https://github.com/aidinhamedi/pytorch-garbage-classification
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%.
https://github.com/aidinhamedi/pytorch-garbage-classification
Science Score: 13.0%
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Low similarity (12.3%) to scientific vocabulary
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Repository
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%.
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Metadata Files
README.md
Garbage Classification with PyTorch
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%.
🚧 I made a new version here: https://github.com/Aydinhamedi/Pytorch-Garbage-Classification-V2 with a significantly improved training process + code and a different dataset 🚧
Dataset
The dataset used for this project is the Garbage Classification (12 classes) Dataset from Kaggle. It contains images of garbage, divided into twelve categories.
Model
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.
Installation
To run the code in this repository, you will need to install the required libraries. You can do this by running the following command:
bash
pip install -r requirements.txt
Usage
The main code for this project is in a Jupyter notebook named Main.ipynb. To run the notebook, use the following command:
bash
jupyter notebook Main.ipynb
Results
Our 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.
License
Copyright (c) 2024 Aydin Hamedi This software is released under the MIT License. https://opensource.org/licenses/MIT
Owner
- Name: Aidin
- Login: AidinHamedi
- Kind: user
- Repositories: 1
- Profile: https://github.com/AidinHamedi
Segmentation fault
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