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