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MediaPipe Tasks Demo

Experience the power of on-device Machine Learning with MediaPipe Tasks. This demo showcases real-time audio, vision and text demos using CPU and GPU acceleration on Web.

Play with the demos here: https://google-ai-edge.github.io/mediapipe-samples-web/

Supported Tasks

Vision

  • Face Detection: Detect faces in images and video.
  • Face Landmarker: Detect 478 3D face landmarks.
  • Gesture Recognizer: Recognize hand gestures (e.g., "Thumbs Up", "Peace").
  • Hand Landmarker: Track 21 3D hand landmarks for both hands.
  • Holistic Landmarker: Simultaneous tracking of face, hands, and pose.
  • Image Classifier: Categorize images into defined classes.
  • Image Embedding: Compare image similarity using vector embeddings.
  • Image Segmentation: Pixel-perfect masking of objects.
  • Interactive Segmentation: Click to segment specific objects of interest.
  • Object Detection: Detect multiple objects with bounding boxes.
  • Pose Landmarker: Full-body pose tracking with segmentation support.

Audio

  • Audio Classifier: Classify ambient sounds in real-time.

Text

  • Language Detection: Identify the language of input text.
  • Text Classification: Classify text sentiment (positive/negative).
  • Text Embedding: Semantic similarity comparison for text.

Quick Start

  1. Clone the repository
  2. Install dependencies: pnpm install
  3. Run the app: pnpm dev
  4. Open browser: Navigate to the local URL (typically http://localhost:5173)

Testing

We ensure robustness with a comprehensive End-to-End (E2E) test suite using Playwright.

pnpm test

About

A collection of examples for the MediaPipe Task APIs that can run fully inside your browser.

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