---
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 high-performance reverse image search.

## Features

- **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
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.