15 lines
1.0 KiB
Markdown
15 lines
1.0 KiB
Markdown
# TESTING
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## Test Suites & Scripts
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The application uses diagnostic and simulation scripts rather than traditional `unittest` or `pytest` suites due to the heavy reliance on Computer Vision and large video downloads.
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- `test_pipeline.py`: Acts as the primary integration test, running the e2e extraction over known sample URLs to verify no missing sections or regressions occur.
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- `scripts/debug/rigorous_validator.py`: A rigid assertion script used locally to guarantee extracted sequences don't fail OCR checks and maintain strict monotonicity.
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- `scripts/debug/test_full_ocr.py`: Isolated test bench for verifying EasyOCR accuracy and tuning bounding box coordinates before baking them into the main pipeline.
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## Validation Methodologies
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Because validating computer vision outputs is visually subjective, 'tests' in this repository focus heavily on output metrics:
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- Number of discrete pages extracted vs expected.
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- Strict ascending sequence of OCR read measure numbers.
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- Absence of specific moving artifacts (e.g., the red/blue 'Playhead cursor').
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