This repository implements an image classification pipeline for garbage / waste classification using deep learning. The goal is to automatically classify waste images into predefined categories to support recycling, waste sorting, and sustainability workflows.
The full implementation is provided in a Jupyter Notebook for reproducibility.
- Multi-class image classification for waste categories
- Deep learning training workflow (data loading, preprocessing, training, evaluation)
- Training curves (accuracy/loss) visualization
- Notebook-based, easy-to-run and extend
- Python
- TensorFlow / Keras
- NumPy
- Matplotlib
- OpenCV (optional)
- Scikit-learn (optional)
- Jupyter Notebook
garbage-classification-image-classification/
├─ notebooks/
│ └─ Garbage_Classification.ipynb
├─ README.md
├─ requirements.txt
├─ LICENSE
├─ .gitignore
└─ docs/
└─ NOTES.md
pip install -r requirements.txtRun the notebook:
jupyter notebook notebooks/Garbage_Classification.ipynb- Ensure your dataset folder structure matches the notebook expectations (class folders).
- For best results, use a balanced dataset and consistent image sizes.
- Consider adding data augmentation or transfer learning for improved performance.
MIT License