🔍 Facial Recognition Service
Powered by MediaPipe Face Mesh
Fast, accurate facial recognition using Google's MediaPipe technology.
- 478 facial landmarks per face
- Real-time processing capability
- CPU-optimized for Hugging Face Spaces
Upload a single image to extract facial features. The system will:
- Detect the face in the image
- Extract 478 3D facial landmarks
- Generate a unique embedding vector
Tips for best results:
- Use clear, well-lit photos
- Face should be visible and not obstructed
- Front-facing photos work best
- Works with various angles and expressions
Upload a target face and up to 5 candidate images to find matches. The system compares facial landmarks and returns similarity scores.
📸 Candidate Images
Similarity Scoring:
- 90-100%: Excellent match
- 75-89%: Very good match
- 65-74%: Good match
- 50-64%: Moderate match
- Below 50%: Low confidence
About This Service
This facial recognition system uses Google's MediaPipe Face Mesh, providing:
- High Precision: 478 3D facial landmarks per face
- Fast Processing: Optimized for real-time performance
- Robust Detection: Works with various angles and lighting
- Privacy-Focused: All processing happens in your session
How It Works
- Face Detection: Locates faces in uploaded images using MediaPipe
- Landmark Extraction: Identifies 478 precise facial points in 3D space
- Embedding Generation: Converts landmarks to a feature vector
- Similarity Comparison: Compares embeddings using cosine similarity
- Threshold Filtering: Returns matches above the confidence threshold
Technology Stack
- Face Detection: MediaPipe Face Detection
- Feature Extraction: MediaPipe Face Mesh (478 landmarks)
- Embedding: 1434-dimensional vector (478 points × 3 coords)
- Similarity: Cosine similarity metric
- Computing: CPU-optimized (no GPU required)
Use Cases
- Identity verification systems
- Photo organization and deduplication
- Access control applications
- Face matching in databases
- Attendance tracking systems
Performance
- Build Time: Fast (~2-3 minutes)
- Processing Speed: ~0.5-1 second per image
- Memory Usage: Low (~500MB)
- Accuracy: High for frontal faces, good for various angles
Advantages vs Other Methods
| Feature | MediaPipe | dlib | InsightFace |
|---|---|---|---|
| Build Time | ✅ Fast | ❌ Slow | ⚠️ Medium |
| Dependencies | ✅ Minimal | ❌ Heavy | ⚠️ Medium |
| CPU Performance | ✅ Excellent | ⚠️ Good | ⚠️ Good |
| HF Spaces | ✅ Works | ❌ Build fails | ⚠️ Complex |
Note: Processing times may vary based on image size and server load. All processing happens server-side - images are not stored after processing.
🔒 Privacy: Images processed in session only • Not stored • Not shared
⚡ Powered by MediaPipe • Optimized for Hugging Face Spaces
⚡ Powered by MediaPipe • Optimized for Hugging Face Spaces