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usda-vision/camera-management-api/docs/legacy/IMPLEMENTATION_SUMMARY.md

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# USDA Vision Camera System - Implementation Summary
## 🎉 Project Completed Successfully!
The USDA Vision Camera System has been fully implemented and tested. All components are working correctly and the system is ready for deployment.
## ✅ What Was Built
### Core Architecture
- **Modular Design**: Clean separation of concerns across multiple modules
- **Multi-threading**: Concurrent MQTT listening, camera monitoring, and recording
- **Event-driven**: Thread-safe communication between components
- **Configuration-driven**: JSON-based configuration system
### Key Components
1. **MQTT Integration** (`usda_vision_system/mqtt/`)
- Listens to two machine topics: `vision/vibratory_conveyor/state` and `vision/blower_separator/state`
- Thread-safe message handling with automatic reconnection
- State normalization (on/off/error)
2. **Camera Management** (`usda_vision_system/camera/`)
- Automatic GigE camera discovery using python demo library
- Periodic status monitoring (every 2 seconds)
- Camera initialization and configuration management
- **Discovered Cameras**:
- Blower-Yield-Cam (192.168.1.165)
- Cracker-Cam (192.168.1.167)
3. **Video Recording** (`usda_vision_system/camera/recorder.py`)
- Automatic recording start/stop based on machine states
- Timestamp-based file naming: `camera1_recording_20250726_143022.avi`
- Configurable FPS, exposure, and gain settings
- Thread-safe recording with proper cleanup
4. **Storage Management** (`usda_vision_system/storage/`)
- Organized file storage under `./storage/camera1/` and `./storage/camera2/`
- File indexing and metadata tracking
- Automatic cleanup of old files
- Storage statistics and integrity checking
5. **REST API Server** (`usda_vision_system/api/`)
- FastAPI server on port 8000
- Real-time WebSocket updates
- Manual recording control endpoints
- System status and monitoring endpoints
6. **Comprehensive Logging** (`usda_vision_system/core/logging_config.py`)
- Colored console output
- Rotating log files
- Component-specific log levels
- Performance monitoring and error tracking
## 🚀 How to Use
### Quick Start
```bash
# Run system tests
python test_system.py
# Start the system
python main.py
# Or use the startup script
./start_system.sh
```
### Configuration
Edit `config.json` to customize:
- MQTT broker settings
- Camera configurations
- Storage paths
- System parameters
### API Access
- System status: `http://localhost:8000/system/status`
- Camera status: `http://localhost:8000/cameras`
- Manual recording: `POST http://localhost:8000/cameras/camera1/start-recording`
- Real-time updates: WebSocket at `ws://localhost:8000/ws`
## 📊 Test Results
All system tests passed successfully:
- ✅ Module imports
- ✅ Configuration loading
- ✅ Camera discovery (found 2 cameras)
- ✅ Storage setup
- ✅ MQTT configuration
- ✅ System initialization
- ✅ API endpoints
## 🔧 System Behavior
### Automatic Recording Flow
1. **Machine turns ON** → MQTT message received → Recording starts automatically
2. **Machine turns OFF** → MQTT message received → Recording stops and saves file
3. **Files saved** with timestamp: `camera1_recording_YYYYMMDD_HHMMSS.avi`
### Manual Control
- Start/stop recording via API calls
- Monitor system status in real-time
- Check camera availability on demand
### Dashboard Integration
The system is designed to integrate with your React + Vite + Tailwind + Supabase dashboard:
- REST API for status queries
- WebSocket for real-time updates
- JSON responses for easy frontend consumption
## 📁 Project Structure
```
usda_vision_system/
├── core/ # Configuration, state management, events, logging
├── mqtt/ # MQTT client and message handlers
├── camera/ # Camera management, monitoring, recording
├── storage/ # File organization and management
├── api/ # FastAPI server and WebSocket support
└── main.py # Application coordinator
Supporting Files:
├── main.py # Entry point script
├── config.json # System configuration
├── test_system.py # Test suite
├── start_system.sh # Startup script
└── README_SYSTEM.md # Comprehensive documentation
```
## 🎯 Key Features Delivered
-**Dual MQTT topic listening** for two machines
-**Automatic camera recording** triggered by machine states
-**GigE camera support** using python demo library
-**Thread-safe multi-tasking** (MQTT + camera monitoring + recording)
-**Timestamp-based file naming** in organized directories
-**2-second camera status monitoring** with on-demand checks
-**REST API and WebSocket** for dashboard integration
-**Comprehensive logging** with error tracking
-**Configuration management** via JSON
-**Storage management** with cleanup capabilities
-**Graceful startup/shutdown** with signal handling
## 🔮 Ready for Dashboard Integration
The system provides everything needed for your React dashboard:
```javascript
// Example API usage
const systemStatus = await fetch('http://localhost:8000/system/status');
const cameras = await fetch('http://localhost:8000/cameras');
// WebSocket for real-time updates
const ws = new WebSocket('ws://localhost:8000/ws');
ws.onmessage = (event) => {
const update = JSON.parse(event.data);
// Handle real-time system updates
};
// Manual recording control
await fetch('http://localhost:8000/cameras/camera1/start-recording', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ camera_name: 'camera1' })
});
```
## 🎊 Next Steps
The system is production-ready! You can now:
1. **Deploy** the system on your target hardware
2. **Integrate** with your existing React dashboard
3. **Configure** MQTT topics and camera settings as needed
4. **Monitor** system performance through logs and API endpoints
5. **Extend** functionality as requirements evolve
The modular architecture makes it easy to add new features, cameras, or MQTT topics in the future.
---
**System Status**: ✅ **FULLY OPERATIONAL**
**Test Results**: ✅ **ALL TESTS PASSING**
**Cameras Detected**: ✅ **2 GIGE CAMERAS READY**
**Ready for Production**: ✅ **YES**