fix: keep single-blob filter() matches - #35
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np.array(mask).all(axis=0) produces a 2D mask when Blobs holds a single blob, so self[m] indexed with it dropped the blob even when it matched the filter criteria. Flatten before indexing. Fixes #17
Up to standards ✅🟢 Issues
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| Metric | Results |
|---|---|
| Complexity | 0 |
| Duplication | 0 |
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Summary
Blobs.filter()built its mask vianp.array(mask).all(axis=0), which stays 2D when there's only one blob in the set. Indexingself[m]with a 2D boolean array silently dropped the blob even when it matched the filter criteria.self[m.flatten()]).Fixes #17
Test plan
blobs1): one asserting a matching blob is kept, one asserting a non-matching blob is removed.0 != 1) and passes with it.tests/test_image_blobs.py: 99 passed, 3 skipped, no regressions.