CNN waste classification
A convolutional neural network project for classifying waste images. Training and experiments live in a Jupyter notebook; the best weights, class labels, and a small Streamlit app let you run inference in the browser on Streamlit Community Cloud.
Overview
The repository includes a trained model checkpoint (best_waste_model.pth), class_names.json, loader utilities, and streamlit_app.py for uploading an image and viewing predictions. A companion notebook (cnn_experiments.ipynb) documents the modeling workflow.
Tech & Tools
- Python, PyTorch
- CNN image classification
- Streamlit (
requirements-streamlit.txtfor cloud deploy) - Jupyter for experiments
Links
See the repo’s STREAMLIT.md and verify_streamlit_ready.py for deployment checks. Treat predictions as demonstrations; real waste-sorting systems need validation for your environment and regulations.
