yolo-object-detection / Project_info /Updated_structure
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Deploying Streamlit YOLO application with CPU-optimized weights
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ObjectDetectionProject/
β”œβ”€β”€ app/
β”‚ β”œβ”€β”€ __init__.py
β”‚ β”œβ”€β”€ detector.py # YOLO detection logic
β”‚ β”œβ”€β”€ api.py # REST API endpoints
β”‚ β”œβ”€β”€ security.py # Auth, rate limiting, validation
β”‚ β”œβ”€β”€ database.py # Data persistence
β”‚ β”œβ”€β”€ config.py # Configuration management
β”‚ └── models.py # Data models
β”œβ”€β”€ gui/
β”‚ β”œβ”€β”€ __init__.py
β”‚ β”œβ”€β”€ main_window.py # Tkinter GUI
β”‚ └── utils.py # GUI utilities
β”œβ”€β”€ tests/
β”‚ β”œβ”€β”€ test_api.py
β”‚ β”œβ”€β”€ test_detector.py
β”‚ └── test_security.py
β”œβ”€β”€ deployment/
β”‚ β”œβ”€β”€ Dockerfile
β”‚ β”œβ”€β”€ docker-compose.yml
β”‚ β”œβ”€β”€ nginx.conf
β”‚ └── gunicorn.conf.py
β”œβ”€β”€ scripts/
β”‚ β”œβ”€β”€ train_custom.py # Custom model training
β”‚ └── export_onnx.py # Model export for deployment
β”œβ”€β”€ requirements.txt
β”œβ”€β”€ README.md
└── .env.example