.claude/skills/mediapipeRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
Use Google MediaPipe for on-device computer vision — face, hand, and pose landmark detection, face detection, object detection, and image segmentation on images, videos, or webcam streams. Activate when the user asks to detect faces/hands/poses/objects, extract landmarks or keypoints, do background
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.claude/skills/mediapipeRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
.agents/skills/mediapipeRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
skills/mediapipeRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
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sha256:bbf3bb537b3e53e044dd7bc340c1698c98596a16666035816d61ae513766931eLICENSEREADME.mdreferences/api_cheatsheet.mdreferences/landmarks.mdscripts/requirements.txtscripts/run_mediapipe.pyskill-card.mdSKILL.mdInitial release: MediaPipe skill for on-device computer vision - Provides a CLI script (`scripts/run_mediapipe.py`) for face, hand, and pose landmark detection, object detection, and image segmentation across images, videos, and webcam streams. - Supports both the legacy solutions API (with bundled models) and the newer MediaPipe Tasks API (requires downloadable model files). - Includes quick-start usage instructions, dependency/environment setup, and bilingual documentation (English & Chinese). - Reference files: model download URLs, API usage patterns (`references/api_cheatsheet.md`), and landmark index tables (`references/landmarks.md`). - Outputs annotated images/videos, per-frame landmark data (JSON/CSV), and segmentation masks.