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Add a GitHub Actions workflow that, on push to main and on pull requests: - checks out the repo with Git LFS (so the model weights are present), - installs the pinned requirements.txt, - runs predict_cls.py on the bundled sample image and asserts the predicted quality is close to 20 (the sample is JPEG quality 20). Also add a CI status badge to the README.
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Closes #6.
What
Adds
.github/workflows/ci.yml. On push tomainand on every PR it:requirements.txt,predict_cls.pyonsample_image/monarch_jpeg_q20.pngand asserts thepredicted quality is within [18, 22] (the sample is JPEG quality 20).
The setup reuses
classifier/env.sh(PYTHONPATH +TF_USE_LEGACY_KERAS=1), so CIexercises the exact documented flow.
A CI status badge is added to the README.
Verified locally
ci.ymlparses as valid YAML; job/steps/triggers checked.20.01and correctly fails for an out-of-range value.