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---
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. |