feat: adaptive background detection for dark mode support#23
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Replace hardcoded white (255,255,255) background assumption in content detection with auto-detection from image perimeter pixels. Two strategies, chosen automatically: - Alpha-only: transparent PNGs skip color-distance filtering entirely - Perimeter sampling: opaque images infer background via quantized color bucketing of edge pixels Adds backgroundColor prop as explicit override fallback.
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Benchmark Comparison: main vs feat/adaptive-background-detectionThreshold: 5%+ change, >100us absolute delta, and statistically significant (p<0.05).
No regressions detected. Feature cost breakdownHow expensive are individual features? Measured on this run's HEAD commit.
Full benchmark output in the CI job logs. |
The corner-first fast path misidentified logo content as background when logos extended to the corners, causing sizing regressions. Restores the first commit's logic (full perimeter scan, alphaOnly for transparent images) with typed arrays instead of Map for bucketing.
- Inverted SVGs (transparent, light content) and JPG test logos - Dark Mode, JPG, and Comparison stories under LogoSoup group - Shared StoryLogoSoup wrapper with debug controls - Consolidated argTypes, defaults, and types in shared.tsx - alphaOnly path for transparent images, color distance for opaque - min(a, sqrt(distSq)) opacity for opaque density normalization
BackgroundColor type accepts hex, rgb(), hsl(), named colors, or [r, g, b] tuples. CSS strings are resolved via a 1×1 canvas.
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Replaces the hardcoded white background assumption in content detection by auto-detecting the background color from the image itself.
Transparent images — alpha-only content detection (unchanged from current behavior)
Opaque images — background color sampled from image edges
Adds
backgroundColorprop as an explicit override fallback.Usage
Works automatically — no config needed for opaque images:
For explicit control (e.g. JPGs on a known dark page):
Also available on the hook:
Closes #2