Add theme_normalize: match a light-mode template in dark mode#445
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match_template correlates raw pixel intensities, so a light-mode template scores terribly against the same control in dark mode (polarity inverted). normalize_theme maps an image to a polarity-invariant single channel (sobel/laplacian gradient magnitude, identical for an image and its inverse) and match_theme normalizes both sides before locating via visual_match.match_template. cv2/numpy imported lazily.
Up to standards ✅🟢 Issues
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| Metric | Results |
|---|---|
| Complexity | 20 |
| Duplication | 0 |
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Summary
Fourth feature of the ROUND-15 perception lane.
match_templatecorrelates raw pixel intensities, so a light-mode template scores terribly against the same control in dark mode — the polarity is inverted. The fix is to compare structure (edges, gradients).utils/theme_normalize/:normalize_theme(map an image to a polarity-invariant single channel —sobel/laplaciangradient magnitude, identical for an image and its colour inverse, orzscore),match_theme(normalize both template and screen, then locate viavisual_match.match_template— finds the template across a light/dark flip). cv2/numpy imported lazily so the module/package stays importable without them.__all__;AC_match_themeexecutor command;ac_match_themeMCP tool (read-only); Script Builder under Image.normalize_theme(returns an image array) is the Python-API surface.v217_features_doc.rst+WHATS_NEW.md.Test
test/unit_test/headless/test_theme_normalize_batch.py— polarity invariance (normalize_theme(img) == normalize_theme(255-img)for sobel), zscore shape/dtype, unknown-method raises,match_themefinds a template embedded inverted in the haystack; wiring + facade tests run cv2-free (lazy import) while behavior tests use per-functionimportorskip. All green (cv2 present);ruff+bandit+radonclean; no float==; package stays Qt-free.