Upload README.md

README.md

@@ -1,19 +1,107 @@
+---
+title: Orcan VisionTrace GPU Service
+emoji: 👁️
+colorFrom: blue
+colorTo: purple
+sdk: docker
+pinned: false
+license: mit
+tags:
+- face-recognition
+- computer-vision
+- faiss
+- gpu-acceleration
+- similarity-search
+---
+
 # Orcan VisionTrace GPU Service
 
-GPU-accelerated face recognition and FAISS indexing service for Orcan VisionTrace.
+GPU-accelerated face recognition and FAISS indexing service for high-performance reverse image search.
 
 ## Features
-- Batch face embedding extraction using InsightFace
-- GPU-accelerated FAISS index creation
-- Image enhancement for poor quality inputs
-- High-performance search capabilities
 
-## Hardware Requirements
-- NVIDIA GPU with CUDA support
-- Minimum 8GB GPU memory recommended
+- **Batch Face Embedding Extraction**: Process multiple images simultaneously using InsightFace on GPU
+- **GPU-Accelerated FAISS Indexing**: Create high-performance vector indexes for similarity search
+- **Image Enhancement**: Automatic quality improvement for poor quality inputs (CCTV, low-light images)
+- **High-Performance Search**: Fast similarity search with adaptive thresholds
+- **Scalable Architecture**: Optimized for production workloads with automatic scaling
 
 ## API Endpoints
-- POST /extract_embeddings_batch - Batch face embedding extraction
-- POST /create_faiss_index - GPU-accelerated index creation  
-- POST /search_faiss - Fast similarity search
-- GET /health - Service health check
+
+### POST /extract_embeddings_batch
+Extract face embeddings from multiple images in parallel.
+
+**Request:**
+```json
+{
+  "images": ["base64_encoded_image1", "base64_encoded_image2"],
+  "enhance_quality": true,
+  "aggressive_enhancement": false
+}
+```
+
+**Response:**
+```json
+{
+  "embeddings": [[embedding_vector1], [embedding_vector2]],
+  "extraction_info": [{"face_count": 1, "confidence": 0.95}, ...],
+  "total_processed": 2,
+  "successful": 2
+}
+```
+
+### POST /create_faiss_index
+Create optimized FAISS index on GPU for fast similarity search.
+
+**Request:**
+```json
+{
+  "embeddings": [[embedding1], [embedding2], ...],
+  "dataset_size": 10000,
+  "dimension": 512
+}
+```
+
+### POST /search_faiss
+Perform similarity search on FAISS index.
+
+### GET /health
+Health check endpoint.
+
+## Hardware Requirements
+
+- **GPU**: NVIDIA A10G or A100 recommended
+- **Memory**: Minimum 8GB GPU memory
+- **CUDA**: Compatible with CUDA 11.8+
+
+## Performance
+
+- **Face Extraction**: 10-20x faster than CPU (0.05-0.1s per image)
+- **Index Creation**: 5-10x faster than CPU
+- **Search Latency**: <50ms for most queries
+- **Throughput**: 50+ images per batch
+
+## Use Cases
+
+- Reverse image search systems
+- Identity verification systems
+- Photo organization and management
+- Security and surveillance applications
+- Digital asset management
+
+## Model Details
+
+- **Face Detection**: InsightFace RetinaFace
+- **Face Recognition**: ArcFace embeddings (512-dimensional)
+- **Enhancement**: Multi-strategy image quality improvement
+- **Indexing**: Adaptive FAISS index selection based on dataset size
+
+## Limitations
+
+- Requires high-quality face images for best results
+- GPU memory limits batch size for very large images
+- Cold start latency of ~30 seconds on first request
+
+## License
+
+MIT License - See LICENSE file for details.