npx skills add majiayu000/claude-skill-registry --skill opencv --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# OpenCV OpenCV is the fundamental library for Image Processing. v5.0 (2025) modernizes deep learning support and licensing. ## When to Use - **Image Manipulation**: Resizing, cropping, color space conversion (BGR -> RGB). - **Classic CV**: Edge detection (Canny), Feature matching (SIFT/ORB). - **Video I/O**: Reading/Writing webcams or video files. ## Core Concepts ### BGR OpenCV reads images as Blue-Green-Red (not RGB) by default. History quirks. ### `cv::Mat` The core matrix structure (in C++). In Python, it's just a NumPy array. ### DNN Module Running darknet/onnx models directly in OpenCV (lightweight inference). ## Best Practices (2025) **Do**: - **Use it for Preprocessing**: `cv2.resize()` is highly optimized. - **Use `headless`**: `pip install opencv-python-headless` for server deployments (smaller, no GUI deps). **Don't**: - **Don't implement Deep Learning training**: Use PyTorch. Use OpenCV only for inference/preprocessing. ## References - [OpenCV Documentation](https://opencv.org/)
- When to Use
- Core Concepts
- BGR
- cv::Mat
- DNN Module
- Best Practices (2025)
- References
What does the opencv skill do?
OpenCV computer vision library. Use for image processing.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill opencv --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 majiayu000/claude-skill-registry, a repository with 534 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.