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生産性・共同作業 · SKILL.md

enhancement

enhancement

Adjust color, exposure, filters, and restoration workflows in scikit-image, with explicit channel-axis and preserve-range handling.

Independent GitHub snapshot · Automated classification · Original documentation governs

スキルの説明

GitHub

name: enhancement description: "Adjust color, exposure, filters, and restoration workflows in scikit-image, with explicit channel-axis and preserve-range handling." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Enhancement

Use this sub-skill when the task changes pixel appearance or intensity statistics rather than geometry or object bookkeeping.

Route here

  • Convert between color spaces, remove alpha, or overlay existing labels with skimage.color.
  • Adjust contrast, histogram shape, and intensity ranges with skimage.exposure.
  • Smooth, sharpen, detect edges, or choose a cutoff with skimage.filters.
  • Denoise, inpaint, deblur, subtract background, unwrap phase, or stabilize denoising with skimage.restoration.

Fast start

  1. Inspect shape, dtype, min, max, and whether the array has a channel dimension.
  2. Set channel_axis explicitly for every multichannel image; use None for scalar or grayscale images.
  3. Use preserve_range=True whenever a function offers it and the numeric values should stay in their native units.
  4. Convert to float or back to storage dtype only when that is the intended next step.
  5. Verify the result on a small sample before chaining multiple enhancement steps.

Working rules

  • channel_axis is about layout, not color meaning. Do not rely on defaults for color images.
  • preserve_range is about value semantics, not dtype. Keep it on when the values already mean something physically or when later steps must not renormalize to [0, 1].
  • Many enhancement functions return float arrays; convert the result afterward with img_as_* only when storage or downstream APIs need it.
  • Thresholding belongs here only as preprocessing. If the task needs connected components, region labeling, or object statistics, route elsewhere.
  • label2rgb is a display helper for existing labels, not a segmentation step.

Boundaries

  • Do not cover segmentation, morphology cleanup, connected components, or label creation.
  • Do not cover region properties, object statistics, or image-quality metrics.
  • Do not cover geometric transforms, warps, alignment, or registration.
  • If a function does not expose channel_axis, either convert to a scalar image first or handle channels explicitly one at a time.

References

  • references/workflows.md
  • references/troubleshooting.md
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