75 lines
2.4 KiB
Markdown
75 lines
2.4 KiB
Markdown
# PySide6 Traffic Monitoring Dashboard (Advanced)
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## Features
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- Real-time video detection (OpenVINO, YOLO)
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- Drag-and-drop video/image, webcam, RTSP
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- Live overlays (bounding boxes, labels, violations)
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- Analytics: trends, histograms, summary cards
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- Violations: searchable, filterable, snapshot preview
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- Export: CSV/JSON, config editor, reload/apply
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- Sidebar: device, thresholds, toggles, dark/light mode
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- Performance overlay: CPU, RAM, FPS, backend
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- Modern UI: QSS, icons, rounded corners, animations
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## Structure
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```
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qt_app_pyside/
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├── main.py
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├── ui/
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│ ├── main_window.py
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│ ├── live_tab.py
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│ ├── analytics_tab.py
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│ ├── violations_tab.py
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│ ├── export_tab.py
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│ └── config_panel.py
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├── controllers/
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│ ├── video_controller.py
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│ ├── analytics_controller.py
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│ └── performance_overlay.py
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├── utils/
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│ ├── helpers.py
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│ └── annotation_utils.py
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├── resources/
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│ ├── icons/
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│ ├── style.qss
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│ └── themes/
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│ ├── dark.qss
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│ └── light.qss
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├── config.json
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├── requirements.txt
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```
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## Usage
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1. Install requirements: `pip install -r requirements.txt`
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2. Run the application (several options):
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- **Recommended**: Use the enhanced controller: `python run_app.py`
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- Standard mode: `python main.py`
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## Enhanced Features
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The application now includes an enhanced video controller that is automatically activated at startup:
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- ✅ **Async Inference Pipeline**: Better frame rate and responsiveness
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- ✅ **FP16 Precision**: Optimized for CPU performance
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- ✅ **Separate FPS Tracking**: UI and detection metrics are tracked separately
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- ✅ **Auto Model Selection**: Uses optimal model based on device (yolo11n for CPU, yolo11x for GPU)
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- ✅ **OpenVINO Embedder**: Optimized DeepSORT tracking with OpenVINO backend
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## Integration
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- Plug in your detection logic from `detection_openvino.py` and `violation_openvino.py` in the controllers.
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- Use `config.json` for all parameters.
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- Extend UI/controllers for advanced analytics, export, and overlays.
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## Troubleshooting
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If you encounter import errors:
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- Try running with `python run_app.py` which handles import paths automatically
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- Ensure you have all required dependencies installed
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- Check that the correct model files exist in the openvino_models directory
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