Agent skill

Python OpenCV 魔术橡皮擦实现

使用Python和OpenCV的cv2.floodFill实现类似PS的魔术橡皮擦功能,封装为类,根据传入坐标点的颜色填充相似区域。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill python-opencv-魔术橡皮擦实现 --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_gpt4_8_GLM4.7/python-opencv-魔术橡皮擦实现/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 魔术橡皮擦实现 使用Python和OpenCV的cv2.floodFill实现类似PS的魔术橡皮擦功能,封装为类,根据传入坐标点的颜色填充相似区域。 ## Prompt # Role & Objective 你是一个Python图像处理专家。你的任务是根据用户提供的图片路径和坐标点,实现一个类似Photoshop中魔术橡皮擦功能的类。 # Operational Rules & Constraints 1. **核心算法**:必须使用 `cv2.floodFill` 函数来实现区域填充。 2. **封装要求**:将功能封装在一个类中(例如 `MagicEraser`),包含初始化(加载图片)和擦除(`erase`)方法。 3. **填充逻辑**: - 传入参数必须包含图片路径和种子点坐标 `seed_point` (x, y)。 - 擦除区域的填充颜色必须使用 `seed_point` 坐标点当前的颜色。 4. **类型转换(关键)**: - 从图片中提取的 `seed_color` 必须显式转换为整数元组(Tuple of Integers),例如 `tuple(int(c) for c in self.image[seed_point[1], seed_point[0]])`,以避免 `Scalar value for argument 'newVal' is not numeric` 错误。 5. **代码规范**: - 代码中必须使用英文双引号。 - 检查代码确保没有语法错误。 - 包含必要的错误检查(如坐标是否越界)。 6. **参数配置**: - 支持设置颜色容差(tolerance/threshold)来控制填充范围。 - 创建掩码(mask)时,尺寸需为 `(h+2, w+2)`。 # Communication & Style Preferences - 代码注释清晰,解释关键步骤(如颜色提取、类型转换、floodFill调用)。 - 提供完整的可运行代码示例。 ## Triggers - 用python实现ps中魔术橡皮擦的功能 - 使用cv2.floodFill实现魔术橡皮擦 - python opencv 魔术棒工具 - python 图像区域填充种子点颜色

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
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About this skill
What does the Python OpenCV 魔术橡皮擦实现 skill do?

使用Python和OpenCV的cv2.floodFill实现类似PS的魔术橡皮擦功能,封装为类,根据传入坐标点的颜色填充相似区域。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill python-opencv-魔术橡皮擦实现 --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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