{"id":18000204,"url":"https://github.com/afnanksalal/waste-detection","last_synced_at":"2026-05-09T14:34:34.420Z","repository":{"id":258609003,"uuid":"874260027","full_name":"Afnanksalal/Waste-Detection","owner":"Afnanksalal","description":"This project implements a waste classification system that uses a custom YOLO model for detecting and categorizing waste materials. 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It integrates with an Arduino to communicate the classification results.\n\n## Table of Contents\n\n- [Features](#features)\n- [Requirements](#requirements)\n- [Installation](#installation)\n- [Usage](#usage)\n- [Results](#results)\n- [Output Images](#output-images)\n- [Contributing](#contributing)\n- [License](#license)\n\n## Features\n\n- Real-time waste classification using a webcam and YOLO model.\n- Categorizes items into burnable and non-burnable waste.\n- Sends classification results to an Arduino for further processing.\n- Web interface for streaming video and viewing detection results.\n\n## Requirements\n\n- Python 3.8 or higher\n- See `requirements.txt` for a complete list of dependencies.\n\n## Installation\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/Afnanksalal/customyolowastesorting.git\n   cd repository-name\n   ```\n\n2. Create a virtual environment (optional but recommended):\n   ```bash\n   python -m venv venv\n   source venv/bin/activate  # On Windows use `venv\\Scripts\\activate`\n   ```\n\n3. Install the required packages:\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n4. Place your YOLO model file (`best.pt`) in the project directory.\n\n## Usage\n\n1. Connect your Arduino to the computer and ensure the correct COM port is set in the code.\n2. Run the FastAPI application:\n   ```bash\n   python main.py\n   ```\n\n3. Open your web browser and go to `http://localhost:8000` to access the web interface.\n\n4. The webcam feed will display detected waste items, and the classification status will be sent to the Arduino.\n\n## Output\n\n![Output](images/output.jpg)\n\n## Results\n\n![Result](images/results.png)\n*Result*\n\n![Normalized Confusion Matrix](images/confusion_matrix_normalized.png)\n*Normalized Confusion Matrix*\n\n![PR Curve](images/PR_curve.png)\n*PR Curve*\n\n![P Curve](images/P_curve.png)\n*P Curve*\n\n![R Curve](images/R_curve.png)\n*R Curve*\n\n![F1 Curve](images/F1_curve.png)\n*F1 Curve*\n\n## Contributing\n\nContributions are welcome! Please open an issue or submit a pull request for any enhancements or bug fixes.\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fafnanksalal%2Fwaste-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fafnanksalal%2Fwaste-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fafnanksalal%2Fwaste-detection/lists"}