⚡ Bolt: Vectorized face prediction and detection optimization#37
⚡ Bolt: Vectorized face prediction and detection optimization#37guesswh0 wants to merge 1 commit into
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- Vectorize BasicEstimator.predict using squared distance expansion formula. - Pre-calculate squared norms in fit to avoid redundant computation. - Vectorize bounding box area calculation in FaceEngine.find_faces. - Fix bug in extra metadata indexing in find_faces. - Add backward compatibility for loaded models. - Add guard clause for empty input embeddings. Co-authored-by: guesswh0 <10531675+guesswh0@users.noreply.github.com>
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💡 What:
BasicEstimator.predictusing the squared distance expansion formula (BasicEstimator.fit.FaceEngine.find_faces.FaceEngine.find_faceswhereextrametadata was incorrectly indexed, leading to data loss/corruption when limiting results.🎯 Why:
The original implementation of
BasicEstimator.predictused a Python loop over input embeddings, which was a significant bottleneck for batch processing.FaceEngine.find_facesalso used a list comprehension for area calculation.📊 Impact:
BasicEstimator.predict: Reduced execution time from ~0.29s to ~0.085s for 500 embeddings against 2000 fitted samples (~3.4x speedup in current env).IndexErroror data misalignment in detection metadata.🔬 Measurement:
Run a benchmark script comparing batch prediction times or run existing tests in
tests/test_face_engine_models.py.PR created automatically by Jules for task 11668485811105077230 started by @guesswh0