AgentSkillsCN

segmentation

通过经过校准的阈值，将皮肤区域从背景杂乱中精准分离，以便进行后续分析。

SKILL.md
--- frontmatter
name: segmentation
description: Isolates skin regions from background clutter using calibrated thresholds for downstream analysis
license: MIT
compatibility: opencode
metadata:
  audience: developers
  workflow: clinical-pipeline

What I do

I isolate skin regions from the background to focus analysis on the relevant areas. I use calibrated thresholds based on skin tone classification to create accurate skin masks.

When to use me

Use this when:

  • •Image preprocessing is complete and you need to segment skin regions
  • •You need to remove background noise for feature extraction
  • •You need a binary mask of skin vs non-skin pixels

Key Concepts

  • •Skin Mask: Binary image where skin pixels are 1, background is 0
  • •Calibrated Thresholds: Thresholds adjusted based on Fitzpatrick type
  • •segmentation_complete: State flag after segmentation complete
  • •Background Removal: Eliminate non-skin pixels for focused analysis

Source Files

  • •services/vision.ts: Segmentation implementation
  • •types.ts: WorldState interface

Code Patterns

  • •Apply calibrated color thresholds based on fitzpatrick_type
  • •Generate binary mask of skin regions
  • •Validate segmentation quality before marking complete

Operational Constraints

  • •Thresholds MUST be calibrated to Fitzpatrick type
  • •Poor segmentation affects all downstream accuracy
  • •Consider fallback to manual region selection if auto-segmentation fails