AI-Driven Waste Classifier for Effective Recycling Practices
The objective of this project is to develop a comprehensive waste classification system for analyzing images or videos to accurately categorize different types of waste. By implementing computer vision techniques, the system aims to automate and optimize waste sorting processes, leading to improved recycling efforts, reduced environmental pollution, and enhanced resource utilization. The project's goal is to provide an intelligent solution that benefits waste management facilities, recycling industries, environmental organizations, and society at large by promoting sustainable practices and minimizing waste mismanagement. (Under the topic of Sustainable Practices Promotion)
https://www.kaggle.com/datasets/asdasdasasdas/garbage-classification
https://www.kaggle.com/datasets/mostafaabla/garbage-classification
Any python editor can be used.
- Install Python and required libraries (OpenCV, TensorFlow, matplotlib).
- Organize the project structure with appropriate directories.
- Prepare and organize your image dataset.
- Update code paths for dataset and implement model training if desired.
- Run the code and follow instructions for camera capture or image upload.
Bin types:
- Battery Bin
- Donate clothes/shoes
- E-waste Bin
- Glass Bin
- Metal Bin
- Organic Bin
- Paper Bin
- Plastic Bin
Waste categories(Labels):
- White glass, Green glass, Brown glass
- Food items
- Plastic, Trash
- Metal
- Paper, Cardboard
- Battery
- Shoes, Clothes
- CAPTURE FROM CAMERA(VIDEO):
- UPLOAD IMAGE:
