Waste Classification System using YOLO and Arduino

This project implements a waste classification system that uses a custom YOLO model for detecting and categorizing waste materials. It integrates with an Arduino to communicate the classification results.

Table of Contents

• Features
• Requirements
• Installation
• Usage
• Results
• Output Images
• Contributing
• License

Features

• Real-time waste classification using a webcam and YOLO model.
• Categorizes items into burnable and non-burnable waste.
• Sends classification results to an Arduino for further processing.
• Web interface for streaming video and viewing detection results.

Requirements

• Python 3.8 or higher
• See requirements.txt for a complete list of dependencies.

Installation

1. Clone the repository:

   git clone https://github.com/Afnanksalal/customyolowastesorting.git
   cd repository-name

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

4. Place your YOLO model file (best.pt) in the project directory.

Usage

1. Connect your Arduino to the computer and ensure the correct COM port is set in the code.

2. Run the FastAPI application:

   python main.py

3. Open your web browser and go to http://localhost:8000 to access the web interface.

4. The webcam feed will display detected waste items, and the classification status will be sent to the Arduino.

Output

Results

Result

Normalized Confusion Matrix

PR Curve

P Curve

R Curve

F1 Curve

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any enhancements or bug fixes.

License

This project is licensed under the MIT License. See the LICENSE file for details.