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/

• 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 Classifier: Classify ambient sounds in real-time.

• Decision Maker: Make decisions from text or JSON input using logic rules.
• Decision Maker - Dino Game: Watch the Decision Maker play a runner game by choosing to jump, duck or wait.

• Semantic Retriever: Index content into a vector store and retrieve it with natural-language queries.
• Universal Embedder: Embed text and images into a shared vector space across modalities.

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

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)

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

pnpm test