Google MediaPipe Tasks API (current supported, NOT legacy mediapipe.solutions): Vision Tasks (Face Detector, Face Landmarker, Face Stylizer, Hand Landmarker, Gesture Recognizer, Pose Landmarker, Holistic Landmarker, Object Detector, Image Classifier, Image Segmenter, Interactive Segmenter, Image Embedder, Image Generator), Audio Tasks (Audio Classifier), Text Tasks (Text Classifier, Text Embedder, Language Detector), GenAI Tasks (LLM Inference — on-device Gemma/Phi-2/Falcon/StableLM). Three run modes: IMAGE, VIDEO, LIVE_STREAM (async). Python: mediapipe.tasks.python.vision/audio/text/genai. Docs at ai.google.dev/edge/mediapipe/solutions. Model Maker for transfer learning. Use when the user asks to detect pose/face/hand landmarks, classify an image, run a body-pose model, segment people, recognize gestures, do on-device LLM inference via MediaPipe, or build a mobile/embedded CV pipeline.
$npx -y skills add damionrashford/media-os --skill cv-mediapipeInstalls into the current project.
Run `npx skills use "https://github.com/damionrashford/media-os" --skill "damionrashford/media-os/cv-mediapipe"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/damionrashford/media-os" that are relevant to the current task. Run `npx skills add "https://github.com/damionrashford/media-os"` and select the relevant skills, then follow their instructions.