mediapipe-pose-detection
MediaPipe pose detection expertise. Use when debugging landmark tracking, adjusting confidence thresholds, fixing pose detection issues, working with pose.py and video_io.py, or validating pose detection with manual observation.
npx skills add majiayu000/claude-skill-registry --skill mediapipe-pose-detection --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.
# MediaPipe Pose Detection ## Key Landmarks for Jump Analysis ### Lower Body (Primary for Jumps) | Landmark | Left Index | Right Index | Use Case | | -------- | ---------- | ----------- | --------------------------- | | Hip | 23 | 24 | Center of mass, jump height | | Knee | 25 | 26 | Triple extension, landing | | Ankle | 27 | 28 | Ground contact detection | | Heel | 29 | 30 | Takeoff/landing timing | | Toe | 31 | 32 | Forefoot contact | ### Upper Body (Secondary) | Landmark | Left Index | Right Index | Use Case | | -------- | ---------- | ----------- | ------------------ | | Shoulder | 11 | 12 | Arm swing tracking | | Elbow | 13 | 14 | Arm action | | Wrist | 15 | 16 | Arm swing timing | ### Reference Points | Landmark | Index | Use Case | | --------- | ----- | ---------------- | | Nose | 0 | Head position | | Left Eye | 2 | Face orientation | | Right Eye | 5 | Face orientation | ## Confidence Thresholds ### Default Settings ```python min_detection_confidence = 0.5 # Initial pose detection min_tracking_confidence = 0.5 # Frame-to-frame tracking ``` ### Quality Presets (auto_tuning.py) | Preset | Detection | Tracking | Use Case | | ---------- | --------- | -------- | ----------------
- Key Landmarks for Jump Analysis
- Lower Body (Primary for Jumps)
- Upper Body (Secondary)
- Reference Points
- Confidence Thresholds
- Default Settings
- Quality Presets (autotuning.py)
- Tuning Guidelines
- Common Issues and Solutions
- Landmark Jitter
- Left/Right Confusion
- Tracking Loss
- Low Confidence Scores
- Video Processing (videoio.py)
FFmpeg rotation options ffmpeg -i input.mp4 -vf "transpose=1" output.mp4 # 90° clockwise ffmpeg -i input.mp4 -vf "transpose=2" output.mp4 # 90° counter-clockwise ffmpeg -i input.mp4 -vf "hflip" output.mp4 # Horizontal flip uv run kinemotion cmj-analyze video.mp4 --output debug.mp4
What does the mediapipe-pose-detection skill do?
MediaPipe pose detection expertise. Use when debugging landmark tracking, adjusting confidence thresholds, fixing pose detection issues, working with pose.py and video_io.py, or validating pose detection with manual observation.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill mediapipe-pose-detection --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.