senior-computer-vision
World-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems. Expertise in PyTorch, OpenCV, YOLO, SAM, diffusion models, and vision transformers. Includes 3D vision, video analysis, real-time processing, and production deployment. Use when building vision AI systems, implementing object detection, training custom vision models, or optimizing inference pipelines.
npx skills add foryourhealth111-pixel/Vibe-Skills --skill senior-computer-vision --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.
# Senior Computer Vision Engineer World-class senior computer vision engineer skill for production-grade AI/ML/Data systems. ## Quick Start ### Main Capabilities ```bash # Core Tool 1 python scripts/vision_model_trainer.py --input data/ --output results/ # Core Tool 2 python scripts/inference_optimizer.py --target project/ --analyze # Core Tool 3 python scripts/dataset_pipeline_builder.py --config
What does the senior-computer-vision skill do?
World-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems. Expertise in PyTorch, OpenCV, YOLO, SAM, diffusion models, and vision transformers. Includes 3D vision, video analysis, real-time processing, and production deployment. Use when building vision AI systems, implementing object detection, training custom vision models, or optimizing inference pipelines.
How do I install it?
Run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill senior-computer-vision --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 foryourhealth111-pixel/Vibe-Skills, a repository with 2,593 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.