v2.3.1

.github/README.pl.md

@@ -4,9 +4,12 @@
 <div id="badges">
     <p align="center">
         <img alt="Github Created At" src="https://img.shields.io/github/created-at/BKDDFS/PerfectFrameAI">
-        <img alt="GitHub Downloads (all assets, all releases)" src="https://img.shields.io/github/downloads/BKDDFS/PerfectFrameAI/total?style=flat&color=blue">
+        <img alt="GitHub last commit" src="https://img.shields.io/github/last-commit/BKDDFS/PerfectFrameAI">
+        <a href="https://codecov.io/github/BKDDFS/PerfectFrameAI" >
+        <img src="https://codecov.io/github/BKDDFS/PerfectFrameAI/graph/badge.svg?token=GT9TGKBGYI"/>
+        </a>
         <img alt="GitHub License" src="https://img.shields.io/github/license/BKDDFS/PerfectFrameAI">
-        <img alt="GitHub Release" src="https://img.shields.io/github/v/release/BKDDFS/PerfectFrameAI">
+        <img alt="GitHub Tag" src="https://img.shields.io/github/v/tag/BKDDFS/PerfectFrameAI">
         <img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/BKDDFS/PerfectFrameAI">
     </p>
 </div>
@@ -47,7 +50,7 @@
         </summary>
         <img src="../static/start_frames.png" width="350">
         <ol>
-            <p>Input: Folder z plikami video <code>.mp4</code>.</p>
+            <p>Input: Folder z plikami video.</p>
             <li>Bierze pierwsze video ze wskazanej lokalizacji.</li>
             <li>
                 Dzieli wideo na klatki.
@@ -69,7 +72,7 @@
         </summary>
         <img src="../static/start_images.png" width="350">
         <ol>
-            <p>Input: Folder z obrazami <code>.jpg</code>.</p>
+            <p>Input: Folder z obrazami.</p>
             <li>Wczytuje obrazy. Obrazy są przetwarzane batchach(seriach).</li>
             <li>Ocenia wszystkie obrazy w batchu za pomocą modelu AI i nadaje im ocenę liczbową.</li>
             <li>
@@ -89,7 +92,7 @@
         <p>Modyfikuje <code>best_frames_extractor</code> poprzez pominięcie części z AI/ocenianiem klatek.</p>
         <code>python start.py best_frames_extractor --all_frames</code>
         <ol>
-            <p>Input: Folder z plikami video <code>.mp4</code>.</p>
+            <p>Input: Folder z plikami video.</p>
             <li>Bierze pierwsze video ze wskazanej lokalizacji.</li>
             <li>
                 Dzieli wideo na klatki. Klatki są brane co 1 sekundę wideo.
@@ -448,7 +451,7 @@
     </div>
     <div id="tests">
         <h2>🧪 Testy</h2>
-        <img src="../static/tests_passed.png">
+        <img src="../static/tests.png">
         <p>
             Testy możesz uruchomić instalując zależności z <code>pyproject.toml</code>
             i wpisując w terminal w lokalizacj projektu - <code>pytest</code>.
@@ -498,7 +501,6 @@
                 Podsumowując, dodanie DALI powinno być kolejnym poważnym krokiem naprzód,
                 jeśli chodzi o poprawę wydajności.
             </li>
-            <li>Przetestowanie działania na starszych wersjach Pythona.</li>
             <li>
                 Naprawienie spillingu danych podczas oceniania klatek. 
                 Obecnie ocenianie ma delikatne spowolnienie w postaci problemu ze spillingiem.

.github/workflows/run_tests.yml

@@ -1,5 +1,3 @@
-# This workflow will install Poetry, install Python dependencies, run tests a single version of Python
-
 name: CI
 
 on:
@@ -11,7 +9,6 @@ on:
 permissions:
   contents: read
 
-
 jobs:
   build:
     runs-on: ubuntu-latest
@@ -46,8 +43,15 @@ jobs:
         run: |
           poetry install
 
-      - name: Run tests
+      - name: Run tests with coverage
         env:
           DOCKER_HOST: tcp://localhost:2375
         run: |
-          poetry run pytest
+          poetry run pytest --cov --cov-report=xml
+
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v3.1.1
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+          files: ./coverage.xml
+          fail_ci_if_error: true

README.md

@@ -5,6 +5,9 @@
     <p align="center">
         <img alt="Github Created At" src="https://img.shields.io/github/created-at/BKDDFS/PerfectFrameAI">
         <img alt="GitHub last commit" src="https://img.shields.io/github/last-commit/BKDDFS/PerfectFrameAI">
+        <a href="https://codecov.io/github/BKDDFS/PerfectFrameAI" >
+        <img src="https://codecov.io/github/BKDDFS/PerfectFrameAI/graph/badge.svg?token=GT9TGKBGYI"/>
+        </a>
         <img alt="GitHub License" src="https://img.shields.io/github/license/BKDDFS/PerfectFrameAI">
         <img alt="GitHub Tag" src="https://img.shields.io/github/v/tag/BKDDFS/PerfectFrameAI">
         <img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/BKDDFS/PerfectFrameAI">
@@ -47,7 +50,7 @@
         </summary>
         <img src="static/start_frames.png" width="350">
         <ol>
-            <p>Input: Folder with <code>.mp4</code> video files.</p>
+            <p>Input: Folder with video files.</p>
             <li>Takes the first video from the specified location.</li>
             <li>
                 Splits the video into frames.
@@ -69,7 +72,7 @@
         </summary>
         <img src="static/start_images.png" width="350">
         <ol>
-            <p>Input: Folder with <code>.jpg</code> images.</p>
+            <p>Input: Folder with images.</p>
             <li>Loads the images. Images are processed in batches.</li>
             <li>Evaluates all images in the batch using an AI model and assigns them a numerical score.</li>
             <li>
@@ -89,7 +92,7 @@
         <p>Modifying <code>best_frames_extractor</code> by skipping AI evaluation part.</p>
         <code>python start.py best_frames_extractor --all_frames</code>
         <ol>
-            <p>Input: Folder with <code>.mp4</code> video files.</p>
+            <p>Input: Folder with video files.</p>
             <li>Takes the first video from the specified location.</li>
             <li>
                 Splits the video into frames.
@@ -440,7 +443,7 @@
     </div>
     <div id="tests">
         <h2>🧪 Tests</h2>
-        <img src="static/tests_passed.png" width="1000" style="border-radius: 10px;">
+        <img src="static/tests.png" width="1000" style="border-radius: 10px;">
         <p>
             You can run the tests by installing the dependencies from <code>pyproject.toml</code>
             and typing in the terminal in the project location - <code>pytest</code>.
@@ -490,7 +493,6 @@
                 In summary, adding DALI should be another significant step forward
                 in terms of performance improvement.
             </li>
-            <li>Testing on older versions of Python.</li>
             <li>
                 Fixing data spilling during frame evaluation.
                 Currently, evaluation has a slight slowdown in the form of a spilling issue.

extractor_service/app/schemas.py

@@ -54,8 +54,8 @@ class ExtractorConfig(BaseModel):
     """
     input_directory: DirectoryPath = Path("/app/input_directory")
     output_directory: DirectoryPath = Path("/app/output_directory")
-    video_extensions: tuple[str] = (".mp4",)
-    images_extensions: tuple[str] = (".jpg",)
+    video_extensions: tuple[str] = (".mp4", ".mov", ".webm", ".mkv", ".avi")  # add more containers here
+    images_extensions: tuple[str] = (".jpg", ".jpeg", ".png", ".webp")  # add more containers here
     processed_video_prefix: str = "frames_extracted_"
     batch_size: int = 100
     compering_group_size: int = 5

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "PerfectFrameAI"
-version = "2.3.0"
+version = "2.3.1"
 description = "AI tool for finding the most aesthetic frames in a video. 🎞️➜🖼️"
 authors = ["Bartłomiej Flis <Bartekdawidflis@gmail.com>"]
 license = "GPL-3.0 license"

tests/extractor_service/unit/schemas_test.py

@@ -12,8 +12,8 @@ def test_config_default():
         config = ExtractorConfig()
     assert config.input_directory == Path("/app/input_directory")
     assert config.output_directory == Path("/app/output_directory")
-    assert config.video_extensions == (".mp4",)
-    assert config.images_extensions == (".jpg",)
+    assert config.video_extensions == (".mp4", ".mov", ".webm", ".mkv", ".avi")
+    assert config.images_extensions == (".jpg", ".jpeg", ".png", ".webp")
     assert config.processed_video_prefix == "frames_extracted_"
     assert isinstance(config.compering_group_size, int)
     assert isinstance(config.batch_size, int)