Babysitter Computer Vision Skill
Specialized skill for robot vision including feature detection, tracking, and camera calibration
install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/robotics-simulation/skills/computer-vision" ~/.claude/skills/a5c-ai-babysitter-computer-vision-skill && rm -rf "$T"
manifest:
library/specializations/robotics-simulation/skills/computer-vision/SKILL.mdsource content
Computer Vision Skill
Overview
Expert skill for robot vision applications including camera calibration, feature detection and tracking, stereo vision, and visual servoing.
Capabilities
- Implement camera intrinsic calibration (pinhole, fisheye)
- Configure stereo camera calibration and rectification
- Set up camera-LiDAR extrinsic calibration
- Implement feature detection (ORB, SIFT, SURF, SuperPoint)
- Configure optical flow tracking (Lucas-Kanade, Farneback)
- Implement depth estimation from stereo
- Set up visual servoing pipelines
- Configure image undistortion and rectification
- Implement ArUco/AprilTag marker detection
- Set up hand-eye calibration
Target Processes
- robot-calibration.js
- visual-slam-implementation.js
- object-detection-pipeline.js
- digital-twin-development.js
Dependencies
- OpenCV
- cv_bridge
- image_geometry
- camera_calibration
Usage Context
This skill is invoked when processes require camera calibration, feature detection, visual tracking, or image processing for robot vision applications.
Output Artifacts
- Camera calibration files (YAML)
- Stereo calibration parameters
- Feature detection configurations
- Visual servoing controllers
- Image processing pipelines
- Marker detection configurations