c\u5168\u200b\u3002

"},{"location":"blog/2022/09/22/inference-summary/#paddlex","title":"PaddleX","text":"

PaddleX \u200b\u96c6\u6210\u200b\u98de\u6868\u200b\u667a\u80fd\u200b\u89c6\u89c9\u200b\u9886\u57df\u200b\u56fe\u50cf\u200b\u5206\u7c7b\u200b\u3001\u200b\u76ee\u6807\u200b\u68c0\u6d4b\u200b\u3001\u200b\u8bed\u4e49\u200b\u5206\u5272\u200b\u3001\u200b\u5b9e\u4f8b\u200b\u5206\u5272\u200b\u4efb\u52a1\u200b\u80fd\u529b\u200b\uff0c\u200b\u5c06\u200b\u6df1\u5ea6\u200b\u5b66\u4e60\u200b\u5f00\u53d1\u200b\u5168\u200b\u6d41\u7a0b\u200b\u4ece\u200b\u6570\u636e\u200b\u51c6\u5907\u200b\u3001\u200b\u6a21\u578b\u200b\u8bad\u7ec3\u200b\u4e0e\u200b\u4f18\u5316\u200b\u5230\u200b\u591a\u7aef\u200b\u90e8\u7f72\u200b\u7aef\u5230\u200b\u7aef\u200b\u6253\u901a\u200b\uff0c\u200b\u5e76\u200b\u63d0\u4f9b\u200b\u7edf\u4e00\u200b\u4efb\u52a1\u200bAPI\u200b\u63a5\u53e3\u200b\u53ca\u200b\u56fe\u5f62\u5316\u200b\u5f00\u53d1\u200b\u754c\u9762\u200bDemo\u3002\u200b\u5f00\u53d1\u8005\u200b\u65e0\u9700\u200b\u5206\u522b\u200b\u5b89\u88c5\u200b\u4e0d\u540c\u200b\u5957\u4ef6\u200b\uff0c\u200b\u4ee5\u4f4e\u200b\u4ee3\u7801\u200b\u7684\u200b\u5f62\u5f0f\u200b\u5373\u53ef\u200b\u5feb\u901f\u200b\u5b8c\u6210\u200b\u98de\u6868\u200b\u5168\u200b\u6d41\u7a0b\u200b\u5f00\u53d1\u200b\u3002

\u200b\u603b\u7ed3\u200b\u6765\u8bf4\u200b\uff0cPaddleX\u200b\u5c31\u662f\u200b\u4e00\u4e2a\u200b\u6574\u5408\u200b\u5df2\u6709\u200b\u6a21\u578b\u200b\u7684\u200b\u4f4e\u200b\u4ee3\u7801\u200b\u5e73\u53f0\u200b\u3002\u200b\u4e25\u683c\u200b\u610f\u4e49\u200b\u6765\u8bf4\u200b\uff0c\u200b\u4e0d\u7b97\u200b\u4e00\u4e2a\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u3002

"},{"location":"blog/2022/10/04/which-inference/","title":"OCR\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u9009\u62e9\u200b\u6307\u5357","text":"

\u200b\u4ecb\u7ecd\u200b\u5728\u200bCPU\u200b\u7aef\u200b\u548c\u200bGPU\u200b\u7aef\u200b\uff0cOCR\u200b\u6a21\u578b\u200b\u7684\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u9009\u62e9\u200b\u95ee\u9898\u200b\u3002

"},{"location":"blog/2022/10/04/which-inference/#cpu","title":"CPU\u200b\u7aef\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u9009\u62e9","text":""},{"location":"blog/2022/10/04/which-inference/#rapidocr_onnxruntime","title":"\u2606 \u200b\u63a8\u8350\u200b\uff1arapidocr_onnxruntime","text":"

\u200b\u76ee\u524d\u200b\u53ef\u7528\u200b\u7684\u200b\u63a8\u7406\u200b\u5e93\u6709\u200b\uff1arapidocr_onnxruntime\uff0crapidocr_openvino\u200b\u548c\u200brapid_paddle\u3002\u200b\u8fd9\u200b\u4e09\u4e2a\u200b\u5e93\u5747\u200b\u53ef\u200b\u5728\u200bCPU\u200b\u4e0a\u200b\u63a8\u7406\u200b\uff0c\u200b\u9664\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u4e0d\u540c\u200b\u5916\u200b\uff0c\u200b\u5176\u4ed6\u200b\u63a5\u53e3\u200b\u5747\u200b\u76f8\u540c\u200b\u3002

\u200b\u5176\u4e2d\u200b\uff0c\u200b\u56e0\u4e3a\u200bopenvino\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u5728\u200b\u63a8\u7406\u200b\u5b8c\u5927\u56fe\u200b\u540e\u200b\uff0c\u200b\u6240\u200b\u5360\u7528\u200b\u7684\u200b\u5185\u5b58\u200b\u4e0d\u200b\u91ca\u653e\u200b\u95ee\u9898\u200b\uff08issue #11939\uff09\uff0c\u200b\u4e0d\u200b\u4f5c\u4e3a\u200b\u4f18\u5148\u200b\u8003\u8651\u200b\u3002

paddlepaddle\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\uff0c\u200b\u5e76\u672a\u200b\u6d4b\u8bd5\u200b\u4e0e\u200b\u5176\u4ed6\u200b\u4e24\u4e2a\u200b\u901f\u5ea6\u200b\u5dee\u5f02\u200b\u3002\u200b\u4f46\u662f\u200b\u76f8\u6bd4\u200b\u4e8e\u200b\u5176\u200bCPU\u200b\u7248\u200b\u5b89\u88c5\u5305\u200b\u8f83\u5927\u200b\uff0c\u200b\u8f83\u4e3a\u200b\u81c3\u80bf\u200b\uff0c\u200b\u4e0d\u5229\u4e8e\u200b\u5206\u53d1\u200b\uff0c\u200b\u56e0\u6b64\u200b\u4e5f\u200b\u4e0d\u4f5c\u200b\u8003\u8651\u200b\u3002\u200b\u4e2a\u4eba\u200b\u8ba4\u4e3a\u200b\uff0cpaddlepaddle\u200b\u4f18\u52bf\u200b\u5728\u4e8e\u200b\u5bf9\u200b\u56fd\u4ea7\u200b\u673a\u5668\u200b\u7684\u200b\u9002\u914d\u200b\u3002

\u200b\u5b89\u88c5\u5305\u200b\u540d\u79f0\u200b \u200b\u5927\u5c0f\u200b paddlepaddle-3.0.0b0-cp312-cp312-win_amd64.whl 90.1MB openvino-2024.2.0-15519-cp312-cp312-win_amd64.whl 32.4MB onnxruntime-1.18.1-cp312-cp312-win_amd64.whl 5.6MB

\u200b\u6c47\u603b\u200b\u5982\u4e0b\u200b\uff1a

\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b \u200b\u63a8\u7406\u200b\u901f\u5ea6\u200b\u66f4\u200b\u5feb\u200b \u200b\u5360\u7528\u200b\u5185\u5b58\u200b\u66f4\u200b\u5c11\u200b rapidocr_onnxruntime \u2713 rapidocr_openvino \u2713"},{"location":"blog/2022/10/04/which-inference/#gpu","title":"GPU\u200b\u7aef\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u9009\u62e9","text":""},{"location":"blog/2022/10/04/which-inference/#rapidocr_paddle","title":"\u2606 \u200b\u63a8\u8350\u200b\uff1arapidocr_paddle","text":""},{"location":"blog/2022/10/04/which-inference/#link","title":"\u63a8\u8350\u200b\u7406\u7531\u200b \u2192 link","text":""},{"location":"blog/2022/10/04/which-inference/#_1","title":"\u5176\u4ed6\u200b\u4e0d\u200b\u63a8\u8350\u200b\u539f\u56e0","text":"

rapidocr_openvino: \u200b\u51fa\u81ea\u200b\u82f1\u7279\u5c14\u200b\uff0c\u200b\u53ea\u200b\u9002\u914d\u200b\u81ea\u5bb6\u200bGPU\uff0c\u200b\u56e0\u6b64\u200b\uff0c\u200b\u80af\u5b9a\u200b\u4e0d\u200b\u652f\u6301\u200b\u5176\u4ed6\u200b\u5bb6\u200b\u7684\u200b\u3002\u200b\u5982\u679c\u200b\u652f\u6301\u200b\u4e86\u200b\uff0c\u200b\u70e6\u8bf7\u200b\u7559\u8a00\u200b\u544a\u77e5\u200b\u3002

rapidocr_onnxruntime: onnxruntime-gpu\u200b\u7248\u200b\u5bf9\u200b\u52a8\u6001\u56fe\u200b\u652f\u6301\u200b\u8f83\u5dee\u200b\uff0c\u200b\u63a8\u7406\u200b\u901f\u5ea6\u200b\u5f88\u200b\u6162\u200b\u3002OCR\u200b\u4e2d\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u90e8\u5206\u200b\u8f93\u5165\u200b\u5c31\u662f\u200b\u52a8\u6001\u200b\u7684\u200b\u3002\u200b\u8be6\u7ec6\u200b\u53c2\u89c1\u200b\u6587\u6863\u200b \u2192 link

"},{"location":"blog/2022/10/04/which-inference/#_2","title":"\u5982\u679c\u200b\u9047\u5230\u200b\u5185\u5b58\u200b\u6cc4\u9732\u200b\u600e\u4e48\u529e\u200b\uff1f","text":""},{"location":"blog/2022/10/04/which-inference/#_3","title":"\u5185\u5b58\u200b\u6cc4\u9732\u200b\u95ee\u9898\u200b\u662f\u200b\u4ec0\u4e48\u200b\uff1f","text":"

\u200b\u5185\u5b58\u200b\u6cc4\u9732\u200b\u95ee\u9898\u200b\u6307\u200b\u7684\u200b\u662f\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u5728\u200b\u63d0\u53d6\u200b\u8f83\u5927\u200b\u56fe\u50cf\u200b\u6587\u5b57\u200b\u65f6\u200b\uff0c\u200b\u4f1a\u200b\u7533\u8bf7\u200b\u8f83\u200b\u591a\u200b\u5185\u5b58\u200b\u3002\u200b\u800c\u200b\u5728\u200b\u63d0\u53d6\u200b\u5b8c\u6210\u200b\u4e4b\u540e\u200b\uff0c\u200b\u4e0d\u200b\u91ca\u653e\u200b\u8fd9\u4e9b\u200b\u4e34\u65f6\u200b\u7533\u8bf7\u200b\u7684\u200b\u5185\u5b58\u200b\u3002\u200b\u5982\u679c\u200b\u540e\u7eed\u200b\u518d\u200b\u9047\u5230\u200b\u4e00\u5f20\u200b\u66f4\u5927\u200b\u5c3a\u5bf8\u200b\u7684\u200b\u56fe\u50cf\u200b\uff0c\u200b\u5f53\u524d\u200b\u5185\u5b58\u200b\u4e0d\u591f\u200b\u7528\u200b\u7684\u8bdd\u200b\uff0c\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u4f1a\u200b\u7533\u8bf7\u200b\u66f4\u200b\u591a\u200b\u5185\u5b58\u200b\u3002\u200b\u540c\u6837\u200b\uff0c\u200b\u8fd9\u4e9b\u200b\u5185\u5b58\u200b\u4e5f\u200b\u4e0d\u4f1a\u200b\u88ab\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u91ca\u653e\u200b\u3002

\u200b\u8fd9\u6837\u200b\uff0c\u200b\u540e\u7eed\u200b\u5982\u679c\u200b\u518d\u200b\u9047\u5230\u200b\u66f4\u5927\u200b\u5c3a\u5bf8\u200b\u56fe\u50cf\u200b\uff0c\u200b\u5219\u200b\u673a\u5668\u200b\u5f88\u200b\u5bb9\u6613\u200b\u5185\u5b58\u200b\u6ea2\u51fa\u200b\u3002

"},{"location":"blog/2022/10/04/which-inference/#_4","title":"\u54ea\u4e9b\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u6709\u200b\u8fd9\u4e2a\u200b\u95ee\u9898\u200b\uff1f","text":"

\u200b\u5df2\u77e5\u200b\u7684\u200b\u662f\u200bOpenVino\u200b\u548c\u200bPaddlePaddle\u200b\u5b58\u5728\u200b\u8fd9\u4e2a\u200b\u95ee\u9898\u200b\uff0cONNXRuntime\u200b\u6ca1\u6709\u200b\u3002

"},{"location":"blog/2022/10/04/which-inference/#_5","title":"\u53ef\u80fd\u200b\u7684\u200b\u89e3\u51b3\u65b9\u6848","text":"

\u200b\u603b\u7ed3\u200b\u81ea\u200b\u7fa4\u53cb\u200b\uff1a\u200b\u591a\u200b\u8fdb\u7a0b\u200b/\u200b\u7ebf\u7a0b\u200b + \u200b\u5b9a\u65f6\u200b\u91cd\u542f\u200b

"},{"location":"blog/2022/09/23/onnxruntime-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/","title":"ONNXRuntime CPU\u200b\u63a8\u7406\u200b\u4f18\u5316","text":""},{"location":"blog/2022/09/23/onnxruntime-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/#_1","title":"\u5f15\u8a00","text":"
  • \u200b\u5e73\u65f6\u200b\u63a8\u7406\u200b\u7528\u200b\u7684\u200b\u6700\u200b\u591a\u200b\u662f\u200bONNXRuntime\uff0c\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u7684\u200b\u5408\u9002\u200b\u8c03\u914d\u200b\u5bf9\u200b\u63a8\u7406\u200b\u6027\u80fd\u200b\u6709\u7740\u200b\u81f3\u5173\u91cd\u8981\u200b\u7684\u200b\u5f71\u54cd\u200b\u3002\u200b\u4f46\u662f\u200b\u6709\u200b\u5173\u4e8e\u200bONNXRuntime\u200b\u53c2\u6570\u8bbe\u7f6e\u200b\u7684\u200b\u8d44\u6599\u200b\u5374\u200b\u6563\u843d\u200b\u5728\u200b\u5404\u4e2a\u200b\u5730\u65b9\u200b\uff0c\u200b\u4e0d\u80fd\u200b\u5f62\u6210\u200b\u6709\u6548\u200b\u7684\u200b\u6307\u5bfc\u200b\u610f\u89c1\u200b\u3002
  • \u200b\u56e0\u6b64\u200b\uff0c\u200b\u51b3\u5b9a\u200b\u5728\u200b\u8fd9\u200b\u4e00\u7bc7\u200b\u6587\u7ae0\u200b\u4e2d\u6765\u200b\u68b3\u7406\u200b\u4e00\u4e0b\u200b\u76f8\u5173\u200b\u7684\u200b\u8bbe\u7f6e\u200b\u3002
  • \u200b\u4ee5\u4e0b\u200b\u53c2\u6570\u200b\u90fd\u200b\u662f\u200b\u6765\u81ea\u200bSessionOptions\u200b\u4e2d\u200b
  • \u200b\u76f8\u5173\u200b\u6d4b\u8bd5\u4ee3\u7801\u200b\u53ef\u4ee5\u200b\u524d\u5f80\u200bAI Studio\u200b\u67e5\u770b\u200b
  • \u200b\u6b22\u8fce\u200b\u8865\u5145\u200b\u548c\u200b\u6307\u51fa\u200b\u4e0d\u8db3\u4e4b\u5904\u200b\u3002
"},{"location":"blog/2022/09/23/onnxruntime-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/#_2","title":"\u63a8\u8350\u200b\u5e38\u7528\u200b\u8bbe\u7f6e","text":"
import onnxruntime as rt\n\nsess_options = rt.SessionOptions()\nsess_options.graph_optimization_level = rt.GraphOptimizationLevel.ORT_ENABLE_ALL\nsess_options.log_severity_level = 4\nsess_options.enable_cpu_mem_arena = False\n\n# \u200b\u5176\u4ed6\u200b\u53c2\u6570\u200b\uff0c\u200b\u91c7\u7528\u200b\u9ed8\u8ba4\u200b\u5373\u53ef\u200b\n
"},{"location":"blog/2022/09/23/onnxruntime-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/#enable_cpu_mem_arena","title":"enable_cpu_mem_arena","text":"
  • \u200b\u4f5c\u7528\u200b\uff1a\u200b\u542f\u7528\u200bCPU\u200b\u4e0a\u200b\u7684\u200bmemory arena\u3002Arena\u200b\u53ef\u80fd\u200b\u4f1a\u4e3a\u200b\u5c06\u6765\u200b\u9884\u5148\u200b\u7533\u8bf7\u200b\u5f88\u591a\u200b\u5185\u5b58\u200b\u3002\u200b\u5982\u679c\u200b\u4e0d\u60f3\u200b\u4f7f\u7528\u200b\u5b83\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u8bbe\u7f6e\u200b\u4e3a\u200benable_cpu_mem_area=False\uff0c\u200b\u9ed8\u8ba4\u200b\u662f\u200bTrue

  • \u200b\u7ed3\u8bba\u200b\uff1a\u200b\u5efa\u8bae\u200b\u5173\u95ed\u200b

    • \u200b\u5f00\u542f\u200b\u4e4b\u540e\u200b\uff0c\u200b\u5360\u7528\u200b\u5185\u5b58\u200b\u4f1a\u200b\u5267\u589e\u200b\uff085618.3M >> 5.3M\uff09\uff0c\u200b\u4e14\u200b\u6301\u7eed\u200b\u5360\u7528\u200b\uff0c\u200b\u4e0d\u200b\u91ca\u653e\u200b\uff1b\u200b\u63a8\u7406\u200b\u65f6\u95f4\u200b\u53ea\u6709\u200b\u5927\u7ea6\u200b13%\u200b\u63d0\u5347\u200b

  • \u200b\u6d4b\u8bd5\u73af\u5883\u200b\uff1a

    • Python: 3.7.13
    • ONNXRuntime: 1.14.1

  • \u200b\u6d4b\u8bd5\u4ee3\u7801\u200b\uff08\u200b\u6765\u81ea\u200bissue 11627\uff0cenable_cpu_memory_area_example.zip\uff09

    # pip install onnxruntime==1.14.1\n# pip install memory_profiler\n\nimport numpy as np\nimport onnxruntime as ort\nfrom memory_profiler import profile\n\n\n@profile\ndef onnx_prediction(model_path, input_data):\n    ort_sess = ort.InferenceSession(model_path, sess_options=sess_options)\n    preds = ort_sess.run(output_names=[\"predictions\"],\n                         input_feed={\"input_1\": input_data})[0]\n    return preds\n\n\nsess_options = ort.SessionOptions()\nsess_options.enable_cpu_mem_arena = False\n\ninput_data = np.load('enable_cpu_memory_area_example/input.npy')\nprint(f'input_data shape: {input_data.shape}')\nmodel_path = 'enable_cpu_memory_area_example/model.onnx'\n\nonnx_prediction(model_path, input_data)\n

  • Windows\u200b\u7aef\u200b | Mac\u200b\u7aef\u200b | Linux\u200b\u7aef\u200b \u200b\u6d4b\u8bd5\u200b\u60c5\u51b5\u200b\u90fd\u200b\u5927\u81f4\u76f8\u540c\u200b

    • enable_cpu_mem_arena=True

      (demo) PS G:> python .\\test_enable_cpu_mem_arena.py\nenable_cpu_mem_arena: True\ninput_data shape: (32, 200, 200, 1)\nFilename: .\\test_enable_cpu_mem_arena.py\n\nLine #    Mem usage    Increment  Occurrences   Line Contents\n=============================================================\n    7     69.1 MiB     69.1 MiB           1   @profile\n    8                                         def onnx_prediction(model_path, input_data):\n    9     77.2 MiB      8.1 MiB           1       ort_sess = ort.InferenceSession(model_path, sess_options=sess_options)\n    10     77.2 MiB      0.0 MiB           1       preds = ort_sess.run(output_names=[\"predictions\"],\n    11   5695.5 MiB   5618.3 MiB           1                            input_feed={\"input_1\": input_data})[0]\n    12   5695.5 MiB      0.0 MiB           1       return preds\n

    • enable_cpu_mem_arena=False

      (demo) PS G:> python .\\test_enable_cpu_mem_arena.py\nenable_cpu_mem_arena: False\ninput_data shape: (32, 200, 200, 1)\nFilename: .\\test_enable_cpu_mem_arena.py\n\nLine #    Mem usage    Increment  Occurrences   Line Contents\n=============================================================\n    7     69.1 MiB     69.1 MiB           1   @profile\n    8                                         def onnx_prediction(model_path, input_data):\n    9     76.9 MiB      7.8 MiB           1       ort_sess = ort.InferenceSession(model_path, sess_options=sess_options)\n    10     76.9 MiB      0.0 MiB           1       preds = ort_sess.run(output_names=[\"predictions\"],\n    11     82.1 MiB      5.3 MiB           1                            input_feed={\"input_1\": input_data})[0]\n    12     82.1 MiB      0.0 MiB           1       return preds\n
    "},{"location":"blog/2022/09/23/onnxruntime-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/#enable_profiling","title":"enable_profiling","text":"
    • \u200b\u5f00\u542f\u200b\u8fd9\u4e2a\u200b\u53c2\u6570\u200b\uff0c\u200b\u5728\u200b\u63a8\u7406\u200b\u65f6\u200b\uff0c\u200b\u4f1a\u200b\u751f\u6210\u200b\u4e00\u4e2a\u200b\u7c7b\u4f3c\u200bonnxruntime_profile__2023-05-07_09-02-15.json\u200b\u7684\u200b\u65e5\u5fd7\u200b\u6587\u4ef6\u200b\uff0c\u200b\u5305\u542b\u200b\u8be6\u7ec6\u200b\u7684\u200b\u6027\u80fd\u200b\u6570\u636e\u200b\uff08\u200b\u7ebf\u7a0b\u200b\u3001\u200b\u6bcf\u4e2a\u200b\u8fd0\u7b97\u7b26\u200b\u7684\u200b\u5ef6\u8fdf\u200b\u7b49\u200b\uff09\u3002
    • \u200b\u5efa\u8bae\u200b\u5f00\u542f\u200b

    • \u200b\u793a\u4f8b\u200b\u4ee3\u7801\u200b\uff1a

      import onnxruntime as rt\n\nsess_options = rt.SessionOptions()\nsess_options.enable_profiling = True\n
    "},{"location":"blog/2022/09/23/onnxruntime-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/#execution_mode","title":"execution_mode","text":"
    • \u200b\u8bbe\u7f6e\u200b\u8fd0\u884c\u200b\u6a21\u578b\u200b\u7684\u200b\u6a21\u5f0f\u200b\uff0c\u200b\u5305\u62ec\u200brt.ExecutionMode.ORT_SEQUENTIAL\u200b\u548c\u200brt.ExecutionMode.ORT_PARALLEL\u3002\u200b\u4e00\u4e2a\u200b\u5e8f\u5217\u200b\u6267\u884c\u200b\uff0c\u200b\u4e00\u4e2a\u200b\u5e76\u884c\u200b\u3002\u200b\u9ed8\u8ba4\u200b\u662f\u200b\u5e8f\u5217\u200b\u6267\u884c\u200b
    • \u200b\u901a\u5e38\u200b\u6765\u8bf4\u200b\uff0c\u200b\u5f53\u200b\u4e00\u4e2a\u200b\u6a21\u578b\u200b\u4e2d\u6709\u200b\u8bb8\u591a\u200b\u5206\u652f\u200b\u65f6\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u8bbe\u7f6e\u200b\u8be5\u200b\u53c2\u6570\u200b\u4e3a\u200bORT_PARALLEL\u200b\u6765\u200b\u8fbe\u5230\u200b\u66f4\u597d\u200b\u7684\u200b\u8868\u73b0\u200b
    • \u200b\u5f53\u200b\u8bbe\u7f6e\u200bsess_options.execution_mode = rt.ExecutionMode.ORT_PARALLEL\u200b\u65f6\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u8bbe\u7f6e\u200bsess_options.inter_op_num_threads\u200b\u6765\u200b\u63a7\u5236\u200b\u4f7f\u7528\u200b\u7ebf\u7a0b\u200b\u7684\u200b\u6570\u91cf\u200b\uff0c\u200b\u6765\u200b\u5e76\u884c\u200b\u5316\u200b\u6267\u884c\u200b\uff08\u200b\u6a21\u578b\u200b\u4e2d\u200b\u5404\u4e2a\u200b\u8282\u70b9\u200b\u4e4b\u95f4\u200b\uff09
    "},{"location":"blog/2022/09/23/onnxruntime-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/#inter_op_num_threads","title":"inter_op_num_threads","text":"
    • \u200b\u8bbe\u7f6e\u200b\u5e76\u884c\u200b\u5316\u200b\u6267\u884c\u200b\u56fe\u200b\uff08\u200b\u8de8\u200b\u8282\u70b9\u200b\uff09\u200b\u65f6\u200b\uff0c\u200b\u4f7f\u7528\u200b\u7684\u200b\u7ebf\u7a0b\u200b\u6570\u200b\u3002\u200b\u9ed8\u8ba4\u200b\u662f\u200b0\uff0c\u200b\u4ea4\u7531\u200bonnxruntime\u200b\u81ea\u884c\u51b3\u5b9a\u200b\u3002

    • \u200b\u793a\u4f8b\u200b\u4ee3\u7801\u200b\uff1a

      import onnxruntime as rt\n\nsess_options = rt.SessionOptions()\nsess_options.inter_op_num_threads = 2\n
    "},{"location":"blog/2022/09/23/onnxruntime-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/#intra_op_num_threads","title":"intra_op_num_threads","text":"
    • \u200b\u8bbe\u7f6e\u200b\u5e76\u884c\u200b\u5316\u200b\u6267\u884c\u200b\u56fe\u200b\uff08\u200b\u5185\u90e8\u200b\u8282\u70b9\u200b\uff09\u200b\u65f6\u200b\uff0c\u200b\u4f7f\u7528\u200b\u7684\u200b\u7ebf\u7a0b\u200b\u6570\u200b\u3002\u200b\u9ed8\u8ba4\u200b\u662f\u200b0\uff0c\u200b\u4ea4\u7531\u200bonnxruntime\u200b\u81ea\u884c\u51b3\u5b9a\u200b\uff0c\u200b\u4e00\u822c\u200b\u4f1a\u200b\u9009\u62e9\u200b\u4f7f\u7528\u200b\u8bbe\u5907\u200b\u4e0a\u200b\u6240\u6709\u200b\u7684\u200b\u6838\u200b\u3002
    • \u26a0\ufe0f \u200b\u8fd9\u4e2a\u200b\u503c\u200b\u5e76\u200b\u4e0d\u662f\u200b\u8d8a\u5927\u8d8a\u200b\u597d\u200b\uff0c\u200b\u5177\u4f53\u200b\u53c2\u8003\u200bAI Studio\u200b\u4e2d\u200b\u7684\u200b\u6d88\u878d\u200b\u5b9e\u9a8c\u200b\u3002

    • \u200b\u793a\u4f8b\u200b\u4ee3\u7801\u200b\uff1a

      import onnxruntime as rt\n\nsess_options = rt.SessionOptions()\nsess_options.intra_op_num_threads = 2\n
    "},{"location":"blog/2022/09/23/onnxruntime-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/#graph_optimization_level","title":"graph_optimization_level","text":"
    • \u200b\u8fd0\u884c\u56fe\u200b\u65f6\u200b\uff0c\u200b\u5bf9\u56fe\u200b\u4e2d\u200b\u7b97\u5b50\u200b\u7684\u200b\u4f18\u5316\u200b\u6c34\u5e73\u200b\u3002\u200b\u9ed8\u8ba4\u200b\u662f\u200b\u5f00\u542f\u200b\u5168\u90e8\u200b\u7b97\u5b50\u200b\u7684\u200b\u4f18\u5316\u200b\u3002\u200b\u5efa\u8bae\u200b\u91c7\u7528\u200b\u9ed8\u8ba4\u503c\u200b\u5373\u53ef\u200b\u3002
    • \u200b\u53ef\u9009\u200b\u7684\u200b\u679a\u4e3e\u200b\u503c\u6709\u200b\uff1aORT_DISABLE_ALL | ORT_ENABLE_BASIC | ORT_ENABLE_EXTENDED | ORT_ENABLE_ALL

    • \u200b\u793a\u4f8b\u200b\u4ee3\u7801\u200b\uff1a

      import onnxruntime as rt\n\nsess_options = rt.SessionOptions()\nsess_options.graph_optimization_level = rt.GraphOptimizationLevel.ORT_ENABLE_ALL\n
    "},{"location":"blog/2022/09/23/onnxruntime-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/#_3","title":"\u53c2\u8003\u8d44\u6599","text":"
    • ONNX Runtime Performance Tuning
    • Python API
    "},{"location":"blog/2022/09/24/onnxruntime-gpu%E6%8E%A8%E7%90%86/","title":"ONNXRuntime GPU\u200b\u63a8\u7406","text":""},{"location":"blog/2022/09/24/onnxruntime-gpu%E6%8E%A8%E7%90%86/#onnxruntime-gpu","title":"onnxruntime-gpu\u200b\u7248\u200b\u76f8\u5173\u200b\u8bf4\u660e","text":"
    • \u200b\u76ee\u524d\u200b\u5df2\u77e5\u200b\u5728\u200bonnxruntime-gpu\u200b\u4e0a\u200b\u6d4b\u8bd5\u200b\u8fc7\u200b\u7684\u200b\u5c0f\u4f19\u4f34\u200b\uff0c\u200b\u53cd\u6620\u200b\u90fd\u200b\u662f\u200bGPU\u200b\u63a8\u7406\u200b\u901f\u5ea6\u200b\u6bd4\u200b\u5728\u200bCPU\u200b\u4e0a\u6162\u200b\u5f88\u591a\u200b\u3002\u200b\u5173\u4e8e\u200b\u8be5\u200b\u95ee\u9898\u200b\uff0c\u200b\u5df2\u7ecf\u200b\u63d0\u4e86\u200b\u76f8\u5173\u200bissue\uff0c\u200b\u5177\u4f53\u200b\u53ef\u200b\u53c2\u89c1\u200bonnxruntime issue#13198
    "},{"location":"blog/2022/09/24/onnxruntime-gpu%E6%8E%A8%E7%90%86/#onnxruntime-gpu_1","title":"\u6709\u5173\u200bonnxruntime-gpu\u200b\u63a8\u7406\u200b\u6162\u200b\u7684\u200b\u76f8\u5173\u200b\u5e16\u5b50","text":"
    • Pre-allocating dynamic shaped tensor memory for ONNX runtime inference?
    "},{"location":"blog/2022/09/24/onnxruntime-gpu%E6%8E%A8%E7%90%86/#_1","title":"\u5feb\u901f\u200b\u67e5\u770b\u200b\u6bd4\u8f83\u200b\u7248\u672c","text":"
    • \u200b\u56fd\u5916\u200b\u5c0f\u4f19\u4f34\u200b\u53ef\u4ee5\u200b\u57fa\u4e8e\u200bGoogle Colab\uff0c\u200b\u56fd\u5185\u200b\u7684\u200b\u5c0f\u4f19\u4f34\u200b\u53ef\u4ee5\u200b\u57fa\u4e8e\u200b\u767e\u5ea6\u200b\u7684\u200bAI Studio\u200b\u6765\u200b\u67e5\u770b\u200b\u6548\u679c\u200b
    "},{"location":"blog/2022/09/24/onnxruntime-gpu%E6%8E%A8%E7%90%86/#_2","title":"\u7ed3\u8bba","text":"

    onnxruntime-gpu\u200b\u7248\u200b\u5728\u200b\u52a8\u6001\u200b\u8f93\u5165\u200b\u60c5\u51b5\u200b\u4e0b\u200b\uff0c\u200b\u63a8\u7406\u200b\u901f\u5ea6\u200b\u8981\u200b\u6bd4\u200bCPU\u200b\u6162\u200b\u5f88\u591a\u200b\u3002\u200b\u800c\u200bOCR\u200b\u4efb\u52a1\u200b\u5c31\u662f\u200b\u52a8\u6001\u200b\u8f93\u5165\u200b\uff0c\u200b\u56e0\u6b64\u200b\u4e0d\u200b\u63a8\u8350\u200b\u4f7f\u7528\u200bonnxruntime-gpu\u200b\u7248\u200b\u63a8\u7406\u200b\u3002

    \u200b\u76ee\u524d\u200b\u4e00\u76f4\u200b\u5728\u200b\u627e\u5bfb\u200bGPU\u200b\u7aef\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u5feb\u901f\u200b\u63a8\u7406\u200bONNX\u200b\u6a21\u578b\u200b\u7684\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u3002

    "},{"location":"blog/2022/09/24/onnxruntime-gpu%E6%8E%A8%E7%90%86/#_3","title":"\u76f8\u5173\u200b\u5bf9\u6bd4\u200b\u8868\u683c","text":"\u8bbe\u5907\u200b onnxruntime-gpu CPU\u200b\u603b\u200b\u8017\u65f6\u200b(s) CPU\u200b\u5e73\u5747\u200b\u8017\u65f6\u200b(s/img) GPU\u200b\u603b\u200b\u8017\u65f6\u200b(s) GPU\u200b\u5e73\u5747\u200b\u8017\u65f6\u200b(s/img) \u200b\u8bbe\u5907\u200b11 1.11.0 296.8841 1.18282 646.14667 2.57429 \u200b\u8bbe\u5907\u200b22 1.12.1 149.35427 0.50504 250.81760 0.99927

    1. \u200b\u5b8f\u7881\u200b(Acer) \u200b\u6697\u5f71\u200b\u9a91\u58eb\u200b\u00b7\u200b\u5a01\u200bN50-N93\u200b\u6e38\u620f\u200b\u53f0\u5f0f\u673a\u200b | Windows | \u200b\u5341\u4ee3\u200bi5-10400F 16G 512G SSD | NVIDIA GeForce GTX 1660Super 6G\u00a0\u21a9

    2. Linux | AMD R9 5950X | NVIDIA GeForce RTX 3090\u00a0\u21a9

    "},{"location":"blog/2022/09/26/openvino-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/","title":"OpenVINO CPU\u200b\u63a8\u7406\u200b\u4f18\u5316","text":"
    • \u200b\u5b98\u65b9\u200b\u53c2\u8003\u200b\u6587\u6863\u200b\uff1adocs
    • \u200b\u8003\u8651\u200b\u5230\u200bopenvino\u200b\u53ea\u80fd\u200b\u4f7f\u7528\u200b\u81ea\u5bb6\u200b\u663e\u5361\u200b\u63a8\u7406\u200b\uff0c\u200b\u901a\u7528\u6027\u200b\u4e0d\u9ad8\u200b\uff0c\u200b\u8fd9\u91cc\u200b\u6682\u4e0d\u4f5c\u200b\u76f8\u5173\u200b\u914d\u7f6e\u200b\u8bf4\u660e\u200b\u3002
    "},{"location":"blog/2022/09/25/openvino-gpu%E6%8E%A8%E7%90%86/","title":"OpenVINO GPU\u200b\u63a8\u7406","text":"

    Warning

    \u200b\u57fa\u4e8e\u200b\u76ee\u524d\u200bopenvino==2022.3.0\u200b\u7248\u200b\uff0c\u200b\u5b58\u5728\u200b\u7533\u8bf7\u200b\u5185\u5b58\u200b\u4e0d\u200b\u91ca\u653e\u200b\u7684\u200b\u95ee\u9898\u200b\uff0c\u200b\u8fd9\u200b\u4e5f\u200b\u5c31\u200b\u610f\u5473\u7740\u200b\u5f53\u200b\u63a8\u7406\u200b\u56fe\u50cf\u200b\u5f88\u5927\u200b\u65f6\u200b\uff0c\u200b\u63a8\u7406\u200b\u5b8c\u200b\u4e4b\u540e\u200b\uff0c\u200b\u5185\u5b58\u200b\u4f1a\u200b\u4e00\u76f4\u200b\u5360\u7528\u200b\u3002\u200b\u8be6\u60c5\u200b\u53ef\u200b\u53c2\u89c1\u200bissue11939

    "},{"location":"blog/2022/09/25/openvino-gpu%E6%8E%A8%E7%90%86/#_1","title":"\u5b89\u88c5","text":"
    $ pip install openvino\n\n# \u200b\u91cc\u9762\u200b\u542b\u6709\u200bmo\n$ pip install openvino-dev\n
    "},{"location":"blog/2022/09/25/openvino-gpu%E6%8E%A8%E7%90%86/#_2","title":"\u6a21\u578b\u200b\u95ee\u9898","text":"
    • \u200b\u56e0\u4e3a\u200bOpenVINO\u200b\u53ef\u4ee5\u200b\u76f4\u63a5\u63a8\u7406\u200bONNX\u200b\u6a21\u578b\u200b\uff0c\u200b\u6545\u200b\u8fd9\u91cc\u200b\u6682\u65f6\u200b\u4e0d\u200b\u4f5c\u200b\u8f6c\u6362\u200b\uff0c\u200b\u76f4\u63a5\u63a8\u7406\u200b\u4e4b\u524d\u200bONNX\u200b\u6a21\u578b\u200b\u5373\u53ef\u200b

    • \u200b\u8fd9\u91cc\u200b\u4ecd\u7136\u200b\u7ed9\u51fa\u200b\u8f6c\u6362\u200b\u7684\u200b\u4ee3\u7801\u200b\uff0c\u200b\u7528\u4f5c\u200b\u53c2\u8003\u200b:

      mo --input_model models/ch_PP-OCRv2_det_infer.onnx --output_dir models/IR/\n\nmo --input_model models/ch_PP-OCRv2_det_infer.onnx \\\n--output_dir models/IR/static \\\n--input_shape \"[1,3,12128,800]\"\n
    "},{"location":"blog/2022/09/25/openvino-gpu%E6%8E%A8%E7%90%86/#openvino","title":"\u5173\u4e8e\u200bOpenVINO","text":"

    • OpenVINO\u200b\u53ef\u4ee5\u200b\u76f4\u63a5\u63a8\u7406\u200bIR\u3001ONNX\u200b\u548c\u200bPaddlePaddle\u200b\u6a21\u578b\u200b\uff0c\u200b\u5177\u4f53\u200b\u5982\u4e0b\u200b(\u200b\u56fe\u200b\u6765\u6e90\u200b:link)\uff1a

    • \u200b\u548c\u200bONNXRuntime\u200b\u540c\u65f6\u200b\u63a8\u7406\u200b\u540c\u4e00\u4e2a\u200bONNX\u200b\u6a21\u578b\u200b\uff0cOpenVINO\u200b\u63a8\u7406\u200b\u901f\u5ea6\u200b\u66f4\u200b\u5feb\u200b

    • \u200b\u4f46\u662f\u200b\u4ece\u200b\u5bf9\u6bd4\u200b\u6765\u770b\u200b\uff0cOpenVINO\u200b\u5360\u7528\u200b\u5185\u5b58\u200b\u66f4\u5927\u200b\uff0c\u200b\u5176\u200b\u539f\u56e0\u200b\u662f\u200b\u62ff\u200b\u7a7a\u95f4\u200b\u6362\u200b\u7684\u200b\u65f6\u95f4\u200b

      • \u200b\u5f53\u200b\u6307\u5b9a\u200binput_shape\u200b\u5728\u200b\u4e00\u4e2a\u200b\u533a\u95f4\u200b\u8303\u56f4\u200b\u65f6\u200b\uff0c\u200b\u63a8\u7406\u200b\u65f6\u200b\u5185\u5b58\u200b\u5360\u7528\u200b\u4f1a\u200b\u51cf\u5c11\u200b\u4e00\u4e9b\u200b\u3002\u200b\u793a\u4f8b\u200b\u547d\u4ee4\u200b:
      mo --input_model models/ch_PP-OCRv2_det_infer.onnx \\\n--output_dir models/IR/static \\\n--input_shape \"[1,3,960:1200,800]\"\n
    "},{"location":"blog/2022/09/25/openvino-gpu%E6%8E%A8%E7%90%86/#openvinoonnxruntime","title":"OpenVINO\u200b\u4e0e\u200bONNXRuntime\u200b\u6027\u80fd\u200b\u5bf9\u6bd4","text":"
    • \u200b\u63a8\u7406\u200b\u8bbe\u5907\u200b\uff1aWindows 64\u200b\u4f4d\u200b Intel(R) Core(TM) i5-4210M CPU @ 2.60GHz 2.59 GHz
    • \u200b\u6d4b\u8bd5\u200b\u56fe\u50cf\u200b\u5bbd\u9ad8\u200b: 12119x810
    \u200b\u6d4b\u8bd5\u200b\u6a21\u578b\u200b \u200b\u63a8\u7406\u200b\u6846\u67b6\u200b \u200b\u5360\u7528\u200b\u5185\u5b58\u200b(3\u200b\u6b21\u200b\u5e73\u5747\u200b) \u200b\u63a8\u7406\u200b\u65f6\u95f4\u200b(3\u200b\u6b21\u200b\u5e73\u5747\u200b) ch_PP-OCRv2_det_infer.onnx ONNXRuntime=1.10.0 0.8G 5.354s ch_PP-OCRv2_det_infer.onnx openvino=2022.1.0 3.225G 2.53s ch_PP-OCRv2_det_infer.xml FP32 \u200b\u52a8\u6001\u56fe\u200b openvino=2022.1.0 3.175G 2.0455s"},{"location":"blog/2022/09/25/openvino-gpu%E6%8E%A8%E7%90%86/#openvinoonnxruntime_1","title":"OpenVINO\u200b\u4e0e\u200bONNXRuntime\u200b\u63a8\u7406\u200b\u4ee3\u7801\u200b\u5199\u6cd5\u200b\u5bf9\u6bd4","text":"

    Example

    \u200b\u4ee5\u200bch_ppocr_mobile_v2_det\u200b\u4e2d\u200b\u63a8\u7406\u200b\u4ee3\u7801\u200b\u4e3a\u200b\u4f8b\u5b50\u200b

    "},{"location":"blog/2022/09/25/openvino-gpu%E6%8E%A8%E7%90%86/#onnxruntime","title":"ONNXRuntime","text":"
    import onnxruntime\n\n# \u200b\u58f0\u660e\u200b\nsess_opt = onnxruntime.SessionOptions()\nsess_opt.log_severity_level = 4\nsess_opt.enable_cpu_mem_arena = False\nsession = onnxruntime.InferenceSession(det_model_path, sess_opt)\ninput_name = session.get_inputs()[0].name\noutput_name = session.get_outputs()[0].name\n\n# \u200b\u63a8\u7406\u200b\npreds = session.run([output_name], {input_name: img})\n
    "},{"location":"blog/2022/09/25/openvino-gpu%E6%8E%A8%E7%90%86/#openvino_1","title":"OpenVINO","text":"
    from openvino.runtime import Core\n\n# \u200b\u521d\u59cb\u5316\u200b\nie = Core()\nmodel_onnx = ie.read_model(det_model_path)\ncompile_model = ie.compile_model(model=model_onnx, device_name='CPU')\nvino_session = compile_model.create_infer_request()\n\n# \u200b\u63a8\u7406\u200b\nvino_session.infer(inputs=[img])\nvino_preds = vino_session.get_output_tensor().data\n
    "},{"location":"blog/2022/09/30/inference-summary/","title":"\u884d\u751f\u200b\u9879\u76ee\u200b(\u200b\u504f\u200b\u5de5\u7a0b\u200b)","text":""},{"location":"blog/2022/09/30/inference-summary/#rapidstructure","title":"RapidStructure \uff1a\u200b\u7248\u9762\u200b\u5206\u6790","text":"
    • \u200b\u542b\u200b\u6587\u672c\u200b\u7684\u200b\u56fe\u50cf\u200b\u65b9\u5411\u200b\u5206\u7c7b\u200b
    • \u200b\u7248\u9762\u200b\u5206\u6790\u200b
    • \u200b\u8868\u683c\u200b\u8fd8\u539f\u200b
    "},{"location":"blog/2022/09/30/inference-summary/#rapidocrserverrapidocr-httpwin32","title":"RapidOCRServer\uff1aRapidOCR HTTP\u200b\u670d\u52a1\u200b/win32\u200b\u7a0b\u5e8f\u200b/\u200b\u6613\u8bed\u8a00\u200b\u7f16\u5199","text":""},{"location":"blog/2022/09/30/inference-summary/#paddleocrmodelconvert","title":"PaddleOCRModelConvert\uff1a \u200b\u6a21\u578b\u200b\u81ea\u52a9\u200b\u8f6c\u6362","text":""},{"location":"blog/2022/09/30/inference-summary/#textdetmetric","title":"TextDetMetric\uff1a\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\u8bc4\u4f30","text":""},{"location":"blog/2022/09/30/inference-summary/#rapidocrpdfpdf","title":"RapidOCRPDF\uff1a\u200b\u89e3\u6790\u200bPDF\u200b\u6587\u4ef6","text":""},{"location":"blog/2022/09/30/inference-summary/#rapidvideocrrapidocr","title":"RapidVideOCR\uff1a\u200b\u57fa\u4e8e\u200bRapidOCR\uff0c\u200b\u63d0\u53d6\u200b\u89c6\u9891\u200b\u4e2d\u200b\u7684\u200b\u786c\u200b\u5b57\u5e55","text":""},{"location":"blog/2022/10/01/inference-summary/","title":"\u5782\u76f4\u200b\u9879\u76ee\u200b(\u200b\u504f\u200b\u5b66\u672f\u200b)","text":""},{"location":"blog/2022/10/01/inference-summary/#_1","title":"\u5f15\u8a00","text":"
    • \u200b\u4ee5\u4e0b\u200b\u51e0\u4e2a\u200b\u65b9\u5411\u200b\uff0c\u200b\u6bcf\u4e2a\u200b\u90fd\u200b\u662f\u200b\u6bd4\u8f83\u200b\u72ec\u7acb\u200b\u7684\u200b\u65b9\u5411\u200b\uff0c\u200b\u4f46\u662f\u200b\u5374\u200b\u548c\u200bOCR\u200b\u6709\u7740\u200b\u5343\u4e1d\u4e07\u7f15\u200b\u7684\u200b\u5173\u7cfb\u200b\uff0c\u200b\u5173\u4e8e\u200b\u5b83\u4eec\u200b\u7684\u200b\u8d44\u6599\u200b\u5c31\u200b\u50cf\u200b\u6563\u843d\u200b\u5728\u200b\u5929\u7a7a\u200b\u4e2d\u200b\u7684\u200b\u661f\u661f\u200b\u4e00\u822c\u200b\uff0c\u200b\u6563\u53d1\u200b\u7740\u200b\u5fae\u5f31\u200b\u7684\u200b\u5149\u8292\u200b\uff0c\u200b\u8fd9\u91cc\u200b\u8981\u200b\u505a\u200b\u7684\u200b\u5c31\u662f\u200b\u5c06\u200b\u8fd9\u4e9b\u200b\u70b9\u70b9\u200b\u5149\u8292\u200b\u805a\u96c6\u200b\u8d77\u6765\u200b\u3002
    • \u200b\u8fd9\u91cc\u200b\u5c06\u4f1a\u200b\u6c47\u603b\u200b\u51fa\u200b\u4ee5\u4e0b\u200b\u51e0\u4e2a\u200bOCR\u200b\u5468\u8fb9\u200b\u9879\u76ee\u200b\u7684\u200b\u4e00\u4e9b\u200b\u6587\u6863\u200b\u548c\u200b\u8d44\u6e90\u200b\uff0c\u200b\u5305\u62ec\u200b\u5b66\u672f\u200b\u52a8\u6001\u200b\u548c\u200b\u4e00\u4e9b\u200b\u5de5\u7a0b\u5316\u200b\u4ee3\u7801\u200b\u3002
    • \u200b\u6b22\u8fce\u200b\u5404\u4f4d\u200b\u5c0f\u4f19\u4f34\u200b\u63d0\u4f9b\u200bPR\u3002
    "},{"location":"blog/2022/10/01/inference-summary/#visual-text-rendering","title":"Visual Text Rendering","text":"
    • Glyph-ByT5: A Customized Text Encoder for Accurate Visual Text Rendering
    "},{"location":"blog/2022/10/01/inference-summary/#_2","title":"\u9605\u8bfb\u200b\u5e8f\u5217\u200b\u62bd\u53d6","text":"

    \u200b\u6570\u636e\u200b\u96c6\u200b\uff1a

    • ReadingBank
    "},{"location":"blog/2022/10/01/inference-summary/#_3","title":"\u624b\u5199\u4f53\u200b\u8bc6\u522b","text":"

    TODO

    "},{"location":"blog/2022/10/01/inference-summary/#_4","title":"\u624b\u5199\u4f53\u200b\u516c\u5f0f\u200b\u8bc6\u522b","text":"

    TODO

    "},{"location":"blog/2022/10/01/inference-summary/#_5","title":"\u516c\u5f0f\u200b\u8bc6\u522b","text":"

    TODO

    "},{"location":"blog/2022/10/01/inference-summary/#_6","title":"\u516c\u5f0f\u200b\u68c0\u6d4b","text":"

    \u200b\u56fe\u50cf\u200b\u4e2d\u200b\u516c\u5f0f\u200b\u68c0\u6d4b\u200b\u9700\u6c42\u200b\u4e00\u822c\u200b\u51fa\u73b0\u200b\u4e8e\u200b\u6587\u6863\u200b\u5206\u6790\u200b\u548c\u200b\u8fd8\u539f\u200b\u9700\u6c42\u200b\u4e2d\u200b\u3002

    \u200b\u5355\u7eaf\u200b\u516c\u5f0f\u200b\u68c0\u6d4b\u200b\u4efb\u52a1\u200b\u5305\u62ec\u200b\u5bf9\u200b\u884c\u5185\u200b\u516c\u5f0f\u200b\u548c\u200b\u884c\u95f4\u200b\u516c\u5f0f\u200b\u7684\u200b\u68c0\u6d4b\u200b\u3002\u200b\u800c\u200b\u7248\u9762\u200b\u5206\u6790\u200b\u4efb\u52a1\u200b\u4e2d\u200b\uff0c\u200b\u4ec5\u200b\u6709\u200b\u5bf9\u200b\u884c\u95f4\u200b\u516c\u5f0f\u200b\u7684\u200b\u6807\u6ce8\u200b\uff0c\u200b\u7f3a\u4e4f\u200b\u884c\u5185\u200b\u516c\u5f0f\u200b\u6807\u6ce8\u200b\u3002\u200b\u5982\u679c\u200b\u60f3\u8981\u200b\u7cbe\u7ec6\u5316\u200b\u505a\u200b\u7248\u9762\u200b\u8fd8\u539f\u200b\uff0c\u200b\u884c\u5185\u200b\u516c\u5f0f\u200b\u7684\u200b\u68c0\u6d4b\u200b\u8bc6\u522b\u200b\u5c31\u200b\u53d8\u5f97\u200b\u5c24\u4e3a\u91cd\u8981\u200b\u3002

    \u200b\u8fd9\u200b\u4e00\u5757\u200b\u7684\u200b\u5de5\u4f5c\u200b\uff0cbreezedeus\u200b\u505a\u200b\u5f97\u200b\u6bd4\u8f83\u200b\u597d\u200b\uff0c\u200b\u8be6\u60c5\u200b\u53ef\u4ee5\u200b\u53c2\u89c1\u200b\u5176\u200b\u535a\u5ba2\u200b\uff1aPix2Text (P2T) \u200b\u65b0\u7248\u200b\u516c\u5f0f\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\u3002

    \u200b\u6709\u5173\u200b\u6570\u636e\u200b\u96c6\u200b\uff1aIBEM \u200b\u548c\u200b\u4e2d\u6587\u200b CnMFD_Dataset

    "},{"location":"blog/2022/10/01/inference-summary/#_7","title":"\u53d1\u7968\u200b\u8bc6\u522b","text":"
    • CSIG 2022 Competition on Invoice Recognition and Analysis
    "},{"location":"blog/2022/10/01/inference-summary/#_8","title":"\u56fe\u50cf\u200b\u6587\u5b57\u200b\u64e6\u9664","text":"
    • CTRNet\uff1a\u200b\u56fe\u50cf\u200b\u6587\u5b57\u200b\u64e6\u9664\u200b | Demo
    "},{"location":"blog/2022/10/01/inference-summary/#_9","title":"\u6587\u6863\u200b\u589e\u5f3a","text":"
    • DocDiff\uff08Github\uff09: \u200b\u6587\u6863\u200b\u589e\u5f3a\u200b\u6a21\u578b\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u7528\u4e8e\u200b\u6587\u6863\u200b\u53bb\u6a21\u7cca\u200b\u3001\u200b\u6587\u6863\u200b\u53bb\u200b\u566a\u200b\u3001\u200b\u6587\u6863\u200b\u4e8c\u503c\u5316\u200b\u3001\u200b\u6587\u6863\u200b\u53bb\u200b\u6c34\u5370\u200b\u548c\u200b\u5370\u7ae0\u200b\u7b49\u200b\u4efb\u52a1\u200b\u3002
    "},{"location":"blog/2022/10/01/inference-summary/#_10","title":"\u6587\u6863\u200b\u56fe\u50cf\u200b\u77eb\u6b63","text":"
    • PaperEdge\uff1a\u200b\u6587\u6863\u200b\u56fe\u50cf\u200b\u77eb\u6b63\u200b | Demo
    • DocTr++ | Demo | Code
    • DocRes\uff1a \u200b\u7edf\u4e00\u200b\u6587\u6863\u200b\u56fe\u50cf\u200b\u6062\u590d\u200b\u4efb\u52a1\u200b\u7684\u200b\u5e7f\u4e49\u200b\u6a21\u578b\u200b
    "},{"location":"blog/2022/10/01/inference-summary/#_11","title":"\u7248\u9762\u200b\u5206\u6790","text":"
    • \u200b\u76f8\u5173\u200b\u8bba\u6587\u200b\u548c\u200b\u5e16\u5b50\u200b\uff1a
      • \u200b\u7248\u9762\u200b\u5206\u6790\u65b9\u6cd5\u200b\u6c47\u603b\u200b
    • \u200b\u76f8\u5173\u200b\u5de5\u7a0b\u200b\uff1a
      • PaddleOCR Layout
      • \u200b\u6d77\u5eb7\u200bDAVAR VSR

    • \u200b\u6570\u636e\u200b\u96c6\u200b\u6c47\u603b\u200b\uff1a

      • \u200b\u82f1\u6587\u7248\u200b\u9762\u200b\u5206\u6790\u200b\u6570\u636e\u200b\u96c6\u200b\uff1a

        • PubLayNet: IBM\u200b\u6784\u5efa\u200b\uff0c34\u200b\u4e07\u5f20\u200b\u56fe\u50cf\u200b\uff0c\u200b\u5206\u4e3a\u200b5\u200b\u7c7b\u200b\uff1atext, title list table figure\u3002
        • DocBank\uff1a\u200b\u5fae\u8f6f\u200b\u4e9a\u6d32\u200b\u7814\u7a76\u9662\u200b\u6784\u5efa\u200b\uff0c50\u200b\u4e07\u200b\u82f1\u6587\u200b\u6587\u6863\u200b\u56fe\u50cf\u200b\uff0c\u200b\u5206\u4e3a\u200b12\u200b\u7c7b\u200b\uff1a\u200b\u6458\u8981\u200b\u3001\u200b\u4f5c\u8005\u200b\u3001\u200b\u6807\u9898\u200b\u3001\u200b\u516c\u5f0f\u200b\u3001\u200b\u56fe\u5f62\u200b\u3001\u200b\u9875\u811a\u200b\u3001\u200b\u5217\u8868\u200b\u3001\u200b\u6bb5\u843d\u200b\u3001\u200b\u53c2\u8003\u200b\u3001\u200b\u8282\u200b\u6807\u9898\u200b\u3001\u200b\u8868\u683c\u200b\u548c\u200b\u6587\u7ae0\u200b\u6807\u9898\u200b\u3002
        • D4LA: \u200b\u963f\u91cc\u200b\u901a\u4e49\u200b\u5b9e\u9a8c\u5ba4\u200b\u6784\u5efa\u200b\uff0c11092\u200b\u5f20\u200b\u56fe\u50cf\u200b\uff0c12\u200b\u4e2a\u200b\u6587\u6863\u200b\u79cd\u7c7b\u200b\uff0c27\u200b\u4e2a\u200b\u7c7b\u522b\u200b\uff0c\u200b\u624b\u5de5\u200b\u6807\u6ce8\u200b\u3002\u200b\u8be6\u60c5\u200b\u53ef\u200b\u53c2\u89c1\u200b\u8bba\u6587\u200bVision Grid Transformer for Document Layout Analysis

      • \u200b\u4e2d\u6587\u7248\u200b\u9762\u200b\u5206\u6790\u200b\u6570\u636e\u200b\u96c6\u200b\uff1a

        • CDLA\uff1a\u200b\u4e2d\u6587\u200b\u6587\u6863\u200b\u7248\u9762\u200b\u5206\u6790\u200b\u6570\u636e\u200b\u96c6\u200b\uff0c\u200b\u9762\u5411\u200b\u4e2d\u6587\u200b\u6587\u732e\u200b\u7c7b\u200b\uff08\u200b\u8bba\u6587\u200b\uff09\u200b\u573a\u666f\u200b\uff0c\u200b\u603b\u5171\u200b6000\u200b\u5f20\u200b\uff085000\u200b\u8bad\u7ec3\u200b\uff0c1000\u200b\u6d4b\u8bd5\u200b\uff09\uff0c\u200b\u5206\u4e3a\u200b10\u200b\u7c7b\u200b\uff1a\u200b\u6b63\u6587\u200b\u3001\u200b\u6807\u9898\u200b\u3001\u200b\u56fe\u7247\u200b\u3001\u200b\u56fe\u7247\u200b\u6807\u9898\u200b\u3001\u200b\u8868\u683c\u200b\u3001\u200b\u8868\u683c\u200b\u6807\u9898\u200b\u3001\u200b\u9875\u7709\u200b\u3001\u200b\u9875\u811a\u200b\u3001\u200b\u6ce8\u91ca\u200b\u548c\u200b\u516c\u5f0f\u200b\u3002
    "},{"location":"blog/2022/10/01/inference-summary/#_12","title":"\u8868\u683c\u200b\u7ed3\u6784\u200b\u8bc6\u522b","text":"
    • table-transformer
    • \u200b\u76f8\u5173\u200b\u8bba\u6587\u200b\u548c\u200b\u5e16\u5b50\u200b\uff1a
      • OCR\u200b\u4e4b\u200b\u8868\u683c\u200b\u7ed3\u6784\u200b\u8bc6\u522b\u200b\u7efc\u8ff0\u200b
      • \u200b\u5408\u5408\u200b\u4fe1\u606f\u200b\uff1a\u200b\u8868\u683c\u200b\u8bc6\u522b\u200b\u4e0e\u200b\u5185\u5bb9\u200b\u63d0\u70bc\u200b\u6280\u672f\u200b\u7406\u89e3\u200b\u53ca\u200b\u7814\u53d1\u200b\u8d8b\u52bf\u200b
      • \u200b\u8bba\u6587\u200b\u9605\u8bfb\u200b: \uff08ICDAR2021 \u200b\u6d77\u5eb7\u200b\u5a01\u89c6\u200b\uff09LGPMA\uff08\u200b\u8868\u683c\u200b\u8bc6\u522b\u200b\u7b97\u6cd5\u200b\uff09\u200b\u53ca\u200b\u5b98\u65b9\u200b\u6e90\u7801\u200b\u5bf9\u5e94\u200b\u89e3\u8bfb\u200b
    • \u200b\u76f8\u5173\u200b\u5de5\u7a0b\u200b\uff1a
      • \u200b\u6d77\u5eb7\u200b\u5b98\u65b9\u200bLGPMA\u200b\u6e90\u7801\u200b
      • LGPMA Inference
      • PaddleOCR Table
    • \u200b\u6570\u636e\u200b\u96c6\u200b\u6c47\u603b\u200b\uff1a
      • \u200b\u82f1\u6587\u200b\u8868\u683c\u200b\u8bc6\u522b\u200b\u6570\u636e\u200b\u96c6\u200b\uff1a
        • PubTabNet: IBM\u200b\u6784\u5efa\u200b\uff0c568k+\u200b\u6587\u6863\u200b\u56fe\u50cf\u200b\u6570\u636e\u200b\uff0c\u200b\u5305\u62ec\u200b\u8868\u683c\u200b\u56fe\u50cf\u200b\u548c\u200b\u5bf9\u5e94\u200b\u7684\u200bHTML\u200b\u6807\u6ce8\u200b\u3002
    "},{"location":"blog/2022/10/01/inference-summary/#ocr","title":"\u89c6\u9891\u200bOCR","text":"
    • \u200b\u76f8\u5173\u200b\u8bba\u6587\u200b\u548c\u200b\u5e16\u5b50\u200b\uff1a
      • \u3010NeurIPS2021\u3011A Bilingual, OpenWorld Video Text Dataset and End-to-end Video Text Spotter with Transformer | \u200b\u535a\u5ba2\u200b\u89e3\u8bfb\u200b
      • \u3010ACM MM 2019\u3011You only recognize once: Towards fast video text spotting
      • VimTS: A Unified Video and Image Text Spotter for Enhancing the Cross-domain Generalization
    • \u200b\u76f8\u5173\u200b\u5de5\u7a0b\u200b\uff1a
      • video-subtitle-extractor: \u200b\u4e00\u6b3e\u200b\u5c06\u200b\u89c6\u9891\u200b\u4e2d\u200b\u7684\u200b\u786c\u200b\u5b57\u5e55\u200b\u63d0\u53d6\u200b\u4e3a\u200b\u5916\u6302\u5b57\u5e55\u200b\u6587\u4ef6\u200b(srt\u200b\u683c\u5f0f\u200b)\u200b\u7684\u200b\u8f6f\u4ef6\u200b
      • RapidVideOCR: \u200b\u63d0\u53d6\u200b\u89c6\u9891\u200b\u4e2d\u786c\u200b\u5b57\u5e55\u200b
    • \u200b\u6570\u636e\u200b\u96c6\u200b\u6c47\u603b\u200b\uff1a
      • BOVText: A Large-Scale, Bilingual Open World Dataset for Video Text Spotting: \u200b\u5feb\u624b\u200b\u79d1\u6280\u200b\u3001\u200b\u6d59\u6c5f\u5927\u5b66\u200b\u548c\u200b\u5317\u4eac\u90ae\u7535\u5927\u5b66\u200b\u5408\u4f5c\u200b\u63d0\u51fa\u200b\uff0c\u200b\u5927\u89c4\u6a21\u200b\u53cc\u8bed\u200b\u5f00\u653e\u200b\u573a\u666f\u200b\u4e0b\u200b\u7684\u200b\u89c6\u9891\u200b\u6587\u672c\u200b\u57fa\u51c6\u200b\u6570\u636e\u200b\u96c6\u200b\uff0c\u200b\u8be5\u200b\u6570\u636e\u200b\u96c6\u200b\u4e3b\u8981\u200b\u63d0\u4f9b\u200b\u4e86\u200b2000+\u200b\u89c6\u9891\u200b\uff0c1,750,000\u200b\u5e27\u200b\u5f00\u653e\u200b\u89c6\u9891\u200b\u573a\u666f\u200b\u7684\u200b\u89c6\u9891\u200b\u3002\u200b\u540c\u65f6\u200b\uff0c\u200b\u8fd8\u200b\u63d0\u4f9b\u200b\u4e86\u200b\u4e30\u5bcc\u200b\u7684\u200b\u6807\u6ce8\u200b\u7c7b\u578b\u200b\uff08\u200b\u6807\u9898\u200b\u3001\u200b\u5b57\u5e55\u200b\u3001\u200b\u573a\u666f\u200b\u6587\u672c\u200b\u7b49\u200b\uff09\u3002\u200b\u8be5\u200b\u6570\u636e\u200b\u96c6\u200b\u652f\u6301\u200b\u56db\u4e2a\u200b\u4efb\u52a1\u200b\uff1a\u200b\u89c6\u9891\u200b\u5e27\u200b\u68c0\u6d4b\u200b\u3001\u200b\u89c6\u9891\u200b\u5e27\u200b\u8bc6\u522b\u200b\u3001\u200b\u89c6\u9891\u200b\u6587\u672c\u200b\u8ddf\u8e2a\u200b\u548c\u200b\u7aef\u200b\u5230\u200b\u7aef\u200b\u89c6\u9891\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u3002
    "},{"location":"blog/2022/10/01/inference-summary/#ocr_1","title":"\u5361\u8bc1\u200bOCR","text":"
    • \u200b\u76f8\u5173\u200b\u8bba\u6587\u200b\u548c\u200b\u5e16\u5b50\u200b\uff1a
    • \u200b\u76f8\u5173\u200b\u5de5\u7a0b\u200b\uff1a
      • fake_certificate_generator: \u200b\u5047\u200b\u7684\u200b\u8bc1\u4ef6\u200b\u5408\u6210\u5668\u200b\uff0c\u200b\u5305\u62ec\u200b\u8eab\u4efd\u8bc1\u200b\u3001\u200b\u9a7e\u9a76\u8bc1\u200b\u3001\u200b\u8425\u4e1a\u6267\u7167\u200b\u3002
    • \u200b\u6570\u636e\u200b\u96c6\u200b\u6c47\u603b\u200b\uff1a
      • \u200b\u6682\u65e0\u200b\uff0c\u200b\u4e00\u822c\u200b\u8fd9\u200b\u7c7b\u200b\u6570\u636e\u200b\u8f83\u4e3a\u200b\u654f\u611f\u200b\uff0c\u200b\u901a\u5e38\u200b\u90fd\u200b\u5408\u6210\u200b\u5047\u200b\u6570\u636e\u200b\u6765\u200b\u4f7f\u7528\u200b\u3002
    "},{"location":"blog/2022/10/01/inference-summary/#ocr_2","title":"\u5370\u7ae0\u200bOCR","text":"
    • \u200b\u76f8\u5173\u200b\u8bba\u6587\u200b\u548c\u200b\u5e16\u5b50\u200b\uff1a
      • \u200b\u6765\u200b\u4e5f\u200b\u667a\u80fd\u200b\u6587\u6863\u200b\u5904\u7406\u200b\u7cfb\u7edf\u200b\u4e2d\u200b\u7684\u200b\u5370\u7ae0\u200b\u8bc6\u522b\u200b\u5b9e\u8df5\u200b
      • \u3010\u200b\u6280\u672f\u200b\u65b0\u200b\u8d8b\u52bf\u200b\u3011\u200b\u5408\u5408\u200b\u4fe1\u606f\u200b\uff1a\u200b\u590d\u6742\u200b\u73af\u5883\u200b\u4e0b\u200bocr\u200b\u4e0e\u200b\u5370\u7ae0\u200b\u8bc6\u522b\u200b\u6280\u672f\u200b\u7406\u89e3\u200b\u53ca\u200b\u7814\u53d1\u200b\u8d8b\u52bf\u200b
      • \u200b\u57fa\u4e8e\u200b\u6587\u5b57\u200b\u5206\u5272\u200b\u7684\u200b\u5370\u7ae0\u200b\u8bc6\u522b\u200b\u6280\u672f\u200b
    • \u200b\u76f8\u5173\u200b\u5de5\u7a0b\u200b\uff1a
      • JS\u200b\u751f\u6210\u200b\u5370\u7ae0\u200b
      • Python\u200b\u7ed8\u5236\u200b\u900f\u660e\u200b\u80cc\u666f\u200b\u5370\u7ae0\u200b
      • \u200b\u5728\u7ebf\u200b\u5370\u7ae0\u200b\u5408\u6210\u200b\u5927\u5168\u200b\u7f51\u7ad9\u200b
      • TrOCR-Seal-Recognition
    • \u200b\u6570\u636e\u200b\u96c6\u200b\u6c47\u603b\u200b\uff1a
      • DocDiff
    "},{"location":"install_usage/api/RapidOCR/","title":"RapidOCR","text":"

    Info

    \u200b\u8be5\u200b\u90e8\u5206\u200b\u4ee5\u200brapidocr_onnxruntime\u200b\u5e93\u4e0b\u200bRapidOCR\u200b\u4e3a\u200b\u4f8b\u4f5c\u200b\u8bb2\u89e3\u200b\uff0c\u200b\u5176\u4ed6\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u4e0e\u200b\u8fd9\u4e2a\u200b\u57fa\u672c\u200b\u7c7b\u4f3c\u200b\uff0c\u200b\u8bf7\u200b\u79fb\u6b65\u200b\u5177\u4f53\u200b\u6e90\u7801\u200b\u67e5\u770b\u200b\u3002

    "},{"location":"install_usage/api/RapidOCR/#__init__-source","title":"__init__ [SOURCE]","text":"
    def __init__(self, text_score: float = 0.5,\n    print_verbose: bool = False,\n    min_height: int = 30,\n    width_height_ratio: float = 8,\n    det_use_cuda: bool = False,\n    det_use_dml: bool = False,\n    det_model_path: Optional[str] = None,\n    det_limit_side_len: float = 736,\n    det_limit_type: str = \"min\",\n    det_thresh: float = 0.3,\n    det_box_thresh: float = 0.5,\n    det_unclip_ratio: float = 1.6,\n    det_donot_use_dilation: bool = False,\n    det_score_mode: str = \"fast\",\n    cls_use_cuda: bool = False,\n    cls_use_dml: bool = False,\n    cls_model_path: Optional[str] = None,\n    cls_image_shape: List[int] = [3, 48, 192],\n    cls_label_list: List[str] = [\"0\", \"180\"],\n    cls_batch_num: int = 6,\n    cls_thresh: float = 0.9,\n    rec_use_cuda: bool = False,\n    rec_use_dml: bool = False,\n    rec_model_path: Optional[str] = None,\n    rec_img_shape: List[int] = [3, 48, 320],\n    rec_batch_num: int = 6,\n    intra_op_num_threads: int = -1,\n    inter_op_num_threads: int = -1,\n):\n    pass\n
    "},{"location":"install_usage/api/RapidOCR/#_1","title":"\u53c2\u6570","text":"
    • text_score (float, optional): \u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u7ed3\u679c\u200b\u7f6e\u4fe1\u5ea6\u200b\uff0c\u200b\u503c\u8d8a\u200b\u5927\u200b\uff0c\u200b\u628a\u63e1\u200b\u8d8a\u5927\u200b\u3002\u200b\u53d6\u503c\u200b\u8303\u56f4\u200b\uff1a[0, 1], \u200b\u9ed8\u8ba4\u503c\u200b\u662f\u200b0.5\u3002
    • print_verbose (bool, optional): \u200b\u662f\u5426\u200b\u6253\u5370\u200b\u5404\u4e2a\u200b\u90e8\u5206\u200b\u8017\u65f6\u200b\u4fe1\u606f\u200b\u3002 \u200b\u9ed8\u8ba4\u200b\u4e3a\u200bFalse\u3002
    • min_height (int, optional): \u200b\u56fe\u50cf\u200b\u6700\u5c0f\u200b\u9ad8\u5ea6\u200b\uff08\u200b\u5355\u4f4d\u200b\u662f\u200b\u50cf\u7d20\u200b\uff09\uff0c\u200b\u4f4e\u4e8e\u200b\u8fd9\u4e2a\u200b\u503c\u200b\uff0c\u200b\u4f1a\u200b\u8df3\u200b\u8fc7\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u9636\u6bb5\u200b\uff0c\u200b\u76f4\u63a5\u200b\u8fdb\u884c\u200b\u540e\u7eed\u200b\u8bc6\u522b\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b30\u3002min_height\u200b\u662f\u200b\u7528\u6765\u200b\u8fc7\u6ee4\u200b\u53ea\u6709\u200b\u4e00\u884c\u200b\u6587\u672c\u200b\u7684\u200b\u56fe\u50cf\u200b\uff08\u200b\u5982\u4e0b\u200b\u56fe\u200b\uff09\uff0c\u200b\u8fd9\u200b\u7c7b\u200b\u56fe\u50cf\u200b\u4e0d\u4f1a\u200b\u8fdb\u5165\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u5757\u200b\uff0c\u200b\u76f4\u63a5\u200b\u8fdb\u5165\u200b\u540e\u7eed\u200b\u8fc7\u7a0b\u200b\u3002

    - width_height_ratio (float, optional): \u200b\u5982\u679c\u200b\u8f93\u5165\u200b\u56fe\u50cf\u200b\u7684\u200b\u5bbd\u9ad8\u6bd4\u200b\u5927\u4e8e\u200bwidth_height_ratio\uff0c\u200b\u5219\u200b\u4f1a\u200b\u8df3\u200b\u8fc7\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\uff0c\u200b\u76f4\u63a5\u200b\u8fdb\u884c\u200b\u540e\u7eed\u200b\u8bc6\u522b\u200b\uff0c\u200b\u53d6\u503c\u200b\u4e3a\u200b-1\u200b\u65f6\u200b\uff1a\u200b\u4e0d\u7528\u200b\u8fd9\u4e2a\u200b\u53c2\u6570\u200b. \u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b8\u3002 - det_use_cuda (bool, optional): \u200b\u662f\u5426\u200b\u4f7f\u7528\u200bCUDA\u200b\u52a0\u901f\u200b\u63a8\u7406\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bFalse\u3002 - det_use_dml (bool, optional): \u200b\u662f\u5426\u200b\u4f7f\u7528\u200bDirectML\u200b\u52a0\u901f\u200b\u63a8\u7406\u200b(\u200b\u4ec5\u9650\u4e8e\u200bWindow10\u200b\u53ca\u200b\u4ee5\u4e0a\u200b)\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bFalse\u3002\u200b\u8be6\u7ec6\u200b\u53c2\u89c1\u200b \u2192 link \u3002 - det_model_path (Optional[str], optional): \u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\u8def\u5f84\u200b\uff0c\u200b\u4ec5\u9650\u4e8e\u200b\u57fa\u4e8e\u200bPaddleOCR\u200b\u8bad\u7ec3\u200b\u6240\u5f97\u200bDBNet\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bNone\u3002 - det_limit_side_len (float, optional): \u200b\u9650\u5236\u200b\u56fe\u50cf\u200b\u8fb9\u200b\u7684\u200b\u957f\u5ea6\u200b\u7684\u200b\u50cf\u7d20\u200b\u503c\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b736\u3002 - det_limit_type (str, optional): \u200b\u9650\u5236\u200b\u56fe\u50cf\u200b\u7684\u200b\u6700\u5c0f\u200b\u8fb9\u200b\u957f\u5ea6\u200b\u8fd8\u662f\u200b\u6700\u5927\u200b\u8fb9\u4e3a\u200blimit_side_len \u200b\u793a\u4f8b\u200b\u89e3\u91ca\u200b\uff1a\u200b\u5f53\u200blimit_type=min\u200b\u548c\u200blimit_side_len=736\u200b\u65f6\u200b\uff0c\u200b\u56fe\u50cf\u200b\u6700\u5c0f\u200b\u8fb9\u200b\u5c0f\u4e8e\u200b736\u200b\u65f6\u200b\uff0c\u200b\u4f1a\u200b\u5c06\u200b\u56fe\u50cf\u200b\u6700\u5c0f\u200b\u8fb9\u200b\u62c9\u4f38\u200b\u5230\u200b736\uff0c\u200b\u53e6\u4e00\u8fb9\u200b\u5219\u200b\u6309\u200b\u56fe\u50cf\u200b\u539f\u59cb\u200b\u6bd4\u4f8b\u200b\u7b49\u200b\u6bd4\u200b\u7f29\u653e\u200b\u3002 \u200b\u53d6\u503c\u200b\u8303\u56f4\u200b\u4e3a\u200b\uff1a[min, max]\uff0c\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bmin\u3002 - det_thresh (float, optional): \u200b\u56fe\u50cf\u200b\u4e2d\u200b\u6587\u5b57\u200b\u90e8\u5206\u200b\u548c\u200b\u80cc\u666f\u200b\u90e8\u5206\u200b\u5206\u5272\u200b\u9608\u503c\u200b\u3002\u200b\u503c\u8d8a\u200b\u5927\u200b\uff0c\u200b\u6587\u5b57\u200b\u90e8\u5206\u200b\u4f1a\u8d8a\u200b\u5c0f\u200b\u3002\u200b\u53d6\u503c\u200b\u8303\u56f4\u200b\uff1a[0, 1]\uff0c\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b0.3\u3002 - det_box_thresh (float, optional): \u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6240\u5f97\u200b\u6846\u200b\u662f\u5426\u200b\u4fdd\u7559\u200b\u7684\u200b\u9608\u503c\u200b\uff0c\u200b\u503c\u8d8a\u200b\u5927\u200b\uff0c\u200b\u53ec\u56de\u200b\u7387\u8d8a\u200b\u4f4e\u200b\u3002\u200b\u53d6\u503c\u200b\u8303\u56f4\u200b\uff1a[0, 1]\uff0c\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b0.5\u3002 - det_unclip_ratio (float, optional): \u200b\u63a7\u5236\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6846\u200b\u7684\u200b\u5927\u5c0f\u200b\uff0c\u200b\u503c\u8d8a\u200b\u5927\u200b\uff0c\u200b\u68c0\u6d4b\u200b\u6846\u200b\u6574\u4f53\u200b\u8d8a\u5927\u200b\u3002\u200b\u53d6\u503c\u200b\u8303\u56f4\u200b\uff1a[1.6, 2.0]\uff0c\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b1.6\u3002 - det_donot_use_dilation (bool, optional): \u200b\u4e0d\u200b\u4f7f\u7528\u200b\u81a8\u80c0\u200b\u64cd\u4f5c\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bFalse\u3002 - det_score_mode (str, optional): \u200b\u8ba1\u7b97\u200b\u6587\u672c\u6846\u200b\u5f97\u5206\u200b\u7684\u200b\u65b9\u5f0f\u200b\u3002\u200b\u53d6\u503c\u200b\u8303\u56f4\u200b\u4e3a\u200b\uff1a[slow, fast]\uff0c\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bfast\u3002 - cls_use_cuda (bool, optional): \u200b\u662f\u5426\u200b\u4f7f\u7528\u200bCUDA\u200b\u52a0\u901f\u200b\u63a8\u7406\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bFalse\u3002 - cls_use_dml (bool, optional): \u200b\u662f\u5426\u200b\u4f7f\u7528\u200bDirectML\u200b\u52a0\u901f\u200b\u63a8\u7406\u200b(\u200b\u4ec5\u9650\u4e8e\u200bWindow10\u200b\u53ca\u200b\u4ee5\u4e0a\u200b)\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bFalse\u3002\u200b\u8be6\u7ec6\u200b\u53c2\u89c1\u200b \u2192 link \u3002 - cls_model_path (Optional[str], optional): \u200b\u6587\u672c\u200b\u884c\u200b\u65b9\u5411\u200b\u5206\u7c7b\u200b\u6a21\u578b\u200b\u8def\u5f84\u200b\uff0c\u200b\u4ec5\u9650\u4e8e\u200bPaddleOCR\u200b\u8bad\u7ec3\u200b\u6240\u5f97\u200b\u4e8c\u200b\u5206\u7c7b\u200b\u5206\u7c7b\u200b\u6a21\u578b\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bNone\u3002 - cls_image_shape (List[int], optional): \u200b\u8f93\u5165\u200b\u65b9\u5411\u200b\u5206\u7c7b\u200b\u6a21\u578b\u200b\u7684\u200b\u56fe\u50cf\u200bShape(CHW)\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b[3, 48, 192]\u3002 - cls_label_list (List[str], optional): \u200b\u65b9\u5411\u200b\u5206\u7c7b\u200b\u7684\u200b\u6807\u7b7e\u200b\uff0c0\u00b0\u200b\u6216\u8005\u200b180\u00b0\uff0c\u200b\u8be5\u200b\u53c2\u6570\u200b\u4e0d\u80fd\u200b\u52a8\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b[\"0\", \"180\"]\u3002 - cls_batch_num (int, optional): \u200b\u6279\u6b21\u200b\u63a8\u7406\u200b\u7684\u200bbatch\u200b\u5927\u5c0f\u200b\uff0c\u200b\u4e00\u822c\u200b\u91c7\u7528\u200b\u9ed8\u8ba4\u503c\u200b\u5373\u53ef\u200b\uff0c\u200b\u592a\u5927\u200b\u5e76\u200b\u6ca1\u6709\u200b\u660e\u663e\u200b\u63d0\u901f\u200b\uff0c\u200b\u6548\u679c\u200b\u8fd8\u200b\u53ef\u80fd\u200b\u4f1a\u5dee\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b6\u3002 - cls_thresh (float, optional): \u200b\u65b9\u5411\u200b\u5206\u7c7b\u200b\u7ed3\u679c\u200b\u7684\u200b\u7f6e\u4fe1\u5ea6\u200b\u3002\u200b\u53d6\u503c\u200b\u8303\u56f4\u200b\uff1a[0, 1]\uff0c\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b0.9\u3002 - rec_use_cuda (bool, optional): \u200b\u662f\u5426\u200b\u4f7f\u7528\u200bCUDA\u200b\u52a0\u901f\u200b\u63a8\u7406\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bFalse\u3002 - rec_use_dml (bool, optional): \u200b\u662f\u5426\u200b\u4f7f\u7528\u200bDirectML\u200b\u52a0\u901f\u200b\u63a8\u7406\u200b(\u200b\u4ec5\u9650\u4e8e\u200bWindow10\u200b\u53ca\u200b\u4ee5\u4e0a\u200b)\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bFalse\u3002\u200b\u8be6\u7ec6\u200b\u53c2\u89c1\u200b \u2192 link \u3002 - rec_model_path (Optional[str], optional): \u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u8def\u5f84\u200b\uff0c\u200b\u4ec5\u9650\u4e8e\u200bPaddleOCR\u200b\u8bad\u7ec3\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bNone\u3002 - rec_img_shape (List[int], optional): \u200b\u8f93\u5165\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u7684\u200b\u56fe\u50cf\u200bShape(CHW)\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b[3, 48, 320]\u3002 - rec_batch_num (int, optional): \u200b\u6279\u6b21\u200b\u63a8\u7406\u200b\u7684\u200bbatch\u200b\u5927\u5c0f\u200b\uff0c\u200b\u4e00\u822c\u200b\u91c7\u7528\u200b\u9ed8\u8ba4\u503c\u200b\u5373\u53ef\u200b\uff0c\u200b\u592a\u5927\u200b\u5e76\u200b\u6ca1\u6709\u200b\u660e\u663e\u200b\u63d0\u901f\u200b\uff0c\u200b\u6548\u679c\u200b\u8fd8\u200b\u53ef\u80fd\u200b\u4f1a\u5dee\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b6\u3002 - intra_op_num_threads (int, optional): \u200b\u53c2\u89c1\u200bdocs\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b-1. - inter_op_num_threads (int, optional): \u200b\u53c2\u89c1\u200bdocs\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200b-1.

    "},{"location":"install_usage/api/RapidOCR/#_2","title":"\u4f7f\u7528\u200b\u793a\u4f8b","text":"
    from pathlib import Path\n\nfrom rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR(text_score=0.6, det_use_cuda=False)\n\nimg_path = Path('tests/test_files/ch_en_num.jpg')\nresult, elapse = engine(img_path)\nprint(result)\nprint(elapse)\n
    "},{"location":"install_usage/api/RapidOCR/#__call__-source","title":"__call__ [SOURCE]","text":"
    def __call__(\n    self,\n    img_content: Union[str, np.ndarray, bytes, Path],\n    use_det: Optional[bool] = None,\n    use_cls: Optional[bool] = None,\n    use_rec: Optional[bool] = None,\n    **kwargs,\n) -> Tuple[Optional[List[List[Union[Any, str]]]], Optional[List[float]]]:\n    pass\n
    "},{"location":"install_usage/api/RapidOCR/#_3","title":"\u53c2\u6570","text":"
    • img_content (Union[str, np.ndarray, bytes, Path]): \u200b\u56fe\u50cf\u200b\u5185\u5bb9\u200b\u3002
    • use_det (Optional[bool], optional): \u200b\u662f\u5426\u200b\u4f7f\u7528\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\uff0c\u200b\u5f53\u4e3a\u200bNone\u200b\u65f6\u200b\uff0c\u200b\u9ed8\u8ba4\u200b\u4f7f\u7528\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bNone\u3002
    • use_cls (Optional[bool], optional): \u200b\u662f\u5426\u200b\u4f7f\u7528\u200b\u6587\u672c\u200b\u884c\u200b\u65b9\u5411\u200b\u5206\u7c7b\u200b\u6a21\u578b\u200b\uff0c\u200b\u5f53\u4e3a\u200bNone\u200b\u65f6\u200b\uff0c\u200b\u9ed8\u8ba4\u200b\u4f7f\u7528\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bNone\u3002
    • use_rec (Optional[bool], optional): \u200b\u662f\u5426\u200b\u4f7f\u7528\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\uff0c\u200b\u5f53\u4e3a\u200bNone\u200b\u65f6\u200b\uff0c\u200b\u9ed8\u8ba4\u200b\u4f7f\u7528\u200b\u3002\u200b\u9ed8\u8ba4\u503c\u200b\u4e3a\u200bNone\u3002
    "},{"location":"install_usage/api/RapidOCR/#_4","title":"\u8f93\u5165","text":"

    \u200b\u786e\u4fdd\u200b\u8f93\u5165\u200b\u6a21\u578b\u200b\u524d\u200b\u7684\u200b\u56fe\u50cf\u200b\u901a\u9053\u200b\u987a\u5e8f\u200b\u4e3a\u200bBGR\u3002\u200b\u5f53\u524d\u200bLoadImage\u200b\u7c7b\u200b\u5185\u90e8\u200b\u5df2\u7ecf\u200b\u5bf9\u6b64\u200b\u505a\u200b\u4e86\u200b\u5904\u7406\u200b\uff0c\u200b\u53c2\u8003\u200b\u4e0b\u9762\u200b\u5199\u6cd5\u200b\u5373\u53ef\u200b\u6b63\u5e38\u200b\u4f7f\u7528\u200b\u3002\u200b\u652f\u6301\u200b4\u200b\u79cd\u200b\u8f93\u5165\u200b\u7c7b\u578b\u200b\uff1aUnion[str, np.ndarray, bytes, Path, PIL.Image.Image]

    strnp.ndarrayPIL.Image.ImageBytesPath 
    from rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\n\nimg_path = 'tests/test_files/ch_en_num.jpg'\nresult, elapse = engine(img_path)\nprint(result)\nprint(elapse)\n
    import cv2\nfrom rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\nimg = cv2.imread('tests/test_files/ch_en_num.jpg')\nresult, elapse = engine(img)\nprint(result)\nprint(elapse)\n
    from PIL import Image\nfrom rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\nimg = Image.open('tests/test_files/ch_en_num.jpg')\nresult, elapse = engine(img)\nprint(result)\nprint(elapse)\n
    from rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\n\nimg_path = 'tests/test_files/ch_en_num.jpg'\nwith open(img_path, 'rb') as f:\n    img = f.read()\nresult, elapse = engine(img)\nprint(result)\nprint(elapse)\n
    from pathlib import Path\n\nfrom rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\n\nimg_path = Path('tests/test_files/ch_en_num.jpg')\nresult, elapse = engine(img_path)\nprint(result)\nprint(elapse)\n
    "},{"location":"install_usage/api/RapidOCR/#_5","title":"\u8f93\u51fa","text":"

    RapidOCR\u200b\u5728\u200b\u8c03\u7528\u200b\u65f6\u200b\uff0c\u200b\u6709\u200b\u4e09\u4e2a\u200b\u53c2\u6570\u200buse_det | use_cls | use_rec\uff0c\u200b\u53ef\u4ee5\u200b\u63a7\u5236\u200b\u662f\u5426\u200b\u4f7f\u7528\u200b\u68c0\u6d4b\u200b\u3001\u200b\u65b9\u5411\u200b\u5206\u7c7b\u200b\u548c\u200b\u8bc6\u522b\u200b\u8fd9\u4e09\u200b\u90e8\u5206\u200b\uff0c\u200b\u4e0d\u540c\u200b\u7684\u200b\u53c2\u6570\u200b\u51b3\u5b9a\u200b\u4e86\u200b\u4e0d\u540c\u200b\u7684\u200b\u8f93\u51fa\u200b\u3002

    \u200b\u5982\u679c\u200b\u56fe\u50cf\u200b\u4e2d\u672a\u200b\u68c0\u6d4b\u200b\u5230\u200b\u6709\u6548\u200b\u6587\u5b57\u200b\u4fe1\u606f\u200b\uff0c\u200b\u5219\u200b\u8fd4\u56de\u200bTuple[None, None]\u3002\u200b\u8be6\u7ec6\u200b\u642d\u914d\u200b\u5982\u4e0b\u200b\uff1a

    \u200b\u53ea\u6709\u200b\u68c0\u6d4b\u200b\u53ea\u6709\u200b\u5206\u7c7b\u200b\u53ea\u6709\u200b\u8bc6\u522b\u200b\u68c0\u6d4b\u200b + \u200b\u8bc6\u522b\u200b\u5206\u7c7b\u200b + \u200b\u8bc6\u522b\u200b\u68c0\u6d4b\u200b + \u200b\u5206\u7c7b\u200b + \u200b\u8bc6\u522b\u200b 
    from rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\n\nimg_path = 'tests/test_files/ch_en_num.jpg'\nresult, elapse = engine(img_path, use_det=True, use_cls=False, use_rec=False)\nprint(result)\nprint(elapse)\n

    \u200b\u8fd4\u56de\u503c\u200bresult: List[List[float]] (\u200b\u6bcf\u4e2a\u200b\u6846\u200b\u7684\u200b\u5750\u6807\u200b[\u200b\u5de6\u200b\u4e0a\u200b, \u200b\u53f3\u200b\u4e0a\u200b, \u200b\u53f3\u200b\u4e0b\u200b, \u200b\u5de6\u200b\u4e0b\u200b]) 

    [\n    [[5.0, 2.0], [322.0, 9.0], [319.0, 103.0], [3.0, 96.0]],\n    [[70.0, 98.0], [252.0, 97.0], [252.0, 125.0], [70.0, 126.0]],\n    ...\n]\n

    from rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\n\nimg_path = 'tests/test_files/ch_en_num.jpg'\nresult, elapse = engine(img_path, use_det=False, use_cls=True, use_rec=False)\nprint(result)\nprint(elapse)\n
    \u200b\u8fd4\u56de\u503c\u200bresult: List[List[str, float]] ([\u200b\u65b9\u5411\u200b0\u200b\u6216\u200b180, \u200b\u7f6e\u4fe1\u5ea6\u200b]) 
    [\n    ['0', 0.9998784],\n    ...\n]\n

    from rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\n\nimg_path = 'tests/test_files/ch_en_num.jpg'\nresult, elapse = engine(img_path, use_det=False, use_cls=False, use_rec=True)\nprint(result)\nprint(elapse)\n

    \u200b\u8fd4\u56de\u503c\u200bresult: List[List[str, float]] ([\u200b\u8bc6\u522b\u200b\u7684\u200b\u6587\u672c\u200b, \u200b\u7f6e\u4fe1\u5ea6\u200b]) 

    [\n    ['\u200b\u97e9\u56fd\u200b\u5c0f\u9986\u200b', 0.7992169380187988],\n    ...\n]\n

    from rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\n\nimg_path = 'tests/test_files/ch_en_num.jpg'\nresult, elapse = engine(img_path, use_det=True, use_cls=False, use_rec=True)\nprint(result)\nprint(elapse)\n
    \u200b\u8fd4\u56de\u503c\u200bresult: List[List[float], str, float] ([[\u200b\u5de6\u200b\u4e0a\u200b, \u200b\u53f3\u200b\u4e0a\u200b, \u200b\u53f3\u200b\u4e0b\u200b, \u200b\u5de6\u200b\u4e0b\u200b], \u200b\u6587\u672c\u200b\u5185\u5bb9\u200b, \u200b\u7f6e\u4fe1\u5ea6\u200b]) 
    [\n    [[[9.0, 2.0], [321.0, 11.0], [318.0, 102.0], [6.0, 93.0]], '\u200b\u6b63\u54c1\u200b\u4fc3\u9500\u200b', '0.7986101984977723'],\n    [[[70.0, 98.0], [251.0, 98.0], [251.0, 125.0], [70.0, 125.0]], '\u200b\u5927\u200b\u6876\u88c5\u200b\u66f4\u200b\u5212\u7b97\u200b', '0.7368737288883754'],\n    ...\n]\n

    from rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\n\nimg_path = 'tests/test_files/ch_en_num.jpg'\nresult, elapse = engine(img_path, use_det=False, use_cls=True, use_rec=True)\nprint(result)\nprint(elapse)\n

    \u200b\u8fd4\u56de\u503c\u200bresult: List[List[str, float]] ([\u200b\u8bc6\u522b\u200b\u7684\u200b\u6587\u672c\u200b, \u200b\u7f6e\u4fe1\u5ea6\u200b]) 

    [\n    ['\u200b\u97e9\u56fd\u200b\u5c0f\u9986\u200b', 0.7992169380187988],\n    ...\n]\n

    from rapidocr_onnxruntime import RapidOCR\n\nengine = RapidOCR()\n\nimg_path = 'tests/test_files/ch_en_num.jpg'\n\n# \u200b\u9ed8\u8ba4\u200b\u90fd\u200b\u4e3a\u200bTrue\nresult, elapse = engine(img_path, use_det=True, use_cls=True, use_rec=True)\nprint(result)\nprint(elapse)\n

    \u200b\u8fd4\u56de\u503c\u200bresult: List[List[float], str, float] ([[\u200b\u5de6\u200b\u4e0a\u200b, \u200b\u53f3\u200b\u4e0a\u200b, \u200b\u53f3\u200b\u4e0b\u200b, \u200b\u5de6\u200b\u4e0b\u200b], \u200b\u6587\u672c\u200b\u5185\u5bb9\u200b, \u200b\u7f6e\u4fe1\u5ea6\u200b]) 

    [\n    [[[9.0, 2.0], [321.0, 11.0], [318.0, 102.0], [6.0, 93.0]], '\u200b\u6b63\u54c1\u200b\u4fc3\u9500\u200b', '0.7986101984977723'],\n    [[[70.0, 98.0], [251.0, 98.0], [251.0, 125.0], [70.0, 125.0]], '\u200b\u5927\u200b\u6876\u88c5\u200b\u66f4\u200b\u5212\u7b97\u200b', '0.7368737288883754'],\n    ...\n]\n

    "},{"location":"install_usage/api/VisRes/","title":"VisRes","text":""},{"location":"install_usage/api/VisRes/#__init__-source","title":"__init__ [SOURCE]","text":"
    def __init__(self, text_score: float = 0.5):\n    pass\n
    "},{"location":"install_usage/api/VisRes/#_1","title":"\u53c2\u6570","text":"
    • text_score (float, optional): \u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u7ed3\u679c\u200b\u7f6e\u4fe1\u5ea6\u200b\uff0c\u200b\u503c\u8d8a\u200b\u5927\u200b\uff0c\u200b\u628a\u63e1\u200b\u8d8a\u5927\u200b\u3002\u200b\u53d6\u503c\u200b\u8303\u56f4\u200b\uff1a[0, 1], \u200b\u9ed8\u8ba4\u503c\u200b\u662f\u200b0.5\u3002
    "},{"location":"install_usage/api/VisRes/#__call__-source","title":"__call__ [SOURCE]","text":"
    def __call__(\n    self,\n    img_content: Union[str, np.ndarray, bytes, Path, Image.Image],\n    dt_boxes: np.ndarray,\n    txts: Optional[Union[List[str], Tuple[str]]] = None,\n    scores: Optional[Tuple[float]] = None,\n    font_path: Optional[str] = None,\n) -> np.ndarray:\n    pass\n
    "},{"location":"install_usage/api/VisRes/#_2","title":"\u53c2\u6570","text":"
    • img_content (Union[str, np.ndarray, bytes, Path, Image.Image]): \u200b\u8f93\u5165\u200b\u56fe\u50cf\u200b\u3002
    • dt_boxes (np.ndarray): \u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6240\u5f97\u200b\u6587\u672c\u6846\u200b\u3002
    • txts (Optional[Union[List[str], Tuple[str]]], optional): \u200b\u6587\u672c\u6846\u200b\u5bf9\u5e94\u200b\u7684\u200b\u6587\u672c\u200b\u5185\u5bb9\u200b\u3002\u200b\u9ed8\u8ba4\u200b\u4e3a\u200bNone\u3002
    • scores (Optional[Tuple[float]], optional): \u200b\u6587\u672c\u200b\u5185\u5bb9\u200b\u5bf9\u5e94\u200b\u7684\u200b\u7f6e\u4fe1\u5ea6\u200b\uff0c\u200b\u9ed8\u8ba4\u200b\u4e3a\u200bNone\u3002
    • font_path (Optional[str], optional): \u200b\u5b57\u4f53\u200b\u6587\u4ef6\u200b\u8def\u5f84\u200b\uff0c\u200b\u9ed8\u8ba4\u200b\u4e3a\u200bNone\u3002
    "},{"location":"install_usage/api/VisRes/#_3","title":"\u4f7f\u7528\u200b\u793a\u4f8b","text":"

    \u200b\u53ef\u89c6\u5316\u200b\u8bc6\u522b\u200b\u7ed3\u679c\u200b\u65f6\u200b\uff0c\u200b\u9700\u8981\u200b\u63d0\u4f9b\u200b\u5b57\u4f53\u200b\u6587\u4ef6\u200b\u3002\u200b\u4e0b\u8f7d\u200b\u94fe\u63a5\u200b\uff1alink\u3002

    \u200b\u53ea\u200b\u53ef\u89c6\u5316\u200b\u68c0\u6d4b\u200b\u53ef\u89c6\u5316\u200b\u68c0\u6d4b\u200b\u548c\u200b\u8bc6\u522b\u200b 
    import cv2\n\nfrom rapidocr_onnxruntime import RapidOCR, VisRes\n\nengine = RapidOCR()\nvis = VisRes()\n\nimage_path = \"tests/test_files/ch_en_num.jpg\"\nimg = cv2.imread(image_path)\n\nresult, elapse_list = engine(img)\nboxes, txts, scores = list(zip(*result))\nres = vis(img, boxes)\ncv2.imwrite(\"only_vis_det.png\", res)\n
    import cv2\n\nfrom rapidocr_onnxruntime import RapidOCR, VisRes\n\nengine = RapidOCR()\nvis = VisRes()\n\nimage_path = \"tests/test_files/ch_en_num.jpg\"\nimg = cv2.imread(image_path)\n\nresult, elapse_list = engine(img)\nboxes, txts, scores = list(zip(*result))\n\nfont_path=\"resources/fonts/FZYTK.TTF\"\nres = vis(img, boxes, txts, scores, font_path)\ncv2.imwrite(\"vis_det_rec.png\", res)\n
    "},{"location":"install_usage/rapidocr/changelog/","title":"\u66f4\u65b0\u200b\u65e5\u5fd7","text":""},{"location":"install_usage/rapidocr/changelog/#rapidocr_vino","title":"rapidocr_vino","text":""},{"location":"install_usage/rapidocr/changelog/#2024-07-11-v1323-update","title":"2024-07-11 v1.3.23 update","text":"
    • \u200b\u53d6\u6d88\u200bShapely\u200b\u7248\u672c\u200b\u9650\u5236\u200b\uff0c\u200b\u5bf9\u5e94\u200b issue #202
    "},{"location":"install_usage/rapidocr/changelog/#2024-06-28-v1322-update","title":"2024-06-28 v1.3.22 update","text":"
    • \u200b\u5bf9\u5e94\u200brapidocr_onnxruntime==1.3.23
    "},{"location":"install_usage/rapidocr/changelog/#2024-05-18-v1319-update","title":"2024-05-18 v1.3.19 update","text":"

    \u200b\u5bf9\u5e94\u200brapidocr_onnxruntime==1.3.20

    "},{"location":"install_usage/rapidocr/changelog/#rapidocr_onnxruntime","title":"rapidocr_onnxruntime","text":"

    Note

    "},{"location":"install_usage/rapidocr/changelog/#2024-05-18","title":"2024-05-18 \u200b\u901a\u77e5","text":"

    \u200b\u540e\u7eed\u200brapidocr_onnxruntime>1.3.20\u200b\u7684\u200b\u66f4\u65b0\u200b\u65e5\u200b\u5fd7\u4e0d\u5728\u6b64\u200b\u66f4\u65b0\u200b\uff0c\u200b\u53ea\u200b\u5728\u200bGithub Release\u200b\u5904\u200b\u66f4\u65b0\u200b

    "},{"location":"install_usage/rapidocr/changelog/#2024-05-15-v1319-update","title":"\ud83d\udee0\ufe0f2024-05-15 v1.3.19 update","text":"
    • \u200b\u56e0\u4e3a\u200bDirectML\u200b\u53d7\u200b\u652f\u6301\u200b\u8bbe\u5907\u200b\u9650\u5236\u200b\uff0c\u200b\u56e0\u6b64\u200b\u5c06\u200bDirectML\u200b\u4f5c\u4e3a\u200b\u4e00\u4e2a\u200b\u9009\u9879\u200b\u5199\u5165\u200b\u914d\u7f6e\u6587\u4ef6\u200b\uff0c\u200b\u9009\u62e9\u6027\u200b\u8c03\u7528\u200b
    • \u200b\u5728\u200bWindows\u200b\u5e73\u53f0\u200b\u4ecd\u7136\u200b\u6062\u590d\u200b\u5230\u200bv1.3.18\u200b\u524d\u200b\uff0c\u200b\u9ed8\u8ba4\u200b\u5b89\u88c5\u200bonnxruntime\u200b\u5e93\u200b\u3002\u200b\u5982\u200bDirectML\u200b\u53ef\u7528\u200b\uff0c\u200b\u4e14\u200b\u663e\u5f0f\u200b\u6307\u5b9a\u200b\u65f6\u200b\uff0c\u200b\u9700\u8981\u200b\u624b\u52a8\u200b\u5b89\u88c5\u200b\u3002
    • \u200b\u76f8\u5173\u200b\u8ba8\u8bba\u200b\uff1aPR #178 Discussion #175
    "},{"location":"install_usage/rapidocr/changelog/#2024-05-12-v1318-update","title":"\ud83e\uddda\ud83c\udffb\u200d\u2640\ufe0f2024-05-12 v1.3.18 update","text":"
    • Merge PR #176
    • \u200b\u652f\u6301\u200bpython 3.12
    "},{"location":"install_usage/rapidocr/changelog/#2024-04-19-v1317-update","title":"\ud83d\udd252024-04-19 v1.3.17 update","text":"
    • Merge PR
    • \u200b\u4fee\u590d\u200bissue #170
    "},{"location":"install_usage/rapidocr/changelog/#2024-04-07-v1316-update","title":"\ud83d\udcd82024-04-07 v1.3.16 update","text":"

    \u200b\u4fee\u590d\u200bissue #161

    "},{"location":"install_usage/rapidocr/changelog/#2024-03-07-v1315-update","title":"\ud83c\udf7f2024-03-07 v1.3.15 update","text":"
    • \u200b\u4fee\u590d\u200b issue #158
    • \u200b\u589e\u52a0\u200b\u4e09\u4e2a\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\uff08onnxruntime\u3001openvino\uff0cpaddlepaddle\uff09\u200b\u521d\u59cb\u5316\u200bRapidOCR\u200b\u7c7b\u200b\uff0c\u200b\u6307\u5b9a\u200b\u7ebf\u7a0b\u200b\u6570\u200b\u7684\u200b\u53c2\u6570\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2024-03-05-v1314-update","title":"\ud83c\udf822024-03-05 v1.3.14 update","text":"

    \u200b\u6dfb\u52a0\u200b\u53ef\u200b\u4f7f\u7528\u200b\u7684\u200bCPU\u200b\u6838\u5fc3\u200b\u6570\u200b\uff0c\u200b\u5305\u62ec\u200b\u4e09\u4e2a\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\uff0connxruntime/OpenVINO/PaddlePaddle

    "},{"location":"install_usage/rapidocr/changelog/#2024-02-28-v1313-update","title":"\ud83d\udd162024-02-28 v1.3.13 update","text":"
    • \u200b\u4f18\u5316\u200bLoadImage\u200b\u7c7b\u200b\uff0c\u200b\u6dfb\u52a0\u200b\u5bf9\u200b\u8f93\u5165\u200bPIL.Image.Image\u200b\u7684\u200b\u652f\u6301\u200b
    • \u200b\u4fee\u590d\u200b\u4e0d\u540c\u200b\u8f93\u5165\u200b\u7c7b\u578b\u200b\u4e0b\u200b\uff0c\u200b\u56fe\u50cf\u200b\u901a\u9053\u200b\u987a\u5e8f\u200b\u4e0d\u540c\u200b\u7684\u200b\u95ee\u9898\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2024-02-27-v1312-update","title":"\ud83c\udf492024-02-27 v1.3.12 update","text":"

    \u200b\u53ef\u89c6\u5316\u200b\u51fd\u6570\u200b\u9002\u914d\u200bPillow v9\u200b\u548c\u200bv10\u200b\u4e24\u4e2a\u200b\u7248\u672c\u200b\uff0c\u200b\u81ea\u52a8\u200b\u6839\u636e\u200b\u5404\u4e2a\u200b\u7248\u672c\u200b\u60c5\u51b5\u200b\uff0c\u200b\u6765\u200b\u9009\u62e9\u200b\u76f8\u5e94\u200b\u83b7\u5f97\u200bchar\u200b\u5927\u5c0f\u200b\u7684\u200b\u51fd\u6570\u200b

    "},{"location":"install_usage/rapidocr/changelog/#2024-02-04-v1311-update","title":"\u2665\ufe0f2024-02-04 v1.3.11 update","text":"

    Merge PR #151 by LWQ2EDU

    • \u200b\u6dfb\u52a0\u200b\u81ea\u52a8\u200bpadding\u200b\u7b56\u7565\u200b\uff1a\u200b\u5f53\u200b\u4f20\u5165\u200b\u56fe\u50cf\u200b\u5c0f\u4e8e\u200bmin_height\u200b\u6216\u8005\u200b>width_height_ratio\u200b\u65f6\u200b\uff0c\u200b\u4f1a\u200b\u89e6\u53d1\u200b\u81ea\u52a8\u200bpadding\u200b\u56fe\u50cf\u200b\uff0c\u200b\u540e\u7eed\u200b\u518d\u200b\u8fdb\u5165\u200b\u68c0\u6d4b\u200b\u3002
    • \u26a0\ufe0f\u200b\u6ce8\u610f\u200b\uff1apadding\u200b\u503c\u200b\u591a\u5c11\u200b\uff1f\u200b\u5f53\u524d\u200b\u503c\u200b\u662f\u200b\u4e00\u4e2a\u200b\u6743\u8861\u200b\u8bbe\u7f6e\u200b\uff0c\u200b\u5927\u5bb6\u200b\u53ef\u200b\u6839\u636e\u200b\u5177\u4f53\u200b\u4f7f\u7528\u200b\u573a\u666f\u200b\uff0c\u200b\u81ea\u200b\u5b9a\u200b\u8bbe\u7f6e\u200b\u5408\u9002\u200b\u503c\u200b\u3002
    "},{"location":"install_usage/rapidocr/changelog/#2024-01-30-v1310-update","title":"\ud83c\udf082024-01-30 v1.3.10 update","text":"
    • \u200b\u4fee\u590d\u200bget_boxes_img_without_det bug by AuroraWright
    "},{"location":"install_usage/rapidocr/changelog/#2023-12-28-v139-update","title":"\ud83e\udd702023-12-28 v1.3.9 update","text":"
    • \u200b\u4f18\u5316\u200brapidocr\u200b\u7cfb\u5217\u200b\u5e93\u4e3b\u200b\u51fd\u6570\u200b\u4ee3\u7801\u200b\u903b\u8f91\u200b\uff0c\u200b\u4fbf\u4e8e\u200b\u5c0f\u4f19\u4f34\u200b\u4eec\u200b\u4e8c\u6b21\u5f00\u53d1\u200b
    • Merge PR #141 by theikkila
    • Merge PR #139 by debanjum
    "},{"location":"install_usage/rapidocr/changelog/#2023-10-25-v138-update","title":"\ud83d\ude1c2023-10-25 v1.3.8 update","text":"
    • \u200b\u4fee\u590d\u200bissue #133
    "},{"location":"install_usage/rapidocr/changelog/#2023-09-21-v137-update","title":"\ud83d\udce12023-09-21 v1.3.7 update","text":"
    • \u200b\u5b8c\u5584\u200bVisRes\u200b\u7c7b\u200b\u5728\u200b\u7ec8\u7aef\u200b\u60c5\u51b5\u200b\u4e0b\u200b\u7684\u200b\u4f7f\u7528\u200b
    • \u200b\u4fee\u590d\u200bauto_text_det\u200b\u7684\u200b\u6761\u4ef6\u200b\u9519\u8bef\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2023-09-20-v136-update","title":"\ud83e\uddf82023-09-20 v1.3.6 update","text":"
    • \u200b\u6dfb\u52a0\u200bVisRes\u200b\u7c7b\u200b\uff0c\u200b\u4fbf\u4e8e\u200b\u5feb\u901f\u200b\u53ef\u89c6\u5316\u200b\u7ed3\u679c\u200b\u3002\u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200bdemo.py\u200b\u7528\u6cd5\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2023-09-20-v135-update","title":"\ud83d\ude002023-09-20 v1.3.5 update","text":"
    • Fixed issue #122
    "},{"location":"install_usage/rapidocr/changelog/#2023-09-18-v134-update","title":"\u23f02023-09-18 v1.3.4 update","text":"
    • \u200b\u4f18\u5316\u200b\u66f4\u65b0\u200b\u53c2\u6570\u200b\u90e8\u5206\u200b\u7684\u200b\u51fd\u6570\u200b\u5b9e\u73b0\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2023-09-06-v132-update","title":"\ud83e\uddf82023-09-06 v1.3.2 update","text":"
    • \u200b\u4fee\u590d\u200bissue #116
    "},{"location":"install_usage/rapidocr/changelog/#2023-08-29-v131-update","title":"\u2b502023-08-29 v1.3.1 update","text":"
    • \u200b\u4fee\u590d\u200bissue #115
    "},{"location":"install_usage/rapidocr/changelog/#2023-08-26-v130-update","title":"\ud83c\udf892023-08-26 v1.3.0 update","text":"
    • \u200b\u5c06\u200bPaddleOCR v4\u200b\u7248\u200b\u5bf9\u5e94\u200b\u7684\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u548c\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u8f7b\u91cf\u200b\u6a21\u578b\u200b\u8f6c\u6362\u200b\u4e3a\u200bonnx\uff0c\u200b\u5e76\u200b\u6253\u5305\u200b\u5230\u200bwhl\u200b\u4e2d\u200b\u3002
    • \u200b\u63a5\u53e3\u200b\u4e0e\u200bv1.2.x\u200b\u4e00\u81f4\u200b\uff0c\u200b\u76f4\u63a5\u200b\u4f7f\u7528\u200b\u5373\u53ef\u200b\u3002
    "},{"location":"install_usage/rapidocr/changelog/#2023-07-12-v1212-update","title":"\ud83d\ude092023-07-12 v1.2.12 update","text":"
    • \u200b\u5728\u200brapidocr_onnxruntime\u200b\u521d\u59cb\u5316\u200b\u65f6\u200b\uff0c\u200b\u6dfb\u52a0\u200bdet_use_cuda\u3001cls_use_cuda\u3001rec_use_cuda\u200b\u53c2\u6570\u200b
    • \u200b\u517c\u5bb9\u200b\u914d\u7f6e\u6587\u4ef6\u200b\u65b9\u5f0f\u200b\u4f20\u5165\u200bRapidOCR\u200b\u7c7b\u4e2d\u200b
    • rapidocr_openvino\u200b\u540c\u7406\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2023-03-11-v122-update","title":"\ud83c\udfae2023-03-11 v1.2.2 update","text":"
    • \u200b\u4fee\u590d\u200b\u5b9e\u4f8b\u200b\u5316\u200bpython\u200b\u4e2d\u200bRapidOCR\u200b\u7c7b\u200b\u4f20\u5165\u200b\u53c2\u6570\u200b\u9519\u8bef\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2023-03-07-v121-update","title":"\ud83e\udde22023-03-07 v1.2.1 update","text":"
    • rapidocr\u200b\u7cfb\u5217\u200b\u5305\u200b\u66f4\u65b0\u200b\u5230\u200bv1.2.0
    • \u200b\u4f18\u5316\u200bpython\u200b\u4e0b\u200brapidocr\u200b\u7cfb\u5217\u200b\u5305\u200b\u7684\u200b\u63a5\u53e3\u200b\u4f20\u5165\u200b\u53c2\u6570\u200b\uff0c\u200b\u652f\u6301\u200b\u5b9e\u4f8b\u200b\u5316\u7c7b\u200b\u65f6\u200b\uff0c\u200b\u52a8\u6001\u200b\u7ed9\u5b9a\u200b\u5404\u4e2a\u200b\u53c2\u6570\u200b\uff0c\u200b\u66f4\u52a0\u200b\u7075\u6d3b\u200b\u3002
    • \u200b\u5982\u679c\u200b\u4e0d\u200b\u6307\u5b9a\u200b\uff0c\u200b\u5219\u200b\u7528\u200bconfig.yaml\u200b\u4e0b\u200b\u7684\u200b\u9ed8\u8ba4\u200b\u53c2\u6570\u200b\u3002
    • \u200b\u5177\u4f53\u200b\u53ef\u200b\u53c2\u89c1\u200b\uff1a\u200b\u4f20\u5165\u200b\u53c2\u6570\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2023-02-16-update","title":"\u26f82023-02-16 update","text":"
    • \u200b\u4f18\u5316\u200bocrweb\u200b\u90e8\u5206\u200b\u4ee3\u7801\u200b\uff0c\u200b\u53ef\u200b\u76f4\u63a5\u200bpip\u200b\u5b89\u88c5\u200b\uff0c\u200b\u5feb\u901f\u200b\u4f7f\u7528\u200b\uff0c\u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200bREADME\u3002
    • \u200b\u4f18\u5316\u200bpython\u200b\u4e2d\u200b\u5404\u4e2a\u200b\u90e8\u5206\u200b\u7684\u200b\u63a8\u7406\u200b\u4ee3\u7801\u200b\uff0c\u200b\u66f4\u52a0\u200b\u7d27\u51d1\u200b\uff0c\u200b\u540c\u65f6\u200b\u6613\u4e8e\u200b\u7ef4\u62a4\u200b\u3002
    "},{"location":"install_usage/rapidocr/changelog/#2023-01-21-update","title":"\ud83c\udf892023-01-21 update","text":"
    • [python] \u200b\u6dfb\u52a0\u200b\u542b\u6709\u200b\u6587\u5b57\u200b\u7684\u200b\u56fe\u50cf\u200b\u65b9\u5411\u200b\u5206\u7c7b\u200b\u6a21\u5757\u200b\uff0c\u200b\u5177\u4f53\u200b\u53c2\u89c1\u200bRapid Orientation
    "},{"location":"install_usage/rapidocr/changelog/#2022-12-19-update","title":"\u26bd2022-12-19 update","text":"
    • [python] \u200b\u6dfb\u52a0\u200b\u8868\u683c\u200b\u7ed3\u6784\u200b\u8fd8\u539f\u200b\u6a21\u5757\u200b\uff0c\u200b\u5177\u4f53\u200b\u53c2\u89c1\u200bRapid Table
    "},{"location":"install_usage/rapidocr/changelog/#2022-12-14-update","title":"\ud83e\udd162022-12-14 update","text":"
    • [python] \u200b\u5c06\u200b\u914d\u7f6e\u200b\u53c2\u6570\u200b\u548c\u200b\u6a21\u578b\u200b\u79fb\u200b\u5230\u200b\u6a21\u5757\u200b\u91cc\u9762\u200b\uff0c\u200b\u540c\u65f6\u200b\u5c06\u200b\u6a21\u578b\u200b\u6253\u200b\u5230\u200bwhl\u200b\u5305\u5185\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u76f4\u63a5\u200bpip\u200b\u5b89\u88c5\u200b\u4f7f\u7528\u200b\uff0c\u200b\u66f4\u52a0\u200b\u65b9\u4fbf\u5feb\u6377\u200b\u3002
    • \u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b\uff1aREADME
    "},{"location":"install_usage/rapidocr/changelog/#2022-11-20-update","title":"\ud83e\uddfb2022-11-20 update","text":"
    • [python] \u200b\u6dfb\u52a0\u200b\u7248\u9762\u200b\u5206\u6790\u200b\u90e8\u5206\u200b,\u200b\u652f\u6301\u200b\u4e2d\u6587\u200b\u3001\u200b\u82f1\u6587\u200b\u548c\u200b\u8868\u683c\u200b\u4e09\u79cd\u200b\u7248\u9762\u200b\u7684\u200b\u68c0\u6d4b\u200b\u5206\u6790\u200b\u3002\u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b:Rapid Structure\u200b\u90e8\u5206\u200b\u3002
    "},{"location":"install_usage/rapidocr/changelog/#2022-11-01-update","title":"\ud83c\udf832022-11-01 update","text":"
    • \u200b\u6dfb\u52a0\u200bHugging Face Demo, \u200b\u589e\u52a0\u200b\u53ef\u4ee5\u200b\u8c03\u8282\u200b\u8d85\u200b\u53c2\u6570\u200b\u7684\u200b\u529f\u80fd\u200b\uff0c\u200b\u8be6\u60c5\u200b\u53ef\u200b\u8bbf\u95ee\u200bHugging Face Demo
    "},{"location":"install_usage/rapidocr/changelog/#2022-10-01-udpate","title":"\ud83d\udea92022-10-01 udpate","text":"
    • \u200b\u4fee\u590d\u200bpython\u200b\u90e8\u5206\u200b\u4e0b\u200b\u4e00\u4e9b\u200b\u8f83\u200b\u5c0f\u200bbugs
    • merge\u200b\u6765\u81ea\u200bAutumnSun1996\u200b\u7684\u200bOCRWeb\u200b\u5b9e\u73b0\u200b\u7684\u200b\u591a\u200b\u8bed\u8a00\u200b\u90e8\u7f72\u200bdemo\uff0c\u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b\uff1aocrweb_mutli-README
    • \u200b\u6dfb\u52a0\u200bonnxruntime-gpu\u200b\u63a8\u7406\u200b\u901f\u5ea6\u200b\u8f83\u6162\u200b\u4e8e\u200bCPU\u200b\u7684\u200b\u95ee\u9898\u200b\u8bf4\u660e\u200b\uff0c\u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b\uff1aonnxruntime-gpu\u200b\u7248\u200b\u76f8\u5173\u200b\u8bf4\u660e\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2022-09-01-update","title":"\ud83d\udef42022-09-01 update","text":"
    • \u200b\u7531\u4e8e\u200bopenvino\u200b\u53d1\u5e03\u200b\u4e86\u200b2022.2.0.dev20220829\u200b\u7248\u672c\u200b\uff0c\u200b\u8be5\u200b\u7248\u672c\u200b\u89e3\u51b3\u200b\u4e86\u200bcls\u200b\u90e8\u5206\u200b\u6a21\u578b\u200b\u63a8\u7406\u200b\u7684\u200b\u95ee\u9898\u200b\u3002\u200b\u81f3\u6b64\u200b\uff0c\u200b\u57fa\u4e8e\u200bopenvino\u200b\u7684\u200brapidocr\u200b\u5b8c\u6210\u200b\u4e86\u200b\u7edf\u4e00\u200b\uff0c\u200b\u5168\u90e8\u200b\u7531\u200bopenvino\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u5b8c\u6210\u200b\u3002
    • \u200b\u8be6\u7ec6\u200b\u4f7f\u7528\u200b\u65b9\u6cd5\u200b\u53c2\u89c1\u200b\uff1apython/README
    "},{"location":"install_usage/rapidocr/changelog/#2022-08-17-update","title":"\ud83e\uddf82022-08-17 update","text":"
    • python/ocrweb\u200b\u90e8\u5206\u200b v1.1.0\u200b\u53d1\u5e03\u200b\uff0c\u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200bv1.1.0
    "},{"location":"install_usage/rapidocr/changelog/#2022-08-14-update","title":"\ud83d\udd762022-08-14 update","text":"
    • ocrweb\u200b\u90e8\u5206\u200b\u589e\u52a0\u200b\u4ee5\u200bAPI\u200b\u65b9\u5f0f\u200b\u90e8\u7f72\u200b\u8c03\u7528\u200b\u7684\u200b\u529f\u80fd\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u901a\u8fc7\u200b\u53d1\u9001\u200bPOST\u200b\u8bf7\u6c42\u200b\uff0c\u200b\u6765\u200b\u83b7\u5f97\u200bOCR\u200b\u8bc6\u522b\u200b\u7ed3\u679c\u200b\u3002
    • \u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b\uff1aAPI\u200b\u65b9\u5f0f\u200b\u8c03\u7528\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2022-07-07-update","title":"\u27282022-07-07 update","text":"
    • \u200b\u4fee\u590d\u200bpython\u200b\u7248\u4e2d\u200bv3 rec\u200b\u63a8\u7406\u200bbug\uff0c\u200b\u5e76\u200b\u5c06\u200bv3 rec\u200b\u4e0e\u200bv2 rec\u200b\u5408\u5e76\u200b\u4e3a\u540c\u200b\u4e00\u5957\u200b\u63a8\u7406\u200b\u4ee3\u7801\u200b\uff0c\u200b\u66f4\u52a0\u200b\u7b80\u6d01\u200b\u548c\u200b\u65b9\u4fbf\u200b
    • \u200b\u6dfb\u52a0\u200bpython\u200b\u6a21\u5757\u200b\u4e0b\u200b\u7684\u200b\u5355\u5143\u6d4b\u8bd5\u200b
    • \u200b\u8be5\u200b\u9875\u9762\u200b\u6dfb\u52a0\u200b\u81f4\u8c22\u200b\u6a21\u5757\u200b\uff0c\u200b\u611f\u8c22\u200b\u4e3a\u200b\u8fd9\u4e2a\u200b\u9879\u76ee\u200b\u4f5c\u51fa\u8d21\u732e\u200b\u7684\u200b\u5c0f\u4f19\u4f34\u200b\u3002
    "},{"location":"install_usage/rapidocr/changelog/#2022-07-05-update","title":"\ud83d\ude012022-07-05 update","text":"
    • \u200b\u6dfb\u52a0\u200b\u5bf9\u200b\u5355\u884c\u200b\u6587\u672c\u200b\u7684\u200b\u5904\u7406\u200b\u80fd\u529b\u200b\uff0c\u200b\u5bf9\u4e8e\u200b\u5355\u884c\u200b\u6587\u672c\u200b\uff0c\u200b\u53ef\u200b\u81ea\u884c\u200b\u8bbe\u5b9a\u200b\u9608\u503c\u200b\uff0c\u200b\u4e0d\u8fc7\u200b\u68c0\u6d4b\u200b\u6a21\u5757\u200b\uff0c\u200b\u76f4\u63a5\u200b\u8bc6\u522b\u200b\u5373\u53ef\u200b\u3002\u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200bREADME
    • \u200b\u4f18\u5316\u200bpython\u200b\u90e8\u5206\u200b\u4ee3\u7801\u200b\u903b\u8f91\u200b\uff0c\u200b\u66f4\u200b\u4f18\u96c5\u200b\u7b80\u6d01\u200b\u3002
    "},{"location":"install_usage/rapidocr/changelog/#2022-06-30-update","title":"\ud83c\udfdd2022-06-30 update","text":"
    • python\u200b\u63a8\u7406\u200b\u90e8\u5206\u200b\uff0c\u200b\u589e\u52a0\u200b\u53c2\u6570\u200b\u9009\u62e9\u200b\u4f7f\u7528\u200bGPU\u200b\u63a8\u7406\u200b\u7684\u200b\u914d\u7f6e\u200b\u9009\u9879\u200b\uff0c\u200b\u5728\u200b\u6b63\u786e\u200b\u5b89\u88c5\u200bonnxruntime-gpu\u200b\u7248\u672c\u200b\u524d\u63d0\u200b\u4e0b\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u4e00\u952e\u200b\u4f7f\u7528\u200b\uff08Fix issue#30\uff09
    • \u200b\u5177\u4f53\u200b\u57fa\u4e8e\u200bGPU\u200b\u7684\u200b\u63a8\u7406\u200b\u60c5\u51b5\u200b\uff0c\u200b\u9700\u8981\u200b\u7b49\u200b\u6211\u200b\u540e\u7eed\u200b\u6574\u7406\u200b\u4e00\u4e0b\u200b\uff0c\u200b\u518d\u200b\u66f4\u65b0\u200b\u51fa\u6765\u200b
    • \u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b\uff1aonnxruntime-gpu\u200b\u7248\u200b\u63a8\u7406\u200b\u914d\u7f6e\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2022-06-25-update","title":"\ud83d\udccc2022-06-25 update","text":"
    • \u200b\u91cd\u65b0\u6574\u7406\u200bpython\u200b\u90e8\u5206\u200b\u63a8\u7406\u200b\u4ee3\u7801\u200b\uff0c\u200b\u5c06\u200b\u5e38\u7528\u200b\u8c03\u8282\u200b\u53c2\u6570\u200b\u5168\u90e8\u200b\u653e\u5230\u200byaml\u200b\u6587\u4ef6\u200b\u4e2d\u200b\uff0c\u200b\u4fbf\u4e8e\u200b\u8c03\u8282\u200b\uff0c\u200b\u66f4\u52a0\u200b\u5bb9\u6613\u200b\u4f7f\u7528\u200b
    • \u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b\uff1aREADME
    "},{"location":"install_usage/rapidocr/changelog/#2022-05-15-udpate","title":"\ud83c\udf7f2022-05-15 udpate","text":"
    • \u200b\u589e\u52a0\u200bPaddleOCR v3 rec\u200b\u6a21\u578b\u200b\u8f6c\u6362\u200b\u540e\u200b\u7684\u200bONNX\u200b\u6a21\u578b\u200b\uff0c\u200b\u76f4\u63a5\u200b\u53bb\u200b\u7f51\u76d8\u200b\u4e0b\u8f7d\u200b\u66ff\u6362\u200b\u5373\u53ef\u200b\u3002(\u200b\u767e\u5ea6\u7f51\u200b\u76d8\u200b | Google Drive)
    • \u200b\u589e\u52a0\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u5404\u4e2a\u200b\u7248\u672c\u200b\u6548\u679c\u200b\u5bf9\u6bd4\u200b\u8868\u683c\u200b\uff0c\u200b\u8be6\u60c5\u200b\u70b9\u51fb\u200b\u5404\u4e2a\u200b\u7248\u672c\u200bONNX\u200b\u6a21\u578b\u200b\u6548\u679c\u200b\u5bf9\u6bd4\u200b\u3002v3\u200b\u7684\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u4ece\u200b\u81ea\u5df1\u200b\u6784\u5efa\u200b\u6d4b\u8bd5\u200b\u96c6\u4e0a\u200b\u7684\u200b\u6307\u6807\u200b\u6765\u770b\u200b\u4e0d\u5982\u200b\u4e4b\u524d\u200b\u7684\u200b\u597d\u200b\u3002
    "},{"location":"install_usage/rapidocr/changelog/#2022-05-12-upadte","title":"\ud83d\ude002022-05-12 upadte","text":"
    • \u200b\u589e\u52a0\u200bPaddleOCR v3 det\u200b\u6a21\u578b\u200b\u8f6c\u6362\u200b\u7684\u200bONNX\u200b\u6a21\u578b\u200b\uff0c\u200b\u76f4\u63a5\u200b\u53bb\u200b\u7f51\u76d8\u200b\u4e0b\u8f7d\u200b\uff0c\u200b\u66ff\u6362\u200b\u5373\u53ef\u200b\u3002(\u200b\u767e\u5ea6\u7f51\u200b\u76d8\u200b | Google Drive)
    • \u200b\u589e\u52a0\u200b\u5404\u4e2a\u200b\u7248\u672c\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\u6548\u679c\u200b\u5bf9\u6bd4\u200b\u8868\u683c\u200b\uff0c\u200b\u8be6\u60c5\u200b\u70b9\u51fb\u200b\u5404\u4e2a\u200b\u7248\u672c\u200bONNX\u200b\u6a21\u578b\u200b\u6548\u679c\u200b\u5bf9\u6bd4\u200b\u3002v3\u200b\u7684\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\u4ece\u200b\u6307\u6807\u200b\u6765\u770b\u200b\u662f\u200b\u597d\u200b\u4e8e\u200b\u4e4b\u524d\u200b\u7684\u200bv2\u200b\u7684\u200b\uff0c\u200b\u63a8\u8350\u200b\u4f7f\u7528\u200b\u3002
    "},{"location":"install_usage/rapidocr/changelog/#2022-04-04-udpate","title":"\ud83c\udfa72022-04-04 udpate","text":"
    • \u200b\u589e\u52a0\u200bpython\u200b\u4e0b\u200b\u7684\u200b\u57fa\u4e8e\u200bOpenVINO\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u7684\u200b\u652f\u6301\u200b
    • \u200b\u7ed9\u51fa\u200bOpenVINO\u200b\u548c\u200bONNXRuntime\u200b\u7684\u200b\u6027\u80fd\u200b\u5bf9\u6bd4\u200b\u8868\u683c\u200b
    • \u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b:python/README
    "},{"location":"install_usage/rapidocr/changelog/#2022-02-24-udpate","title":"2022-02-24 udpate","text":"
    • \u200b\u4f18\u5316\u200bpython\u200b\u76ee\u5f55\u200b\u4e0b\u200b\u7684\u200b\u63a8\u7406\u200b\u4ee3\u7801\u200b
    • \u200b\u6dfb\u52a0\u200b\u8c03\u7528\u200b\u4e0d\u540c\u200b\u8bed\u8a00\u200b\u6a21\u578b\u200b\u7684\u200b\u63a8\u7406\u200b\u4ee3\u7801\u200b\u793a\u4f8b\u200b
    • \u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b\uff1apython/onnxruntime_infer/README
    "},{"location":"install_usage/rapidocr/changelog/#2021-12-18-udpate","title":"2021-12-18 udpate","text":"
    • \u200b\u6dfb\u52a0\u200bGoogle Colab Demo
    "},{"location":"install_usage/rapidocr/changelog/#2021-11-28-udpate","title":"2021-11-28 udpate","text":"
    • \u200b\u66f4\u65b0\u200bocrweb\u200b\u90e8\u5206\u200b
    • \u200b\u6dfb\u52a0\u200b\u663e\u793a\u200b\u5404\u4e2a\u200b\u9636\u6bb5\u200b\u5904\u7406\u200b\u65f6\u95f4\u200b
    • \u200b\u66f4\u65b0\u200b\u8bf4\u660e\u200b\u6587\u6863\u200b
    • \u200b\u66f4\u6362\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\u4e3a\u200bch_PP-OCRv2_det_infer.onnx,\u200b\u63a8\u7406\u200b\u66f4\u200b\u5feb\u200b\uff0c\u200b\u66f4\u51c6\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2021-11-13-udpate","title":"2021-11-13 udpate","text":"
    • \u200b\u6dfb\u52a0\u200bpython\u200b\u7248\u672c\u200b\u4e2d\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u548c\u200b\u8bc6\u522b\u200b\u53ef\u200b\u8c03\u8282\u200b\u7684\u200b\u8d85\u200b\u53c2\u6570\u200b\uff0c\u200b\u4e3b\u8981\u200b\u6709\u200bbox_thresh|unclip_ratio|text_score\uff0c\u200b\u8be6\u60c5\u200b\u89c1\u200b\u53c2\u6570\u200b\u8c03\u8282\u200b
    • \u200b\u5c06\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u4e2d\u200b\u5b57\u5178\u200b\u4f4d\u7f6e\u200b\u4ee5\u200b\u53c2\u6570\u200b\u65b9\u5f0f\u200b\u7ed9\u51fa\u200b\uff0c\u200b\u4fbf\u4e8e\u200b\u7075\u6d3b\u200b\u914d\u7f6e\u200b\uff0c\u200b\u8be6\u60c5\u200b\u89c1\u200bkeys_path
    "},{"location":"install_usage/rapidocr/changelog/#2021-10-27-udpate","title":"2021-10-27 udpate","text":"
    • \u200b\u6dfb\u52a0\u200b\u4f7f\u7528\u200bonnxruntime-gpu\u200b\u7248\u200b\u63a8\u7406\u200b\u7684\u200b\u4ee3\u7801\u200b\uff08\u200b\u4e0d\u8fc7\u200bgpu\u200b\u7248\u672c\u200b\u7684\u200bonnxruntime\u200b\u4e0d\u592a\u597d\u200b\u7528\u200b\uff0c\u200b\u6309\u7167\u200b\u5b98\u65b9\u200b\u6559\u7a0b\u200b\u914d\u7f6e\u200b\uff0c\u200b\u611f\u89c9\u200b\u6ca1\u6709\u200b\u8c03\u7528\u200b\u8d77\u6765\u200bGPU\uff09
    • \u200b\u5177\u4f53\u200b\u4f7f\u7528\u200b\u6b65\u9aa4\u200b\u53c2\u89c1\u200b: onnxruntime-gpu\u200b\u63a8\u7406\u200b\u914d\u7f6e\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2021-09-13-udpate","title":"2021-09-13 udpate","text":"
    • \u200b\u6dfb\u52a0\u200b\u57fa\u4e8e\u200bpython\u200b\u7684\u200bwhl\u200b\u6587\u4ef6\u200b\uff0c\u200b\u4fbf\u4e8e\u200b\u4f7f\u7528\u200b\uff0c\u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200brelease/python_sdk
    "},{"location":"install_usage/rapidocr/changelog/#2021-09-11-udpate","title":"2021-09-11 udpate","text":"
    • \u200b\u6dfb\u52a0\u200bPP-OCRv2\u200b\u65b0\u589e\u200b\u6a21\u578b\u200bonnx\u200b\u7248\u672c\u200b
    • \u200b\u4f7f\u7528\u200b\u65b9\u6cd5\u200b\u63a8\u7406\u200b\u4ee3\u7801\u200b\u4e0d\u53d8\u200b\uff0c\u200b\u76f4\u63a5\u200b\u66ff\u6362\u200b\u5bf9\u5e94\u200b\u6a21\u578b\u200b\u5373\u53ef\u200b\u3002
    • \u200b\u7ecf\u8fc7\u200b\u5728\u200b\u81ea\u6709\u200b\u6d4b\u8bd5\u200b\u96c6\u4e0a\u200b\u8bc4\u6d4b\u200b\uff1a
    • PP-OCRv2\u200b\u68c0\u6d4b\u200b\u6a21\u578b\u200b\u6548\u679c\u200b\u6709\u200b\u5927\u5e45\u5ea6\u200b\u63d0\u5347\u200b\uff0c\u200b\u6a21\u578b\u200b\u5927\u5c0f\u200b\u6ca1\u200b\u53d8\u200b\u3002
    • PP-OCRv2\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\u6548\u679c\u200b\u65e0\u200b\u660e\u663e\u200b\u63d0\u5347\u200b\uff0c\u200b\u6a21\u578b\u200b\u5927\u5c0f\u200b\u589e\u52a0\u200b\u4e86\u200b3.58M\u3002
    • \u200b\u6a21\u578b\u200b\u4e0a\u200b\u4f20\u5230\u200b\u767e\u5ea6\u7f51\u200b\u76d8\u200b \u200b\u63d0\u53d6\u200b\u7801\u200b\uff1a30jv
    "},{"location":"install_usage/rapidocr/changelog/#2021-08-07-udpate","title":"2021-08-07 udpate","text":"
    • PP-Structure \u200b\u8868\u683c\u200b\u7ed3\u6784\u200b\u548c\u200bcell\u200b\u5750\u6807\u200b\u9884\u6d4b\u200b \u200b\u6b63\u5728\u200b\u6574\u7406\u200b\u4e2d\u200b
    • \u200b\u4e4b\u524d\u200b\u505a\u200b\u7684\u200b,\u200b\u672a\u200b\u5b8c\u6210\u200b\u7684\u200b\uff0c\u200b\u6b22\u8fce\u200b\u63d0\u200bPR
    • \u200b\u6253\u200bDokcer\u200b\u955c\u50cf\u200b
    • \u200b\u5c1d\u8bd5\u200bonnxruntime-gpu\u200b\u63a8\u7406\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2021-07-17-udpate","title":"2021-07-17 udpate","text":"
    • \u200b\u5b8c\u5584\u200bREADME\u200b\u6587\u6863\u200b
    • \u200b\u589e\u52a0\u200b\u82f1\u6587\u200b\u3001\u200b\u6570\u5b57\u200b\u8bc6\u522b\u200bonnx\u200b\u6a21\u578b\u200b\uff0c\u200b\u5177\u4f53\u200b\u53c2\u89c1\u200bpython/en_number_ppocr_mobile_v2_rec\uff0c\u200b\u7528\u6cd5\u200b\u540c\u200b\u5176\u4ed6\u200b
    • \u200b\u6574\u7406\u200b\u4e00\u4e0b\u200b\u6a21\u578b\u200b\u8f6c\u200bonnx
    "},{"location":"install_usage/rapidocr/changelog/#2021-07-04-udpate","title":"2021-07-04 udpate","text":"
    • \u200b\u76ee\u524d\u200b\u4ed3\u5e93\u200b\u4e0b\u200b\u7684\u200bpython\u200b\u7a0b\u5e8f\u200b\u5df2\u7ecf\u200b\u53ef\u4ee5\u200b\u5728\u200b\u6811\u8393\u200b\u6d3e\u200b4B\u200b\u4e0a\u200b\uff0c\u200b\u6210\u529f\u200b\u8fd0\u884c\u200b\uff0c\u200b\u8be6\u7ec6\u4fe1\u606f\u200b\u8bf7\u200b\u8fdb\u7fa4\u200b\uff0c\u200b\u8be2\u95ee\u200b\u7fa4\u4e3b\u200b
    • \u200b\u66f4\u65b0\u200b\u6574\u4f53\u200b\u7ed3\u6784\u56fe\u200b\uff0c\u200b\u6dfb\u52a0\u200b\u6811\u8393\u200b\u6d3e\u200b\u7684\u200b\u652f\u6301\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2021-06-20-udpate","title":"2021-06-20 udpate","text":"
    • \u200b\u4f18\u5316\u200bocrweb\u200b\u4e2d\u200b\u8bc6\u522b\u200b\u7ed3\u679c\u663e\u793a\u200b\uff0c\u200b\u540c\u65f6\u200b\u6dfb\u52a0\u200b\u8bc6\u522b\u200b\u52a8\u56fe\u200b\u6f14\u793a\u200b
    • \u200b\u66f4\u65b0\u200bdatasets\u200b\u76ee\u5f55\u200b\uff0c\u200b\u6dfb\u52a0\u200b\u4e00\u4e9b\u200b\u5e38\u7528\u200b\u6570\u636e\u5e93\u200b\u94fe\u63a5\u200b(\u200b\u642c\u8fd0\u200b\u4e00\u4e0b\u200b-)
    • \u200b\u66f4\u65b0\u200bFAQ
    "},{"location":"install_usage/rapidocr/changelog/#2021-06-10-udpate","title":"2021-06-10 udpate","text":"
    • \u200b\u6dfb\u52a0\u200bserver\u200b\u7248\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\u6a21\u578b\u200b\uff0c\u200b\u8be6\u60c5\u200b\u89c1\u200b\u63d0\u53d6\u200b\u7801\u200b\uff1a30jv
    "},{"location":"install_usage/rapidocr/changelog/#2021-06-08-udpate","title":"2021-06-08 udpate","text":"
    • \u200b\u6574\u7406\u200b\u4ed3\u5e93\u200b\uff0c\u200b\u7edf\u4e00\u200b\u6a21\u578b\u200b\u4e0b\u8f7d\u200b\u8def\u5f84\u200b
    • \u200b\u5b8c\u5584\u200b\u76f8\u5173\u200b\u8bf4\u660e\u200b\u6587\u6863\u200b
    "},{"location":"install_usage/rapidocr/changelog/#2021-03-24-udpate","title":"2021-03-24 udpate","text":"
    • \u200b\u65b0\u200b\u6a21\u578b\u200b\u5df2\u7ecf\u200b\u5b8c\u5168\u200b\u517c\u5bb9\u200bONNXRuntime 1.7 \u200b\u6216\u200b\u66f4\u200b\u9ad8\u200b\u7248\u672c\u200b\u3002 \u200b\u7279\u522b\u611f\u8c22\u200b\uff1a@Channingss
    • \u200b\u65b0\u7248\u200bonnxruntime\u200b\u6bd4\u200b1.6.0 \u200b\u6027\u80fd\u200b\u63d0\u5347\u200b40%\u200b\u4ee5\u4e0a\u200b\u3002
    "},{"location":"install_usage/rapidocr/cli/","title":"\u547d\u4ee4\u884c\u200b\u5de5\u5177","text":"

    rapidocr_onnxruntime\u200b\u5305\u542b\u200b\u4e86\u200b\u547d\u4ee4\u884c\u200b\u5de5\u5177\u200b\uff0c\u200b\u5b89\u88c5\u200b\u4e4b\u540e\u200b\uff0c\u200b\u5373\u53ef\u200b\u4f7f\u7528\u200b\u3002

    "},{"location":"install_usage/rapidocr/cli/#_1","title":"\u53c2\u6570\u200b\u8bf4\u660e","text":"
    $ rapidocr_onnxruntime -h\nusage: rapidocr_onnxruntime [-h] -img IMG_PATH [-p] [--text_score TEXT_SCORE]\n                            [--no_det] [--no_cls] [--no_rec] [--print_verbose]\n                            [--min_height MIN_HEIGHT]\n                            [--width_height_ratio WIDTH_HEIGHT_RATIO]\n                            [--det_use_cuda] [--det_model_path DET_MODEL_PATH]\n                            [--det_limit_side_len DET_LIMIT_SIDE_LEN]\n                            [--det_limit_type {max,min}]\n                            [--det_thresh DET_THRESH]\n                            [--det_box_thresh DET_BOX_THRESH]\n                            [--det_unclip_ratio DET_UNCLIP_RATIO]\n                            [--det_donot_use_dilation]\n                            [--det_score_mode {slow,fast}] [--cls_use_cuda]\n                            [--cls_model_path CLS_MODEL_PATH]\n                            [--cls_image_shape CLS_IMAGE_SHAPE]\n                            [--cls_label_list CLS_LABEL_LIST]\n                            [--cls_batch_num CLS_BATCH_NUM]\n                            [--cls_thresh CLS_THRESH] [--rec_use_cuda]\n                            [--rec_model_path REC_MODEL_PATH]\n                            [--rec_img_shape REC_IMG_SHAPE]\n                            [--rec_batch_num REC_BATCH_NUM] [-vis]\n                            [--vis_font_path VIS_FONT_PATH]\n                            [--vis_save_path VIS_SAVE_PATH]\n\noptional arguments:\n  -h, --help            show this help message and exit\n  -img IMG_PATH, --img_path IMG_PATH\n  -p, --print_cost\n\nGlobal:\n  --text_score TEXT_SCORE\n  --no_det\n  --no_cls\n  --no_rec\n  --print_verbose\n  --min_height MIN_HEIGHT\n  --width_height_ratio WIDTH_HEIGHT_RATIO\n\nDet:\n  --det_use_cuda\n  --det_model_path DET_MODEL_PATH\n  --det_limit_side_len DET_LIMIT_SIDE_LEN\n  --det_limit_type {max,min}\n  --det_thresh DET_THRESH\n  --det_box_thresh DET_BOX_THRESH\n  --det_unclip_ratio DET_UNCLIP_RATIO\n  --det_donot_use_dilation\n  --det_score_mode {slow,fast}\n\nCls:\n  --cls_use_cuda\n  --cls_model_path CLS_MODEL_PATH\n  --cls_image_shape CLS_IMAGE_SHAPE\n  --cls_label_list CLS_LABEL_LIST\n  --cls_batch_num CLS_BATCH_NUM\n  --cls_thresh CLS_THRESH\n\nRec:\n  --rec_use_cuda\n  --rec_model_path REC_MODEL_PATH\n  --rec_img_shape REC_IMG_SHAPE\n  --rec_batch_num REC_BATCH_NUM\n\nVisual Result:\n  -vis, --vis_res\n  --vis_font_path VIS_FONT_PATH\n                        When -vis is True, the font_path must have value.\n  --vis_save_path VIS_SAVE_PATH\n                        The directory of saving the vis image.\n
    "},{"location":"install_usage/rapidocr/cli/#_2","title":"\u4f7f\u7528\u200b\u793a\u4f8b","text":"

    Example

    \u200b\u4ee5\u4e0b\u200b\u53ea\u200b\u7ed9\u51fa\u200b\u5e38\u89c1\u200b\u7528\u4f8b\u200b\uff0c\u200b\u5177\u4f53\u200b\u53ef\u200b\u81ea\u884c\u200b\u63a2\u7d22\u200b\u4f7f\u7528\u200b

    \u200b\u56fe\u50cf\u200b\u9884\u6d4b\u200b\u53ea\u200b\u4f7f\u7528\u200b\u68c0\u6d4b\u200b\u53ea\u200b\u4f7f\u7528\u200b\u8bc6\u522b\u200b\u53ef\u89c6\u5316\u200b\u67e5\u770b\u200b 
    rapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg\n
    rapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg -no_cls -no_rec\n
    rapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg -no_det -no_cls\n
    raprapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg -vis --vis_font_path resources/fonts/FZYTK.TTF\n
    "},{"location":"install_usage/rapidocr/config_yaml/","title":"\u53c2\u6570\u200b\u89e3\u91ca","text":"

    \u200b\u8bf7\u200b\u79fb\u6b65\u200bAPI/RapidOCR\u200b\u67e5\u770b\u200b

    "},{"location":"install_usage/rapidocr/install/","title":"\u5b89\u88c5","text":""},{"location":"install_usage/rapidocr/install/#_1","title":"\u7b80\u4ecb","text":"

    rapidocr_onnxruntime\u200b\u548c\u200brapidocr_openvino\u200b\u4e24\u4e2a\u200b\u5305\u9664\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u4e0d\u540c\u200b\u4e4b\u5916\u200b\uff0c\u200b\u5176\u4f59\u200b\u5747\u200b\u76f8\u540c\u200b\u3002\u200b\u540e\u7eed\u200b\u8bf4\u660e\u200b\u6587\u6863\u200b\u5747\u200b\u4ee5\u200brapidocr_onnxruntime\u200b\u4e3a\u4f8b\u200b

    \u200b\u5982\u200b\u4f7f\u7528\u200brapidocr_openvino\uff0c\u200b\u76f4\u63a5\u200b\u66f4\u6362\u200b\u5173\u952e\u8bcd\u200brapidocr_onnxruntime\u200b\u4e3a\u200brapidocr_openvino\u200b\u5373\u53ef\u200b\u3002

    \u200b\u4e24\u8005\u200b\u5747\u200b\u662f\u200b\u5728\u200bCPU\u200b\u4e0a\u200b\u63a8\u7406\u200b\u7684\u200b\uff0c\u200b\u5982\u60f3\u200b\u5728\u200bGPU\u200b\u4e0a\u200b\u63a8\u7406\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u53c2\u8003\u200brapidocr_paddle\u200b\u7248\u200b\u3002

    "},{"location":"install_usage/rapidocr/install/#_2","title":"\u7248\u672c\u200b\u60c5\u51b5","text":"

    \u200b\u5404\u4e2a\u200b\u5e93\u200b\u7684\u200b\u6700\u65b0\u200b\u7248\u672c\u200b\uff1a

    \u200b\u5e93\u200b pypi\u200b\u6700\u65b0\u200b\u7248\u672c\u200b rapidocr_onnxruntime rapidocr_openvino rapidocr_paddle

    pypi\u200b\u4e0a\u200b\u5404\u4e2a\u200b\u7248\u672c\u200b\u7684\u200b\u5bf9\u5e94\u200b\u5173\u7cfb\u200b\uff1a

    \u200b\u7248\u672c\u200b \u200b\u5185\u7f6e\u200b\u6a21\u578b\u200b\u7248\u672c\u200b \u200b\u5bf9\u5e94\u200bPaddleOCR \u200b\u5206\u652f\u200b v1.3.x PaddleOCR v4\u200b\u7248\u200b release/2.7 v1.2.xv1.1.xv1.0.x PaddleOCR v3\u200b\u7248\u200b release/2.6"},{"location":"install_usage/rapidocr/install/#_3","title":"\u5b89\u88c5","text":"

    \u200b\u987a\u5229\u200b\u7684\u8bdd\u200b\uff0c\u200b\u4e00\u884c\u200b\u547d\u4ee4\u200b\u5373\u53ef\u200b\u3002\u200b\u5305\u200b\u5927\u5c0f\u200b\u7ea6\u200b\u4e3a\u200b14M\u200b\u5de6\u53f3\u200b\uff0c\u200b\u5305\u542b\u200b\u4e86\u200b\u4e09\u4e2a\u200b\u6a21\u578b\u200b\uff08\u200b\u6587\u672c\u200b\u68c0\u6d4b\u200b\u3001\u200b\u6587\u672c\u200b\u884c\u200b\u65b9\u5411\u200b\u5206\u7c7b\u200b\u548c\u200b\u6587\u672c\u200b\u8bc6\u522b\u200b\uff09\u3002\u200b\u56e0\u4e3a\u200b\u5176\u4e2d\u200bmobile\u200b\u7248\u200b\u6a21\u578b\u200b\u8f83\u200b\u5c0f\u200b\uff0c\u200b\u56e0\u6b64\u200b\u5c06\u200b\u76f8\u5173\u200b\u6a21\u578b\u200b\u90fd\u200b\u5df2\u200b\u6253\u200b\u5230\u200bwhl\u200b\u5305\u200b\uff0c\u200b\u53ef\u200b\u76f4\u63a5\u200bpip\u200b\u5b89\u88c5\u200b\u4f7f\u7528\u200b\u3002

    Info

    \u200b\u8bf7\u200b\u4f7f\u7528\u200bPython3.6\u200b\u53ca\u200b\u4ee5\u4e0a\u200b\u7248\u672c\u200b\u3002 rapidocr_onnxruntime\u200b\u7cfb\u5217\u200b\u5e93\u200b\u76ee\u524d\u200b\u4ec5\u200b\u5728\u200bCPU\u200b\u4e0a\u200b\u652f\u6301\u200b\u8f83\u200b\u597d\u200b\uff0cGPU\u200b\u4e0a\u200b\u63a8\u7406\u200b\u5f88\u200b\u6162\u200b\uff0c\u200b\u8fd9\u200b\u4e00\u70b9\u200b\u53ef\u200b\u53c2\u8003\u200blink\u3002\u200b\u56e0\u6b64\u200b\u4e0d\u200b\u5efa\u8bae\u200b\u7528\u200bonnxruntime-gpu\u200b\u7248\u200b\u63a8\u7406\u200b\u3002GPU\u200b\u7aef\u200b\u63a8\u7406\u200b\u63a8\u8350\u200b\u7528\u200brapidocr_paddle

    pip install rapidocr-onnxruntime\n\n# \u200b\u57fa\u4e8e\u200bOpenVINO\npip install rapidocr_openvino\n

    \u200b\u5b89\u88c5\u200b\u901f\u5ea6\u6162\u200b\u7684\u8bdd\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u6307\u5b9a\u200b\u56fd\u5185\u200b\u7684\u200b\u5b89\u88c5\u200b\u6e90\u200b\uff0c\u200b\u5982\u200b\u4f7f\u7528\u200b\u6e05\u534e\u200b\u6e90\u200b\uff1a 

    pip install rapidocr_onnxruntime -i https://pypi.tuna.tsinghua.edu.cn/simple/\n

    \u200b\u4f9d\u8d56\u200b\u7684\u200b\u5305\u200b\u5982\u4e0b\u200b\uff1a

    Info

    \u200b\u5982\u679c\u200b\u5728\u200b\u5b89\u88c5\u200b\u8fc7\u7a0b\u200b\u4e2d\u200b\uff0c\u200b\u51fa\u73b0\u200b\u67d0\u4e2a\u200b\u4f9d\u8d56\u200b\u5305\u200b\u4e0d\u80fd\u200b\u6b63\u786e\u200b\u5b89\u88c5\u200b\u65f6\u200b\uff0c\u200b\u53ef\u200b\u5148\u200b\u5355\u72ec\u200b\u5b89\u88c5\u200b\u67d0\u4e2a\u200b\u4f9d\u8d56\u200b\u5305\u200b\uff0c\u200b\u4e4b\u540e\u200b\u518d\u200b\u5b89\u88c5\u200brapidocr_onnxruntime\u200b\u5373\u53ef\u200b\u3002

    pyclipper>=1.2.1\nonnxruntime>=1.7.0\nopencv_python>=4.5.1.48\nnumpy>=1.19.3\nsix>=1.15.0\nShapely>=1.7.1\nPyYAML\nPillow\n
    "},{"location":"install_usage/rapidocr/usage/","title":"\u4f7f\u7528\u200b\u8bf4\u660e","text":"

    \u200b\u8bf7\u200b\u79fb\u6b65\u200bAPI/RapidOCR\u200b\u67e5\u770b\u200b

    "},{"location":"install_usage/rapidocr_api/changelog/","title":"\u66f4\u65b0\u200b\u65e5\u5fd7","text":""},{"location":"install_usage/rapidocr_api/changelog/#2024-07-11-v007-update","title":"2024-07-11 v0.0.7 update","text":"
    • Merge PR #200
    "},{"location":"install_usage/rapidocr_api/changelog/#2024-03-04-v006-update","title":"\ud83e\udd652024-03-04 v0.0.6 update","text":"
    • \u200b\u4f18\u5316\u200b\u56fe\u50cf\u200b\u8bfb\u53d6\u200b\u90e8\u5206\u200b\uff0c\u200b\u4e0e\u200brapidocr_onnxruntime>=1.3.13\u200b\u7248\u672c\u200b\u4fdd\u6301\u4e00\u81f4\u200b
    • \u200b\u7edf\u4e00\u200b\u63a5\u53e3\u200b\u8fd4\u56de\u503c\u200b\u7c7b\u578b\u200b\u4e3a\u200b\u5b57\u5178\u200b
    "},{"location":"install_usage/rapidocr_api/changelog/#2023-05-22-api-update","title":"\ud83c\udf5c2023-05-22 api update","text":"
    • \u200b\u5c06\u200bAPI\u200b\u4ece\u200bocrweb\u200b\u4e2d\u89e3\u200b\u8026\u200b\u51fa\u6765\u200b\uff0c\u200b\u4f5c\u4e3a\u200b\u5355\u72ec\u200b\u6a21\u5757\u200b\u7ef4\u62a4\u200b\uff0c\u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200bAPI
    • rapidocr_web>0.1.6\u200b\u4e4b\u540e\u200b\uff0c\u200b\u5c06\u200b\u4e0d\u200b\u652f\u6301\u200bpip install rapidocr_web[api]\u200b\u65b9\u5f0f\u200b\u5b89\u88c5\u200b\uff0c\u200b\u53ef\u200b\u76f4\u63a5\u200bpip install rapidocr_api\u200b\u5b89\u88c5\u200b\u4f7f\u7528\u200b\u3002
    "},{"location":"install_usage/rapidocr_api/usage/","title":"\u5b89\u88c5\u200b\u53ca\u200b\u4f7f\u7528","text":"

    Note

    OCR API\u200b\u7684\u200b\u8f93\u51fa\u200b\u7ed3\u679c\u200b\u4e3a\u200b\u6700\u200b\u539f\u59cb\u200b\u7ed3\u679c\u200b\uff0c\u200b\u5927\u5bb6\u200b\u53ef\u200b\u6309\u200b\u9700\u200b\u8fdb\u4e00\u6b65\u200b\u6269\u5c55\u200b\u3002

    "},{"location":"install_usage/rapidocr_api/usage/#_1","title":"\u7b80\u4ecb","text":"
    • \u200b\u8be5\u200b\u5305\u662f\u200b\u5c06\u200brapidocr_onnxruntime\u200b\u5e93\u200b\u505a\u200b\u4e86\u200bAPI\u200b\u5c01\u88c5\u200b\uff0c\u200b\u91c7\u7528\u200bFastAPI + uvicorn\u200b\u5b9e\u73b0\u200b\u3002
    • \u200b\u5b9a\u4f4d\u200b\u662f\u200b\u4e00\u4e2a\u200b\u5feb\u901f\u200b\u8c03\u7528\u200brapidocr_onnxruntime\u200b\u7684\u200bAPI\u200b\u63a5\u53e3\u200b\uff0c\u200b\u6ca1\u6709\u200b\u8003\u8651\u200b\u591a\u200b\u8fdb\u7a0b\u200b\u5904\u7406\u200b\u5e76\u53d1\u200b\u8bf7\u6c42\u200b\uff0c\u200b\u5982\u679c\u200b\u6709\u200b\u8fd9\u200b\u9700\u6c42\u200b\u7684\u200b\u5c0f\u4f19\u4f34\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u770b\u770b\u200bgunicorn\u200b\u7b49\u200b\u3002
    "},{"location":"install_usage/rapidocr_api/usage/#_2","title":"\u5b89\u88c5","text":"
    pip install rapidocr_api\n
    "},{"location":"install_usage/rapidocr_api/usage/#_3","title":"\u542f\u52a8\u200b\u670d\u52a1\u7aef","text":"

    • \u200b\u7528\u6cd5\u200b:

      $ rapidocr_api -h\nusage: rapidocr_api [-h] [-ip IP] [-p PORT]\n\noptional arguments:\n-h, --help            show this help message and exit\n-ip IP, --ip IP       IP Address\n-p PORT, --port PORT  IP port\n

    • \u200b\u542f\u52a8\u200b:

      rapidocr_api -ip 0.0.0.0 -p 9003\n
    "},{"location":"install_usage/rapidocr_api/usage/#_4","title":"\u8c03\u7528","text":"

    Info

    \u200b\u8c03\u7528\u200b\u672c\u8d28\u200b\u5c31\u662f\u200b\u53d1\u9001\u200b\u4e00\u4e2a\u200bPOST\u200b\u8bf7\u6c42\u200b\uff0c\u200b\u4ee5\u4e0b\u200b\u7ed9\u51fa\u200bCurl\u200b\u548c\u200bPython\u200b\u7684\u200b\u8c03\u7528\u200b\u793a\u4f8b\u200b\uff0c\u200b\u5176\u4ed6\u200b\u7f16\u7a0b\u8bed\u8a00\u200b\u540c\u7406\u200b\u3002

    "},{"location":"install_usage/rapidocr_api/usage/#curl","title":"Curl\u200b\u8c03\u7528","text":"
    curl -F image_file=@1.png http://0.0.0.0:9003/ocr\n
    "},{"location":"install_usage/rapidocr_api/usage/#python","title":"Python\u200b\u8c03\u7528","text":"\u4ee5\u200b\u6587\u4ef6\u200b\u65b9\u5f0f\u200b\u53d1\u9001\u200bPOST\u200b\u8bf7\u6c42\u200b\u4ee5\u200bbase64\u200b\u65b9\u5f0f\u200b\u53d1\u9001\u200bPOST\u200b\u8bf7\u6c42\u200b 
    import requests\n\nurl = 'http://localhost:9003/ocr'\nimg_path = 'tests/test_files/ch_en_num.jpg'\n\nwith open(img_path, 'rb') as f:\n    file_dict = {'image_file': (img_path, f, 'image/png')}\n    response = requests.post(url, files=file_dict, timeout=60)\n\nprint(response.json())\n
    import base64\nimport requests\n\nurl = 'http://localhost:9003/ocr'\nimg_path = 'tests/test_files/ch_en_num.jpg'\n\nwith open(img_path, 'rb') as fa:\n    img_str = base64.b64encode(fa.read())\n\npayload = {'image_data': img_str}\nresponse = requests.post(url, data=payload, timeout=60)\n\nprint(response.json())\n
    "},{"location":"install_usage/rapidocr_api/usage/#api","title":"API\u200b\u8f93\u51fa","text":"
    • \u200b\u8f93\u51fa\u200b\u7ed3\u679c\u200b\u8bf4\u660e\u200b\uff1a

    • \u200b\u5982\u679c\u200b\u56fe\u50cf\u200b\u4e2d\u200b\u5b58\u5728\u200b\u6587\u5b57\u200b\uff0c\u200b\u5219\u200b\u4f1a\u200b\u8f93\u51fa\u200b\u5b57\u5178\u200b\u683c\u5f0f\u200b\uff0c\u200b\u5177\u4f53\u200b\u4ecb\u7ecd\u200b\u5982\u4e0b\u200b\uff1a

      ```python linenums=\"1\"\n{\n\"0\": {\n    \"rec_txt\": \"\u200b\u9999\u6e2f\u200b\u6df1\u5733\u200b\u62bd\u8840\u200b\uff0c\",  # \u200b\u8bc6\u522b\u200b\u7684\u200b\u6587\u672c\u200b\n    \"dt_boxes\": [  # \u200b\u4f9d\u6b21\u200b\u4e3a\u200b\u5de6\u4e0a\u89d2\u200b \u2192 \u200b\u53f3\u4e0a\u89d2\u200b \u2192 \u200b\u53f3\u4e0b\u89d2\u200b \u2192 \u200b\u5de6\u4e0b\u89d2\u200b\n        [265, 18],\n        [472, 231],\n        [431, 271],\n        [223, 59]\n    ],\n    \"score\": \"0.8176\"  # \u200b\u7f6e\u4fe1\u5ea6\u200b\n    }\n}\n```\n

    • \u200b\u5982\u679c\u200b\u6ca1\u6709\u200b\u68c0\u6d4b\u200b\u5230\u200b\u6587\u5b57\u200b\uff0c\u200b\u5219\u200b\u4f1a\u200b\u8f93\u51fa\u200b\u7a7a\u200b\u5b57\u5178\u200b({})\u3002

    • \u200b\u793a\u4f8b\u200b\u7ed3\u679c\u200b\uff1a

      {\n    \"0\": {\n        \"rec_txt\": \"8\u200b\u6708\u200b26\u200b\u65e5\u200b\uff01\",\n        \"dt_boxes\": [\n            [333.0, 72.0],\n            [545.0, 40.0],\n            [552.0, 90.0],\n            [341.0, 122.0]\n        ],\n        \"score\": \"0.7342\"\n    },\n    \"1\": {\n        \"rec_txt\": \"\u200b\u6fb3\u6d32\u200b\u540d\u6821\u200b\u62db\u751f\u200b\u4fe1\u606f\u200b\",\n        \"dt_boxes\": [\n            [266.0, 163.0],\n            [612.0, 116.0],\n            [619.0, 163.0],\n            [272.0, 210.0]\n        ],\n        \"score\": \"0.8262\"\n    },\n    \"2\": {\n        \"rec_txt\": \"\u200b\u89e3\u8bfb\u200b\uff01\uff01\",\n        \"dt_boxes\": [\n            [341.0, 187.0],\n            [595.0, 179.0],\n            [598.0, 288.0],\n            [344.0, 296.0]\n        ],\n        \"score\": \"0.6152\"\n    },\n    \"3\": {\n        \"rec_txt\": \"Rules...\",\n        \"dt_boxes\": [\n            [446.0, 321.0],\n            [560.0, 326.0],\n            [559.0, 352.0],\n            [445.0, 347.0]\n        ],\n        \"score\": \"0.8704\"\n    }\n}\n
    "},{"location":"install_usage/rapidocr_paddle/changelog/","title":"\u66f4\u65b0\u200b\u65e5\u5fd7","text":""},{"location":"install_usage/rapidocr_paddle/changelog/#2024-07-11-v1325-update","title":"2024-07-11 v1.3.25 update","text":"
    • \u200b\u53d6\u6d88\u200bShapely\u200b\u7248\u672c\u200b\u9650\u5236\u200b\uff0c\u200b\u5bf9\u5e94\u200b issue #202
    "},{"location":"install_usage/rapidocr_paddle/changelog/#2024-06-28-v1324-update","title":"2024-06-28 v1.3.24 update","text":"
    • \u200b\u5bf9\u5e94\u200brapidocr_onnxruntime==1.3.23
    "},{"location":"install_usage/rapidocr_paddle/changelog/#2024-05-18-v1321-update","title":"2024-05-18 v1.3.21 update","text":"
    • \u200b\u5bf9\u5e94\u200brapidocr_onnxruntime==1.3.20
    "},{"location":"install_usage/rapidocr_paddle/changelog/#2024-05-12-v1320-update","title":"2024-05-12 v1.3.20 update","text":"

    \u200b\u540c\u200brapidocr_onnxruntime Change log

    "},{"location":"install_usage/rapidocr_paddle/changelog/#2024-04-19-v1319-update","title":"2024-04-19 v1.3.19 update","text":"

    \u200b\u540c\u200brapidocr_onnxruntime Change log

    "},{"location":"install_usage/rapidocr_paddle/changelog/#2024-04-07-v1318-update","title":"2024-04-07 v1.3.18 update","text":"

    \u200b\u540c\u200brapidocr_onnxruntime Change log

    "},{"location":"install_usage/rapidocr_paddle/changelog/#2024-03-07-v1317-update","title":"2024-03-07 v1.3.17 update","text":"

    \u200b\u540c\u200brapidocr_onnxruntime Change log

    "},{"location":"install_usage/rapidocr_paddle/changelog/#2024-03-05-v1316-update","title":"2024-03-05 v1.3.16 update","text":"

    \u200b\u540c\u200brapidocr_onnxruntime Change log

    "},{"location":"install_usage/rapidocr_paddle/changelog/#2024-02-28-v1315-update","title":"2024-02-28 v1.3.15 update","text":"

    \u200b\u540c\u200brapidocr_onnxruntime Change log

    "},{"location":"install_usage/rapidocr_paddle/changelog/#2024-02-27-v1314-update","title":"2024-02-27 v1.3.14 update","text":"

    \u200b\u540c\u200brapidocr_onnxruntime Change log

    "},{"location":"install_usage/rapidocr_paddle/changelog/#2024-02-04-v1313-update","title":"2024-02-04 v1.3.13 update","text":"

    \u200b\u540c\u200brapidocr_onnxruntime Change log

    "},{"location":"install_usage/rapidocr_paddle/changelog/#2024-01-30-v1312-update","title":"2024-01-30 v1.3.12 update","text":"

    \u200b\u540c\u200brapidocr_onnxrutnime Change log

    "},{"location":"install_usage/rapidocr_paddle/changelog/#2023-10-25-v1310-update","title":"2023-10-25 v1.3.10 update","text":"

    \u200b\u4fee\u590d\u200bissue #133

    "},{"location":"install_usage/rapidocr_paddle/changelog/#2023-10-23-v139-update","title":"2023-10-23 v1.3.9 update","text":"

    \u200b\u9996\u6b21\u200b\u9002\u914d\u200bPaddlePaddle\u200b\u6846\u67b6\u200b\uff0c\u200b\u4f5c\u4e3a\u200bGPU\u200b\u7aef\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b

    "},{"location":"install_usage/rapidocr_paddle/usage/","title":"\u5b89\u88c5\u200b\u53ca\u200b\u4f7f\u7528","text":""},{"location":"install_usage/rapidocr_paddle/usage/#_1","title":"\u7b80\u4ecb","text":"

    PaddleOCR\u200b\u6a21\u578b\u200b\u672c\u8eab\u200b\u5c31\u662f\u200b\u7531\u200bPaddlePaddle\u200b\u6846\u67b6\u200b\u8bad\u7ec3\u200b\u800c\u6765\u200b\u7684\u200b\uff0cPaddlePaddle\u200b\u6846\u67b6\u200b\u539f\u751f\u200b\u652f\u6301\u200b\u5728\u200bCPU\u200b\u548c\u200bGPU\u200b\u4e0a\u200b\u63a8\u7406\u200bPaddleOCR\u200b\u76f8\u5173\u200b\u6a21\u578b\u200b\u3002

    rapidocr_paddle\u200b\u5305\u662f\u200b\u57fa\u4e8e\u200bPaddlePaddle\u200b\u6846\u67b6\u200b\u4f5c\u4e3a\u200b\u63a8\u7406\u200b\u5f15\u64ce\u200b\u7684\u200b\uff0c\u200b\u652f\u6301\u200bCPU\u200b\u548c\u200bGPU\u200b\u4e0a\u200b\u63a8\u7406\u200b\uff0c\u200b\u63a8\u8350\u200bGPU\u200b\u7aef\u200b\u4f7f\u7528\u200b\u3002\u200b\u539f\u56e0\u200b\u662f\u200bONNXRuntime\u200b\u548c\u200bOpenVINO\u200b\u5728\u200bGPU\u200b\u4e0a\u200b\u652f\u6301\u200b\u8f83\u5dee\u200b\u3002

    CPU\u200b\u7aef\u200b\u8fd8\u662f\u200b\u4ee5\u200brapidocr_onnxruntime\u200b\u548c\u200brapidocr_openvino\u200b\u4e3a\u4e3b\u200b\u3002\u200b\u6bd5\u7adf\u200bPaddlePaddle\u200b\u7684\u200bCPU\u200b\u7aef\u200b\u8fd8\u662f\u200b\u6bd4\u8f83\u200b\u91cd\u200b\u7684\u200b\u3002

    \u200b\u503c\u5f97\u200b\u8bf4\u660e\u200b\u7684\u200b\u662f\u200b\uff0c\u200b\u8fd9\u4e2a\u200b\u5305\u200b\u548c\u200bPaddleOCR\u200b\u76f8\u6bd4\u200b\uff0c\u200b\u4ee3\u7801\u200b\u57fa\u672c\u200b\u90fd\u200b\u662f\u200b\u4e00\u6837\u200b\u7684\u200b\uff0c\u200b\u53ea\u4e0d\u8fc7\u200b\u8fd9\u4e2a\u200b\u5e93\u200b\u5c06\u200b\u91cc\u9762\u200b\u6838\u5fc3\u200b\u63a8\u7406\u200b\u4ee3\u7801\u200b\u62bd\u200b\u4e86\u200b\u51fa\u6765\u200b\uff0c\u200b\u66f4\u52a0\u200b\u7cbe\u7b80\u200b\u800c\u5df2\u200b\u3002

    "},{"location":"install_usage/rapidocr_paddle/usage/#_2","title":"\u5b89\u88c5","text":"

    1. \u200b\u5b89\u88c5\u200bPaddlePaddle\u200b\u6846\u67b6\u200bGPU\u200b\u7248\u200b\uff0c\u200b\u5e76\u200b\u9a8c\u8bc1\u200b\u53ef\u884c\u6027\u200b\uff0c\u200b\u8be6\u7ec6\u200b\u53c2\u89c1\u200b: \u200b\u5b98\u65b9\u200b\u6559\u7a0b\u200b\u3002\u200b\u9a8c\u8bc1\u200b\u662f\u5426\u200b\u5b89\u88c5\u200b\u6210\u529f\u200b\u4ee3\u7801\u200b\u5982\u4e0b\u200b\uff1a

      import paddle\n\nprint(paddle.utils.run_check())\n# \u200b\u5982\u679c\u200b\u51fa\u73b0\u200bPaddlePaddle is installed successfully!\uff0c\u200b\u8bf4\u660e\u200b\u60a8\u200b\u5df2\u200b\u6210\u529f\u200b\u5b89\u88c5\u200b\u3002\n

    2. \u200b\u5b89\u88c5\u200brapidocr_paddle

      pip install rapidocr_paddle\n
    "},{"location":"install_usage/rapidocr_paddle/usage/#_3","title":"\u4f7f\u7528","text":"
    import cv2\n\nfrom rapidocr_paddle import RapidOCR\n\n# \u200b\u6ce8\u610f\u200b\u8fd9\u91cc\u200b\u7684\u200b\u53c2\u6570\u200b\nengine = RapidOCR(det_use_cuda=True, cls_use_cuda=True, rec_use_cuda=True)\n\nimage_path = \"tests/test_files/ch_en_num.jpg\"\nresult, elapse_list = engine(image_path)\n

    \u200b\u5176\u4ed6\u200b\u4f7f\u7528\u200b\u8be6\u60c5\u200b\uff0c\u200b\u540c\u200brapidocor_onnxruntime\u200b\u7cfb\u5217\u200b\uff0c\u200b\u53c2\u89c1\u200b: link

    "},{"location":"install_usage/rapidocr_paddle/usage/#_4","title":"\u63a8\u7406\u200b\u901f\u5ea6\u200b\u6bd4\u8f83","text":"

    \u200b\u76f8\u5173\u200b\u6d4b\u8bc4\u200b\u4ee3\u7801\u200b\uff0c\u200b\u53c2\u89c1\u200bAI Studio\uff0cFork\u200b\u53ef\u200b\u76f4\u63a5\u200b\u8fd0\u884c\u200b\u67e5\u770b\u200b\u3002\u200b\u4e0d\u8981\u200b\u53ea\u200b\u63a8\u7406\u200b\u4e00\u5f20\u200b\u6765\u200b\u6d4b\u8bd5\u200b\u63a8\u7406\u200b\u901f\u5ea6\u200b\uff0c\u200b\u9700\u8981\u200b\u5148\u200b\u63a8\u7406\u200b\u4e00\u5f20\u200b\u4f5c\u4e3a\u200b\u9884\u70ed\u200b\uff0c\u200b\u540e\u7eed\u200b\u518d\u200b\u770b\u200b\u63a8\u7406\u200b\u901f\u5ea6\u200b\u3002

    \u200b\u7ecf\u8fc7\u200b\u521d\u6b65\u200b\u7c97\u7565\u200b\u4f30\u8ba1\u200b\uff0c\u200b\u540c\u200b\u4e00\u5f20\u200b\u56fe\u50cf\u200b\uff0c\u200b\u63a8\u7406\u200b10\u200b\u6b21\u200b\uff0c\u200b\u8017\u65f6\u200b\u60c5\u51b5\u200b\u89c1\u200b\u4e0b\u8868\u200b\uff1a

    \u200b\u63a8\u7406\u200b\u5e93\u200b \u200b\u5e73\u5747\u200b\u8017\u65f6\u200b(s/img) \u200b\u8fd0\u884c\u200b\u73af\u5883\u200b rapidocr_onnxruntime 1.6505 CPU 2 Cores RAM 16GB rapidocr_paddle[GPU] 0.0508 CPU 2 Cores RAM 16GB GPU Tesla V100 16G"},{"location":"install_usage/rapidocr_web/changelog/","title":"\u66f4\u65b0\u200b\u65e5\u5fd7","text":""},{"location":"install_usage/rapidocr_web/changelog/#2024-07-08-v0110-update","title":"2024-07-08 v0.1.10 update:","text":"
    • \u200b\u4fee\u590d\u200bissue #197
    "},{"location":"install_usage/rapidocr_web/changelog/#2023-05-20-ocrweb-update","title":"\u27642023-05-20 ocrweb update:","text":"
    • \u200b\u589e\u52a0\u200b\u684c\u9762\u7248\u200bRapidOCRWeb\uff0c\u200b\u8be6\u60c5\u200b\u53ef\u200b\u53c2\u89c1\u200bRapidOCRWeb\u200b\u684c\u9762\u7248\u200b\u4f7f\u7528\u200b\u6559\u7a0b\u200b
    • \u200b\u5bf9\u200b\u4ed3\u5e93\u200b\u6587\u6863\u200b\u505a\u200b\u4e86\u200b\u6574\u7406\u200b\uff0c\u200b\u5927\u90e8\u5206\u200b\u6587\u6863\u200b\u653e\u5230\u200b\u4e86\u200bWiki
    "},{"location":"install_usage/rapidocr_web/changelog/#2023-05-14-ocrweb-v015-update","title":"\ud83c\udf392023-05-14 ocrweb v0.1.5 update:","text":"
    • \u200b\u589e\u52a0\u200b\u754c\u9762\u200b\u7248\u200b\u8fd4\u56de\u200b\u5750\u6807\u200b\u6846\u200b\u7684\u200b\u8fd4\u56de\u503c\u200b(issue #85)
    • API\u200b\u6a21\u5f0f\u200b\u589e\u52a0\u200bbase64\u200b\u683c\u5f0f\u200b\u4f20\u5165\u200b
    • \u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b\uff1alink
    "},{"location":"install_usage/rapidocr_web/changelog/#2023-04-16-ocrweb-v011-update","title":"\ud83c\udff82023-04-16 ocrweb v0.1.1 update:","text":"
    • API\u200b\u90e8\u7f72\u200b\u6539\u4e3a\u200bFastAPI\u200b\u5e93\u200b\u652f\u6301\u200b
    • \u200b\u5c06\u200bAPI\u200b\u6a21\u5f0f\u200b\u4e0e\u200bWeb\u200b\u89e3\u200b\u8026\u5408\u200b\uff0c\u200b\u53ef\u200b\u901a\u8fc7\u200bpip install rapidocr_web[api]\u200b\u6765\u200b\u9009\u62e9\u6027\u200b\u5b89\u88c5\u200b
    • \u200b\u8be6\u60c5\u200b\u53c2\u89c1\u200b\uff1alink
    "},{"location":"install_usage/rapidocr_web/desktop_usage/","title":"\u684c\u9762\u7248\u200b\u4f7f\u7528\u200b\u6559\u7a0b","text":""},{"location":"install_usage/rapidocr_web/desktop_usage/#_1","title":"\u5f15\u8a00","text":"
    • \u200b\u8bf4\u660e\u200b\uff1a\u200b\u684c\u9762\u7248\u200b\u6307\u200b\u7684\u200b\u662f\u200b\u53ef\u4ee5\u200b\u76f4\u63a5\u200b\u89e3\u538b\u200b\uff0c\u200b\u53cc\u51fb\u200b\u5373\u53ef\u200b\u8fd0\u884c\u200b\u7684\u200b\u7248\u672c\u200b\u3002
    • \u200b\u901a\u4fd7\u200b\u6765\u8bf4\u200b\uff0c\u200b\u5bf9\u200brapidocr_web\u200b\u505a\u200b\u4e86\u200b\u6253\u5305\u200b\uff0c\u200b\u5c06\u200b\u76f8\u5173\u200b\u4f9d\u8d56\u200b\u5168\u90e8\u200b\u653e\u5230\u200b\u4e00\u4e2a\u200bzip\u200b\u5305\u4e2d\u200b\uff0c\u200b\u4e0d\u200b\u9700\u8981\u200b\u672c\u5730\u200b\u6709\u200b\u989d\u5916\u200b\u7684\u200b\u73af\u5883\u200b\uff0c\u200b\u964d\u4f4e\u200b\u4f7f\u7528\u200b\u95e8\u69db\u200b\u3002
    • \u200b\u4e0b\u9762\u200b\u4f1a\u4ee5\u200bWindows\u200b\u7248\u4e3a\u4f8b\u200b\uff0c\u200b\u4f5c\u200b\u7b80\u8981\u200b\u8bf4\u660e\u200b\u3002
    "},{"location":"install_usage/rapidocr_web/desktop_usage/#_2","title":"\u4f7f\u7528\u200b\u6b65\u9aa4","text":"

    1. \u200b\u4e0b\u8f7d\u200b\u5bf9\u5e94\u200b\u7684\u200bzip\u200b\u5305\u200b

      • \u200b\u76ee\u524d\u200b\u5df2\u6709\u200b\u7684\u200bzip\u200b\u5305\u200b\u5982\u4e0b\u200b\uff1a

      • \u200b\u4e0b\u8f7d\u65b9\u5f0f\u200b: Github | \u200b\u767e\u5ea6\u7f51\u200b\u76d8\u200b | QQ\u200b\u7fa4\u200b\u5171\u4eab\u200b\uff08\u200b\u7fa4\u53f7\u200b\uff1a755960114\uff09

    2. \u200b\u89e3\u538b\u200b\u76ee\u5f55\u200b\u5982\u4e0b\u200b\u793a\u4f8b\u200b

      .\n\u251c\u2500\u2500 api-ms-win-core-console-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-datetime-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-debug-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-errorhandling-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-file-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-file-l1-2-0.dll\n\u251c\u2500\u2500 api-ms-win-core-file-l2-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-handle-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-heap-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-interlocked-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-libraryloader-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-localization-l1-2-0.dll\n\u251c\u2500\u2500 api-ms-win-core-memory-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-namedpipe-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-processenvironment-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-processthreads-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-processthreads-l1-1-1.dll\n\u251c\u2500\u2500 api-ms-win-core-profile-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-rtlsupport-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-string-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-synch-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-synch-l1-2-0.dll\n\u251c\u2500\u2500 api-ms-win-core-sysinfo-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-timezone-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-core-util-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-conio-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-convert-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-environment-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-filesystem-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-heap-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-locale-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-math-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-process-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-runtime-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-stdio-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-string-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-time-l1-1-0.dll\n\u251c\u2500\u2500 api-ms-win-crt-utility-l1-1-0.dll\n\u251c\u2500\u2500 _asyncio.pyd\n\u251c\u2500\u2500 base_library.zip\n\u251c\u2500\u2500 _bz2.pyd\n\u251c\u2500\u2500 _ctypes.pyd\n\u251c\u2500\u2500 cv2\n\u251c\u2500\u2500 _decimal.pyd\n\u251c\u2500\u2500 _hashlib.pyd\n\u251c\u2500\u2500 importlib_metadata-6.6.0.dist-info\n\u251c\u2500\u2500 libcrypto-1_1.dll\n\u251c\u2500\u2500 libopenblas.XWYDX2IKJW2NMTWSFYNGFUWKQU3LYTCZ.gfortran-win_amd64.dll\n\u251c\u2500\u2500 libssl-1_1.dll\n\u251c\u2500\u2500 _lzma.pyd\n\u251c\u2500\u2500 markupsafe\n\u251c\u2500\u2500 MSVCP140.dll\n\u251c\u2500\u2500 _multiprocessing.pyd\n\u251c\u2500\u2500 numpy\n\u251c\u2500\u2500 onnxruntime\n\u251c\u2500\u2500 _overlapped.pyd\n\u251c\u2500\u2500 PIL\n\u251c\u2500\u2500 pyclipper\n\u251c\u2500\u2500 pyexpat.pyd\n\u251c\u2500\u2500 python37.dll\n\u251c\u2500\u2500 python3.dll\n\u251c\u2500\u2500 _queue.pyd\n\u251c\u2500\u2500 rapidocr_onnxruntime\n\u251c\u2500\u2500 RapidOCRWeb.exe\n\u251c\u2500\u2500 select.pyd\n\u251c\u2500\u2500 shapely\n\u251c\u2500\u2500 Shapely.libs\n\u251c\u2500\u2500 _socket.pyd\n\u251c\u2500\u2500 _ssl.pyd\n\u251c\u2500\u2500 static\n\u251c\u2500\u2500 templates\n\u251c\u2500\u2500 ucrtbase.dll\n\u251c\u2500\u2500 unicodedata.pyd\n\u251c\u2500\u2500 VCRUNTIME140_1.dll\n\u251c\u2500\u2500 VCRUNTIME140.dll\n\u2514\u2500\u2500 yaml\n

    3. \u200b\u53cc\u51fb\u200bRapidOCRWeb.exe\u200b\u8fd0\u884c\u200b\uff0c\u200b\u754c\u9762\u200b\u5982\u4e0b\u200b\u56fe\u200b\u6240\u793a\u200b\uff1a

    4. \u200b\u6d4f\u89c8\u5668\u200b\u4e2d\u200b\u6253\u5f00\u200bhttp://localhost:9003/\uff0c\u200b\u5373\u53ef\u200b\u770b\u5230\u200b\u719f\u6089\u200b\u7684\u200bRapidOCRWeb\u200b\u754c\u9762\u200b\u3002

      Note

      \u200b\u5982\u679c\u200b\u9047\u5230\u200b\u6d4f\u89c8\u5668\u200b\u4e0d\u200b\u663e\u793a\u200b\u754c\u9762\u200b\u7684\u200b\u60c5\u51b5\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u5c1d\u8bd5\u200b\u5728\u200b\u9ed1\u200b\u6846\u4e0a\u200b\u6309\u200bCtrl + C

      5. "},{"location":"install_usage/rapidocr_web/nuitka_package/","title":"Nuitka\u200b\u6253\u5305","text":"

      --by DeadWood8

      "},{"location":"install_usage/rapidocr_web/nuitka_package/#_1","title":"\u6253\u5305\u200b\u73af\u5883","text":"
      • OS: Windows11
      • Python: 3.8.10
      • rapidocr_onnxruntime: 1.2.0
      • nuitka: 1.5.3
      • onnxruntime: 1.14.0
      "},{"location":"install_usage/rapidocr_web/nuitka_package/#_2","title":"\u6253\u5305\u200b\u6b65\u9aa4","text":"
      1. \u200b\u5b89\u88c5\u200bNuitka 
        pip install nuitka\n
        \u200b\u6ce8\u200b\uff1a\u200b\u7b2c\u4e00\u6b21\u200b\u5b89\u88c5\u200b\u4f1a\u200b\u81ea\u52a8\u200b\u4e0b\u8f7d\u200bmingw\u200b\u548c\u200bccache\uff0c\u200b\u4e5f\u200b\u53ef\u4ee5\u200b\u624b\u52a8\u200b\u914d\u7f6e\u200b\uff0c\u200b\u81ea\u884c\u200b\u67d0\u5ea6\u200b\u3002

      2. \u200b\u4fee\u6539\u200brapidocr-onnxruntime\u200b\u6e90\u7801\u200b\uff08\u200b\u4fee\u6539\u200b\u540e\u200b\u53ef\u4ee5\u200b\u5c06\u200b\u6240\u6709\u200b\u4f9d\u8d56\u200b\u6253\u5305\u200b\u8fdb\u200b\u6587\u4ef6\u200b\uff09 !!! note rapidocr_onnxruntime>=1.2.8\u200b\u4ee5\u540e\u200b\u4e0d\u7528\u200b\u518d\u200b\u624b\u52a8\u200b\u4fee\u6539\u200b\u4e0b\u9762\u200b\u4ee3\u7801\u200b\uff0c\u200b\u5df2\u7ecf\u200b\u505a\u200b\u4e86\u200b\u4fee\u6539\u200b\u3002\u200b\u53ef\u4ee5\u200b\u8df3\u8fc7\u200b\u8be5\u6b65\u200b\u3002\"

      3. \u200b\u8fdb\u5165\u200brapidocr-onnxruntime\u200b\u5b89\u88c5\u200b\u4f4d\u7f6e\u200b\uff0c\u200b\u4e00\u822c\u200b\u5728\u200bLib\\site-packages\\rapidocr_onnxruntime\u200b\u6216\u8005\u200b\u4f60\u200b\u8bbe\u7f6e\u200b\u7684\u200b\u865a\u62df\u73af\u5883\u200b\u4e0b\u200b\u3002

      4. \u200b\u7528\u200b\u7f16\u8f91\u5668\u200b\u6253\u5f00\u200brapid_ocr_api.py\uff0c\u200b\u5bf9\u200b39-52\u200b\u884c\u200b\u8fdb\u884c\u200b\u4fee\u6539\u200b\uff0c\u200b\u5982\u4e0b\u200b\u56fe\u200b\uff1a
      5. nuitka\u200b\u6253\u5305\u200b 
        cd rapidocr_web\nnuitka --mingw64 --standalone --show-memory --show-progress --nofollow-import-to=tkinter --output-dir=out ocrweb.py\n
      6. \u200b\u5982\u4e0b\u200b\u56fe\u200b\u6240\u793a\u200b\uff1a
      7. \u200b\u62f7\u8d1d\u200b\u9759\u6001\u200b\u6587\u4ef6\u200b
        • \u200b\u6253\u5305\u200b\u540e\u200b\u7684\u200b\u6587\u4ef6\u200b\u4f4d\u4e8e\u200b\u5f53\u524d\u200b\u4f4d\u7f6e\u200b\u7684\u200bout\\ocrweb.dist\u200b\u76ee\u5f55\u200b\u4e0b\u200b\uff0c\u200b\u9700\u8981\u200b\u5c06\u200bweb\u200b\u9879\u76ee\u200b\u548c\u200brapidocr-onnxruntime\u200b\u76f8\u5173\u200b\u6587\u4ef6\u200b\u62f7\u8d1d\u5230\u200b\u6b64\u200b\u76ee\u5f55\u200b\u3002
        • \u200b\u62f7\u8d1d\u200brapidocr_web\u200b\u76ee\u5f55\u200bstatic\u200b\u548c\u200btemplates\u200b\u4e24\u4e2a\u200b\u6587\u4ef6\u5939\u200b\u5168\u90e8\u200b\u62f7\u8d1d\u5230\u200bout\\ocrweb.dist\u200b\u4e0b\u200b
        • \u200b\u5728\u200bout\\ocrweb.dist\u200b\u521b\u5efa\u200brapidocr_onnxruntime\u200b\u6587\u4ef6\u5939\u200b\uff0c\u200b\u5c06\u200bLib\\site-packages\\rapidocr_onnxruntime\u200b\u76ee\u5f55\u200b\u4e0b\u200b\u7684\u200bconfig.yaml\u200b\u548c\u200bmodels\u200b\u6587\u4ef6\u5939\u200b\u62f7\u8d1d\u5230\u200bout\\ocrweb.dist\\rapidocr_onnxruntime\u200b\u6587\u4ef6\u5939\u200b\u5185\u200b
      8. \u200b\u8fd0\u884c\u200b\u7a0b\u5e8f\u200b\u3002\u200b\u8fdb\u5165\u200bout\\ocrweb.dist\uff0c\u200b\u76f4\u63a5\u200b\u53cc\u51fb\u200bocrweb.exe\u200b\u8fd0\u884c\u200b\u3002
      9. \u200b\u6253\u5305\u200b\u597d\u200b\u7684\u200bexe\u200b\u4e0b\u8f7d\u200b\uff1a\u200b\u767e\u5ea6\u7f51\u200b\u76d8\u200b | Google Drive | Gitee
      "},{"location":"install_usage/rapidocr_web/nuitka_package/#_3","title":"\u8865\u5145","text":"
      • \u200b\u5982\u679c\u200b\u4e0d\u60f3\u200b\u8fd0\u884c\u200b\u7a0b\u5e8f\u200b\u540e\u200b\u6709\u200b\u9ed1\u6846\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u5728\u200b\u6253\u5305\u200b\u547d\u4ee4\u200b\u4e2d\u200b\u52a0\u5165\u200b\u4ee5\u4e0b\u200b\u53c2\u6570\u200b --windows-disable-console
      • \u200b\u5b8c\u6574\u200b\u547d\u4ee4\u200b\u4e3a\u200b\uff1a 
        nuitka --mingw64 --standalone --show-memory --show-progress --nofollow-import-to=tkinter --windows-disable-console --output-dir=out ocrweb.py\n
      "},{"location":"install_usage/rapidocr_web/ocrweb_multi/","title":"\u591a\u200b\u8bed\u8a00\u200b\u7248\u672c\u200b\u90e8\u7f72","text":""},{"location":"install_usage/rapidocr_web/ocrweb_multi/#_1","title":"\u7b80\u4ecb","text":"
      • \u200b\u540c\u65f6\u200b\u652f\u6301\u200b\u591a\u79cd\u8bed\u8a00\u200b\uff0c\u200b\u53ef\u200b\u901a\u8fc7\u200b\u63a5\u53e3\u200b\u53c2\u6570\u200b\u914d\u7f6e\u200b\u8bed\u8a00\u200b\u53ca\u200b\u9884\u6d4b\u200b\u8fc7\u7a0b\u200b\u4e2d\u200b\u7684\u200b\u5176\u4ed6\u200b\u53c2\u6570\u200b
      • \u200b\u8c03\u6574\u200b\u7ed3\u679c\u200b\u5c55\u793a\u200b\u65b9\u5f0f\u200b\u4e3a\u200b\u57fa\u4e8e\u200bcanvas, \u200b\u51cf\u5c11\u200b\u540e\u200b\u7aef\u200b\u5904\u7406\u200b\u548c\u200b\u63a5\u53e3\u200b\u6570\u636e\u4f20\u8f93\u200b
      • \u200b\u9884\u6d4b\u200b\u63a5\u53e3\u200b\u6dfb\u52a0\u200bToken\u200b\u9a8c\u8bc1\u200b\u652f\u6301\u200b
      • \u200b\u6dfb\u52a0\u200bpyinstaller\u200b\u6253\u5305\u200b\u811a\u672c\u200b\uff0c\u200b\u7b80\u5316\u200b\u5b89\u88c5\u200b\u6b65\u9aa4\u200b
      • \u200b\u793a\u4f8b\u200b\u6253\u5305\u200b\u7ed3\u679c\u200b\uff1apyinstaller demo
      "},{"location":"install_usage/rapidocr_web/ocrweb_multi/#_2","title":"\u5b89\u88c5","text":"
      1. \u200b\u514b\u9686\u200b\u9879\u76ee\u200b\u5230\u200b\u672c\u5730\u200b 
        git clone -b main https://github.com/RapidAI/RapidOCR.git\n
      2. \u200b\u5b89\u88c5\u200b\u8fd0\u884c\u200b\u6240\u200b\u9700\u200b\u73af\u5883\u200b 
        cd ocrweb_multi\npip install -r requirements.txt -i https://pypi.douban.com/simple/\n
      "},{"location":"install_usage/rapidocr_web/ocrweb_multi/#_3","title":"\u8fd0\u884c\u200b\u6b65\u9aa4","text":"
      1. \u200b\u4e0b\u8f7d\u200bmodels\u200b\u6587\u4ef6\u200b\u5230\u200b\u5f53\u524d\u76ee\u5f55\u200b\u4e0b\u200b
        • \u200b\u4e0b\u8f7d\u200b\u94fe\u63a5\u200b\uff1a\u200b\u767e\u5ea6\u7f51\u200b\u76d8\u200b | Google Drive
        • \u200b\u6700\u7ec8\u200b\u76ee\u5f55\u200b\u7ed3\u6784\u200b\u5982\u4e0b\u200b\uff1a 
          ocr_web_multi\n    |-- README.md\n    |-- build.py\n    |-- config.yaml\n    |-- main.py\n    |-- main.spec\n    |-- models\n    |   |-- Multilingual_PP-OCRv3_det_infer.onnx\n    |   |-- ch_PP-OCRv3_det_infer.onnx\n    |   |-- ch_PP-OCRv3_rec_infer.meta.onnx\n    |   |-- ch_ppocr_mobile_v2.0_cls_infer.meta.onnx\n    |   |-- chinese_cht_PP-OCRv3_rec_infer.meta.onnx\n    |   |-- en_PP-OCRv3_det_infer.onnx\n    |   |-- en_PP-OCRv3_rec_infer.meta.onnx\n    |   `-- japan_PP-OCRv3_rec_infer.meta.onnx\n    |-- rapidocr\n    |   |-- __init__.py\n    |   |-- classify.py\n    |   |-- detect.py\n    |   |-- detect_process.py\n    |   |-- main.py\n    |   |-- rapid_ocr_api.py\n    |   `-- recognize.py\n    |-- requirements.txt\n    |-- static\n    |   |-- css\n    |   |-- favicon.ico\n    |   |-- hint.svg\n    |   |-- index.html\n    |   `-- js\n    |-- utils\n    |   |-- config.py\n    |   `-- utils.py\n    |-- wrapper.c\n    `-- wrapper.rc\n
      2. \u200b\u8fd0\u884c\u200bmain.py 
        python main.py\n
      3. \u200b\u6253\u5f00\u200b http://127.0.0.1:8001 \u200b\u5373\u53ef\u200b\uff0c enjoy it!
      "},{"location":"install_usage/rapidocr_web/pyinstaller/","title":"PyInstaller\u200b\u6253\u5305","text":"

      \u200b\u53c2\u8003\u200bActions\u200b\u4e2d\u200b\u5199\u6cd5\u200b\uff0c\u200b\u8be6\u60c5\u200b\u79fb\u6b65\u200b\uff1apackage_ocrweb.yml

      "},{"location":"install_usage/rapidocr_web/usage/","title":"\u5b89\u88c5\u200b\u53ca\u200b\u4f7f\u7528","text":""},{"location":"install_usage/rapidocr_web/usage/#_1","title":"\u7b80\u4ecb","text":"
      • \u200b\u8be5\u5e93\u200b\u662f\u200brapidocr_onnxruntime\u200b\u7684\u200bweb\u200b\u7248\u672c\u200b\uff0c\u200b\u4f9d\u8d56\u200b\u6700\u65b0\u200b\u7248\u672c\u200b\u7684\u200brapidocr_onnxruntime\u200b\u5e93\u200b\u3002
      • \u200b\u5982\u679c\u200b\u60f3\u8981\u200b\u79bb\u7ebf\u200b\u90e8\u7f72\u200b\uff0c\u200b\u53ef\u4ee5\u200b\u5148\u200b\u624b\u52a8\u200b\u4e0b\u8f7d\u200brapidocr_onnxruntime whl\u200b\u5305\u200b\uff0c\u200b\u518d\u200b\u624b\u52a8\u200b\u5b89\u88c5\u200brapidocr_web whl\u200b\u5305\u6765\u200b\u4f7f\u7528\u200b\u3002

      • \u200b\u7f51\u9875\u200b\u4e0a\u200b\u663e\u793a\u200b\u7684\u200b\u63a8\u7406\u200b\u65f6\u95f4\u200b\u5177\u4f53\u200b\u89e3\u91ca\u200b\u5982\u4e0b\u200b\uff1a

      "},{"location":"install_usage/rapidocr_web/usage/#_2","title":"\u5b89\u88c5","text":"
      pip install rapidocr_web\n
      "},{"location":"install_usage/rapidocr_web/usage/#_3","title":"\u4f7f\u7528","text":""},{"location":"install_usage/rapidocr_web/usage/#_4","title":"\u7528\u6cd5\u200b:","text":"
      $ rapidocr_web -h\nusage: rapidocr_web [-h] [-ip IP] [-p PORT]\n\noptional arguments:\n-h, --help            show this help message and exit\n-ip IP, --ip IP       IP Address\n-p PORT, --port PORT  IP port\n
      "},{"location":"install_usage/rapidocr_web/usage/#_5","title":"\u8fd0\u884c\u200b:","text":"
      rapidocr_web -ip 0.0.0.0 -p 9003\n
      "},{"location":"install_usage/rapidocr_web/usage/#httplocalhost9003enjoy-it","title":"\u6d4f\u89c8\u5668\u200b\u6253\u5f00\u200b http://localhost:9003/\uff0cenjoy it!","text":"

      Info

      \u200b\u6d4f\u89c8\u5668\u200b\u6253\u5f00\u200b\u7684\u200b\u7f51\u5740\u200b\u662f\u200bhttp\u200b\u7684\u200b\uff0c\u200b\u4e0d\u662f\u200bhttps\u3002

      "},{"location":"blog/category/general/","title":"General","text":""},{"location":"blog/category/%E6%A8%A1%E5%9E%8B%E7%9B%B8%E5%85%B3/","title":"\u6a21\u578b\u200b\u76f8\u5173","text":""},{"location":"blog/category/%E6%8E%A8%E7%90%86%E5%BC%95%E6%93%8E/","title":"\u63a8\u7406\u200b\u5f15\u64ce","text":""},{"location":"blog/category/fqa/","title":"FQA","text":""},{"location":"blog/category/ocr%E7%9B%B8%E5%85%B3%E9%A1%B9%E7%9B%AE/","title":"OCR\u200b\u76f8\u5173\u200b\u9879\u76ee","text":""}]} \ No newline at end of file diff --git a/sitemap.xml b/sitemap.xml new file mode 100644 index 00000000..43cd04bd --- /dev/null +++ b/sitemap.xml @@ -0,0 +1,248 @@ + + + + https://rapidai.github.io/RapidOCRDocs/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/business_support/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/communicate/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/online_demo/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/quickstart/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/related_projects/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/sponsor/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/visualization/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/10/02/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98-faq/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2024/07/13/how-to-use-directml/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/10/03/optim-tutorial/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/08/20/%E5%85%B6%E4%BB%96%E7%BC%96%E7%A8%8B%E8%AF%AD%E8%A8%80%E6%94%AF%E6%8C%81/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2023/10/08/read-dict-onnx/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/09/27/%E8%BD%AC%E6%8D%A2paddleocr%E6%A8%A1%E5%9E%8B%E4%B8%BAonnx/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2023/10/17/%E5%A6%82%E4%BD%95%E6%9B%B4%E6%8D%A2%E5%85%B6%E4%BB%96%E6%A3%80%E6%B5%8B%E5%92%8C%E8%AF%86%E5%88%AB%E6%A8%A1%E5%9E%8B/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2024/04/12/%E5%B7%B2%E6%9C%89onnx%E6%A8%A1%E5%9E%8B%E4%B8%8B%E8%BD%BD/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/04/16/%E5%BC%80%E6%BA%90ocr%E6%A8%A1%E5%9E%8B%E5%AF%B9%E6%AF%94/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/09/28/%E6%94%AF%E6%8C%81%E8%AF%86%E5%88%AB%E8%AF%AD%E8%A8%80/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/09/22/inference-summary/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/10/04/which-inference/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/09/23/onnxruntime-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/09/24/onnxruntime-gpu%E6%8E%A8%E7%90%86/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/09/26/openvino-cpu%E6%8E%A8%E7%90%86%E4%BC%98%E5%8C%96/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/09/25/openvino-gpu%E6%8E%A8%E7%90%86/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/09/30/inference-summary/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/2022/10/01/inference-summary/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/api/RapidOCR/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/api/VisRes/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr/changelog/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr/cli/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr/config_yaml/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr/install/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr/usage/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_api/changelog/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_api/usage/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_paddle/changelog/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_paddle/usage/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_web/changelog/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_web/desktop_usage/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_web/nuitka_package/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_web/ocrweb_multi/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_web/pyinstaller/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_web/usage/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/category/general/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/category/%E6%A8%A1%E5%9E%8B%E7%9B%B8%E5%85%B3/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/category/%E6%8E%A8%E7%90%86%E5%BC%95%E6%93%8E/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/category/fqa/ + 2024-07-15 + daily + + + https://rapidai.github.io/RapidOCRDocs/blog/category/ocr%E7%9B%B8%E5%85%B3%E9%A1%B9%E7%9B%AE/ + 2024-07-15 + daily + + \ No newline at end of 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