Welcome to the repository of our garbage classification project! We have developed a model using PyTorch and EfficientNet-B4 that classifies garbage into twelve different types. The model has achieved an impressive accuracy of 98.45%.
The dataset used for this project is the Garbage Classification (12 classes) Dataset from Kaggle. It contains images of garbage, divided into twelve categories.
We used the EfficientNet-B4 model for this project. EfficientNet-B4 is a convolutional neural network that is pretrained on the ImageNet dataset. It is known for its efficiency and high performance on a variety of image classification tasks.
To run the code in this repository, you will need to install the required libraries. You can do this by running the following command:
pip install -r requirements.txtThe main code for this project is in a Jupyter notebook named Main.ipynb. To run the notebook, use the following command:
jupyter notebook Main.ipynbOur model achieved an accuracy of 98.45% on the test set. This is a significant improvement over previous models, demonstrating the power of EfficientNet-B4 and PyTorch.
Copyright (c) 2024 Aydin Hamedi This software is released under the MIT License. https://opensource.org/licenses/MIT