Functions to QC histopathology images#1036
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Codecov Report❌ Patch coverage is Additional details and impacted files@@ Coverage Diff @@
## main #1036 +/- ##
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- Coverage 74.05% 73.56% -0.50%
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Files 39 44 +5
Lines 6495 6929 +434
Branches 1122 1174 +52
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+ Hits 4810 5097 +287
- Misses 1230 1347 +117
- Partials 455 485 +30
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selmanozleyen
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selmanozleyen
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Things to do:
- Sync with main (some files are old)
- Vectorize for loops I mentioned
- Use scikit-image when we can
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Replaces the earlier qc_sharpness prototype with a general-purpose qc_image function that computes tile-based QC metrics on spatial images. Compute (sq.experimental.im.qc_image): - Tile-based metrics: sharpness (tenengrad, var_of_laplacian), intensity (brightness, entropy), staining (hematoxylin/eosin via HED deconvolution), and artifact detection (fold fraction, tissue fraction) - QCMetric enum and registry mapping each metric to its input kind and callable - Percentile-rank unfocus scoring within tissue tiles for outlier detection - Preview overlay showing flagged tiles on the image - Shared utilities in _utils.py: vectorized TileGrid (numpy + shapely.box), mask helpers, and shapes persistence (also used by make_tiles) Plot (sq.experimental.pl.qc_image): - Multi-panel summary: spatial view, KDE distribution (tissue vs background), and descriptive statistics per metric Metrics use scikit-image filters (sobel_h/v, laplace) instead of hand-rolled convolutions, and thread-safe HED caching avoids redundant deconvolution. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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…ficiency - Rename _ensure_tissue_mask → _resolve_tissue_mask (clearer intent) - Split intensity/staining/artifact metrics into _intensity_metrics.py, keeping _qc_metrics.py as a lean registry + enums module - Remove redundant tissue_similarity/background_similarity columns - Simplify _detect_tissue_from_mask → _classify_tiles_by_tissue (accept TileGrid, return 2 arrays instead of 4, reuse pre-binarized mask) - Cache FFT frequency grid via @lru_cache (avoid recomputing per tile) - Pre-compute grayscale luminance weights as module-level constant - Fix O(n) var_names lookup in plotting with dict - Reduce allocations in _entropy - Fix stats text indentation in plot panel - Revert stale .pre-commit-config.yaml pins to match main - Document _fold_fraction HSV thresholds as H&E-tuned Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- test_plot_calc_qc_image_not_hne: use metrics=None so is_hne=False actually exercises different default metrics (was identical to hne test) - test_qc_image_rgb_metric: add explicit is_hne=True for clarity - Add test_qc_image_outlier_detection_with_tissue: verify outlier and tissue columns are populated correctly - Add test_qc_image_outlier_detection_without_tissue: verify detect_tissue=False path (no tissue columns, no NaN scores) - Add test_qc_image_compute_only: verify minimal compute-only path Note: QCImage_calc_qc_image_not_hne.png reference image needs regeneration since the test now produces a different plot. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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@timtreis could you resolve the conflicts please its hard to review like this |
…tion-to-qc-he-images # Conflicts: # .pre-commit-config.yaml # src/squidpy/experimental/im/_make_tiles.py
Functions exported across private modules (e.g. _sharpness_metrics, _intensity_metrics, _utils) no longer use a leading underscore since the module itself is already private. Also removes the unnecessary lru_cache from fft_high_freq_mask — the mask computation is cheap relative to the fft2 call it supports. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
for more information, see https://pre-commit.ci
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selmanozleyen
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all looks good except the points I made. We can put them as a TODO and move on if we want to
Co-authored-by: Selman Özleyen <32667648+selmanozleyen@users.noreply.github.com>
…-qc-he-images Resolve conflict in _intensity_metrics.py: keep the batched hed_metrics() function from the PR and remove the old thread-local cache approach. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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