fix #453: use np.array() instead of np.asarray() for PIL image conversion - #455
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fix #453: use np.array() instead of np.asarray() for PIL image conversion#455cursor[bot] wants to merge 1 commit into
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…sion in stereo_to_anndata np.asarray() creates a read-only view of the PIL Image pixel buffer rather than an independent copy. When the PIL Image objects are garbage collected after the function returns, the numpy arrays stored in adata.uns['spatial'] can point to freed memory, resulting in all-255 (white) pixel values. Replace np.asarray() with np.array() to ensure the numpy arrays own their data independently of the PIL Image lifecycle. Co-authored-by: wanruiwen-genomics-cn <wanruiwen-genomics-cn@users.noreply.github.com>
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Summary
In
stereo_to_anndata(), the image processing code usesnp.asarray()to convert PIL Image objects to numpy arrays.np.asarray()creates a read-only view of the PIL Image's internal pixel buffer rather than an independent copy. When the PIL Image objects are garbage collected after the function returns, the numpy arrays stored inadata.uns['spatial']can point to freed memory, resulting in all-255 (white) pixel values.This issue is version-dependent — some Pillow/NumPy combinations maintain the data through a
bytesreference, while others do not, making it a subtle intermittent bug.Changes
stereo/io/reader.py: Replacenp.asarray(hires)withnp.array(hires)andnp.asarray(lowres)withnp.array(lowres)to ensure the numpy arrays own their pixel data independently of the PIL Image lifecycle.Verification
np.array()always creates an owned copyClassification
Closes #453