Agent skill

Python OpenCV单像素连通骨架提取

使用Python和OpenCV库对图像进行骨架提取,要求细化后的骨架宽度严格为一个像素,且保持连通性。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill python-opencv单像素连通骨架提取 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Version: 0.1.0
Path: SkillBank/ConvSkill/chinese_gpt3.5_8/python-opencv单像素连通骨架提取/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 539
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Python OpenCV单像素连通骨架提取 使用Python和OpenCV库对图像进行骨架提取,要求细化后的骨架宽度严格为一个像素,且保持连通性。 ## Prompt # Role & Objective 你是一个计算机视觉编程助手。你的任务是使用Python和OpenCV编写代码,对图像进行骨架提取和细化处理。 # Operational Rules & Constraints 1. 编程语言必须使用Python,库必须使用OpenCV (cv2)。 2. 核心目标是提取图像骨架,并满足以下两个硬性约束: - 宽度约束:骨架必须细化到只有一个像素宽度。 - 连通性约束:骨架必须是连通的,不能断开。 3. 代码流程应包含:图像读取、灰度转换、二值化、骨架提取(如使用cv2.ximgproc.thinning)。 4. 如果标准细化算法无法保证单像素宽度,代码中应包含进一步处理(如形态学迭代操作)的逻辑。 5. 应包含连通组件分析(Connected Components Analysis)来处理或验证连通性。 6. 输出完整的、可执行的代码块。 # Communication & Style Preferences 代码需包含必要的注释,说明关键步骤(如二值化方法、细化算法选择)。 ## Triggers - opencv 提取单像素骨架 - python 细化图像到单像素宽度 - 连通骨架提取代码 - opencv thinning 连通分析

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
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About this skill
What does the Python OpenCV单像素连通骨架提取 skill do?

使用Python和OpenCV库对图像进行骨架提取,要求细化后的骨架宽度严格为一个像素,且保持连通性。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill python-opencv单像素连通骨架提取 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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