Add end-to-end tutorial for feature extraction and evaluation#8
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prachitbhike wants to merge 1 commit intoYalaLab:mainfrom
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Add end-to-end tutorial for feature extraction and evaluation#8prachitbhike wants to merge 1 commit intoYalaLab:mainfrom
prachitbhike wants to merge 1 commit intoYalaLab:mainfrom
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Adds a tutorial that walks through the full pipeline: generating synthetic data, extracting embeddings (CLI and Python API), running evaluation, and adding a custom dataset. - tutorial/setup_tutorial.py: generates a synthetic chest X-ray image and dummy labels JSON so the DummyDataset works out of the box - TUTORIAL.md: four-part guide covering extraction, Python API, evaluation, and custom datasets - README.md: link to tutorial This also provides a workaround for the missing rve package (YalaLab#5) and explains how the model converts images to embeddings (YalaLab#7). Closes YalaLab#2 Addresses YalaLab#5, YalaLab#7
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Summary
TUTORIAL.md) walking through the full pipeline: synthetic data setup, feature extraction (CLI + Python API), evaluation, and adding a custom datasettutorial/setup_tutorial.pyto generate the synthetic image and labels needed byDummyDatasetREADME.mdIssues addressed
rve-free path viaDummyDatasetand documents the workaround in the troubleshooting sectionWhat's included
tutorial/setup_tutorial.pyassets/CXR145_IM-0290-1001.png(synthetic 1024x1024 grayscale image) andtutorial/dummy_labels.json(100 studies, 3 binary findings). Uses only PIL + stdlib.TUTORIAL.mdREADME.md## Tutorialsection with link toTUTORIAL.mdTest plan
python tutorial/setup_tutorial.pyand verify both files are created--max-samples 10to verify extraction worksdiscover_questions_from_jsonexpectations