AI Plastic Detector

An AI-powered system for detecting plastic waste using drone images. By leveraging machine learning and the YOLO algorithm, the system identifies various types of plastic waste in real-time, enhancing waste management efficiency in hard-to-reach areas.

Table of Contents

• Introduction
• Features
• Installation
• Usage
• Contributing
• License

Introduction

Plastic waste is a major environmental issue that affects ecosystems worldwide. The AI Plastic Detector aims to address this problem by using advanced AI models to detect and classify plastic waste in real-time. This system leverages the YOLO (You Only Look Once) algorithm to provide accurate and efficient waste detection.

Features

• Real-time Detection: Utilizes the YOLO algorithm for fast and accurate identification of plastic waste.
• Image Upload: Works by uploading drone images, which are then processed to mark detected plastic waste.
• Machine Learning: Trained on a diverse dataset of plastic waste images to improve detection accuracy.
• Scalability: Can be deployed in various environments, from urban areas to remote locations.

To use the AI Plastic Detector, navigate to the link: https://aiplasticdetector.streamlit.app/

Alternatively, to run the application locally, follow the Installation and Usage steps:

Installation

To install and set up the AI Plastic Detector, follow these steps:

1. Clone the repository:

   git clone https://github.com/CIumsy/AI_Plastic_Detector.git
   cd AI_Plastic_Detector

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

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

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

To use the AI Plastic Detector, follow these steps:

1. Run the detection script:

   python detect_plastic.py --input <input_image_folder> --output <output_folder>

   Replace <input_image_folder> with the path to your folder containing drone images and <output_folder> with the desired path for the output images.

2. View the results: The output images will show the detected plastic waste with bounding boxes and labels.

Contributing

We welcome contributions to the AI Plastic Detector project. If you have any ideas, suggestions, or improvements, feel free to submit a pull request or open an issue.

1. Fork the repository.

2. Create a new branch:

   git checkout -b feature-branch

3. Make your changes and commit them:

   git commit -m "Description of your changes"

4. Push to the branch:

   git push origin feature-branch

5. Open a pull request.