Traffic-Intersection-Monitoring/qt_app_pyside1/README.md

PySide6 Traffic Monitoring Dashboard (Advanced)

Features

• Real-time video detection (OpenVINO, YOLO)
• Drag-and-drop video/image, webcam, RTSP
• Live overlays (bounding boxes, labels, violations)
• Analytics: trends, histograms, summary cards
• Violations: searchable, filterable, snapshot preview
• Export: CSV/JSON, config editor, reload/apply
• Sidebar: device, thresholds, toggles, dark/light mode
• Performance overlay: CPU, RAM, FPS, backend
• Modern UI: QSS, icons, rounded corners, animations

Structure

qt_app_pyside/
├── main.py
├── ui/
│   ├── main_window.py
│   ├── live_tab.py
│   ├── analytics_tab.py
│   ├── violations_tab.py
│   ├── export_tab.py
│   └── config_panel.py
├── controllers/
│   ├── video_controller.py
│   ├── analytics_controller.py
│   └── performance_overlay.py
├── utils/
│   ├── helpers.py
│   └── annotation_utils.py
├── resources/
│   ├── icons/
│   ├── style.qss
│   └── themes/
│       ├── dark.qss
│       └── light.qss
├── config.json
├── requirements.txt

Usage

1. Install requirements: pip install -r requirements.txt

2. Run the application (several options):

   • Recommended: Use the enhanced controller: python run_app.py
   • Standard mode: python main.py

Enhanced Features

The application now includes an enhanced video controller that is automatically activated at startup:

• ✅ Async Inference Pipeline: Better frame rate and responsiveness
• ✅ FP16 Precision: Optimized for CPU performance
• ✅ Separate FPS Tracking: UI and detection metrics are tracked separately
• ✅ Auto Model Selection: Uses optimal model based on device (yolo11n for CPU, yolo11x for GPU)
• ✅ OpenVINO Embedder: Optimized DeepSORT tracking with OpenVINO backend

Integration

• Plug in your detection logic from detection_openvino.py and violation_openvino.py in the controllers.
• Use config.json for all parameters.
• Extend UI/controllers for advanced analytics, export, and overlays.

Troubleshooting

If you encounter import errors:

• Try running with python run_app.py which handles import paths automatically
• Ensure you have all required dependencies installed
• Check that the correct model files exist in the openvino_models directory