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Migrate tutorial to use the quarto framework (#63)
* Minimal quarto setup (#56) minimal setup to generate the tutorials with quarto * Add front matter (#57) * add missing front matters (#58) * add thumbnails (#59) * fix typo categories tags (#60) * Update theme customization (#61) Co-authored-by: Paolla Olsen <paollaolsen@gmail.com> * move to quarto actions * cleanup * add contribution guide --------- Co-authored-by: Paolla Olsen <paollaolsen@gmail.com>
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| tutorials/assets/* binary | ||
| tutorial/_static/img/* binary |
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| name: Generate docs and deploy to GitHub Pages | ||
| on: | ||
| workflow_dispatch: | ||
| push: | ||
| branches: [master] | ||
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| jobs: | ||
| deploy: | ||
| name: Deploy tutorials - ${{ matrix.os }}, ${{ matrix.python-version }}, ${{ matrix.pytorch-version }} | ||
| runs-on: ${{ matrix.os }}-latest | ||
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| strategy: | ||
| fail-fast: true | ||
| matrix: | ||
| os: ['Ubuntu'] | ||
| python-version: ['3.10'] | ||
| pytorch-version: ['2.0.1'] | ||
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| steps: | ||
| - uses: actions/checkout@v3 | ||
| - name: Setup conda dependencies | ||
| uses: conda-incubator/setup-miniconda@v2 | ||
| with: | ||
| auto-update-conda: true | ||
| python-version: ${{ matrix.python-version }} | ||
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| - name: Install dependencies | ||
| shell: bash -l {0} | ||
| run: | | ||
| conda install pytorch=${{ matrix.pytorch-version }} torchvision cpuonly -c pytorch | ||
| pip install -r requirements.txt | ||
| pip install -r requirements-dev.txt; | ||
| - uses: quarto-dev/quarto-actions/setup@v2 | ||
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| - name: Render Quarto Project | ||
| uses: quarto-dev/quarto-actions/render@v2 | ||
| with: | ||
| to: html | ||
| path: . | ||
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| - name: Deploy to GitHub Pages | ||
| uses: peaceiris/actions-gh-pages@v3 | ||
| with: | ||
| github_token: ${{ secrets.GITHUB_TOKEN }} | ||
| force_orphan: true | ||
| publish_dir: ./_site | ||
| user_name: github-actions[bot] | ||
| user_email: 41898282+github-actions[bot]@users.noreply.github.com |
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| Original file line number | Diff line number | Diff line change |
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| @@ -1,10 +1,126 @@ | ||
| # tutorials | ||
| # Kornia tutorials | ||
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| ## development | ||
| The kornia tutorials provide from basic to advanced tutorials for [kornia library](https://github.com/kornia/kornia). | ||
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| To compile the docs in local to debug | ||
| These tutorials are made by the community for the community. To shows how to use the Kornia API, and also show how these | ||
| computer vision algorithms can be used in a variety of scenarios. | ||
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| ```bash | ||
| make setup | ||
| make build | ||
| The kornia tutorials uses the [quarto](https://quarto.org/) framework to generate the website from jupyter notebooks. | ||
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| ## Guide | ||
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| ### Step-by-step setup environment | ||
| 1. Install [quarto](https://quarto.org/) following the official docs: https://quarto.org/docs/get-started/ | ||
| 1. Create a virtual environment | ||
| ```console | ||
| # with virtual env | ||
| $ virtualenv venv -p python3.10 | ||
| # with conda | ||
| $ conda create -p venv python=3.10 | ||
| ``` | ||
| 1. Install the dependencies | ||
| ```console | ||
| $ pip install -r requirements.txt | ||
| $ pip install -r requirements-dev.txt | ||
| ``` | ||
| 1. Run quarto on preview mode. Which automatically reloads the browser when input files or document resources change. | ||
| ```console | ||
| # Using our makefile command | ||
| $ make preview | ||
| # Using the quarto cli directly | ||
| $ quarto preview . | ||
| ``` | ||
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| For Linux users, you can use the `make setup` which will download and install the quarto binary for linux. And pip install | ||
| the requirements. | ||
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| ### How to add a new tutorial | ||
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| The kornia tutorials are jupyter notebooks (you can find them into [./nbs/](./nbs/) directory). Each notebook corresponds into a | ||
| "blogpost" page within the same content. The notebook is compiled into a webpage by quarto, which means you can write a | ||
| tutorial using a jupyter notebook with the normal pattern of Python and Markdown cells. This enable some special features | ||
| , for use it we recomment you to check the [quarto docs](https://quarto.org/docs/). | ||
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| Aside from the content of the tutorial, the first cell of the notebook should have a header content (markdown cell). This header | ||
| allow us to have thumbmail, author, categories, etc. This header should look like: | ||
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| ```txt | ||
| --- | ||
| title: "<YOUR TUTORIAL TITLE HERE>" | ||
| description: "<YOUR TUTORIAL DESCRIPTION HERE>" | ||
| author: | ||
| - "<YOUR NAME HERE>" | ||
| date: "<TUTORIAL DATE INTO FORMAT MM-DD-YYYY>" | ||
| categories: | ||
| - "<CATEGORY HERE: basic, itermediate or advanced>" | ||
| - "<CATEGORY HERE, based on the kornia module used: kornia.color, kornia.augmentation, etc>" | ||
| - "<OTHER CATEGORY: checkout the readme list of categories>" | ||
| - "<OTHER CATEGORY: checkout the readme list of categories>" | ||
| - "<OTHER CATEGORY: checkout the readme list of categories>" | ||
| image: "../tutorials/assets/<YOUR TUTORIAL THUMBMAIL FILENAME HERE>.png" | ||
| --- | ||
| <a href="https://colab.sandbox.google.com/github/kornia/tutorials/blob/master/nbs/<YOUR TUTORIAL FILENAME HERE>.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in google colab"></a> | ||
| ``` | ||
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| For this header you should generate a image to be used as thumbmail, and save it into the [tutorials/assets/](./tutorials/assets/) | ||
| directory. Also update the link for the colab, for user can be able to directly open your tutorial into the colab. You can add | ||
| `N` categories, look at the categories already available in the README, if you want to use a different one, please update the | ||
| README too. | ||
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| ### Tutorials categories | ||
| If you add a new category on the tutorials frontmatter, update this too. | ||
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| By Levels | ||
| - Basic | ||
| - Intermediate | ||
| - Advanced | ||
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| By module | ||
| - kornia.augmentation | ||
| - Kornia.feature | ||
| - kornia.contrib | ||
| - kornia.filters | ||
| - kornia.color | ||
| - kornia.io | ||
| - kornia.geometry | ||
| - kornia.enhance | ||
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| By generic type/category | ||
| - Data augmentation | ||
| - Segmentation | ||
| - Edge Detection | ||
| - Labeling | ||
| - Denoising | ||
| - Color spaces | ||
| - Local features | ||
| - Filters | ||
| - Blur | ||
| - Line | ||
| - Plane | ||
| - Keypoints | ||
| - Homography | ||
| - Image matching | ||
| - Image Registration | ||
| - Warp image | ||
| - Augmentation container | ||
| - Augmentation Sequential | ||
| - Line detection | ||
| - Line matching | ||
| - Rescale | ||
| - Affine | ||
| - 2D | ||
| - Unsupervised | ||
| - Self-supervised | ||
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| By specific names of models / API | ||
| - SOLD2 | ||
| - KeyNet | ||
| - Adalam | ||
| - HardNet | ||
| - DISK | ||
| - Patches | ||
| - LAF | ||
| - LoFTR |
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