# Computer Vision Platform Boilerplate

## Overview
Image processing, object detection, facial recognition, machine learning vision models

## Tech Stack
- **Backend**: Python, FastAPI, Flask
- **Frontend**: React, TypeScript
- **Database**: PostgreSQL, MongoDB
- **ML/AI**: OpenCV, TensorFlow, PyTorch
- **Cloud**: AWS Rekognition, Google Vision
- **Processing**: CUDA, GPU acceleration

## Specialized Agents
- `computer-vision-engineer` - CV model development and training
- `image-processing-specialist` - Advanced image manipulation
- `ml-model-optimizer` - Model performance optimization
- `vision-api-integrator` - Third-party vision service integration

## Key Features
- Image and video processing
- Object detection and tracking
- Facial recognition systems
- OCR and text extraction
- Real-time video analysis
- Custom model training

## Computer Vision Tasks
- Image classification
- Object detection and segmentation
- Facial analysis and recognition
- Optical character recognition
- Motion detection and tracking
- Style transfer and enhancement

## Architecture Patterns
- ML pipeline processing
- GPU-accelerated computing
- Real-time video streaming
- Model serving and inference

## Implementation Requirements
- High-performance image processing
- Real-time video analysis
- Scalable model inference
- GPU optimization
- Large dataset handling
- Model versioning and deployment