Classification with PyTorch

This repository provides a template for image classification projects using PyTorch. It includes a Jupyter notebook (main.ipynb) that contains the main code for the project.

🚀 Getting Started

1. Clone this repository to your local machine.
2. Install the required dependencies listed in requirements.txt.
3. Open the main.ipynb Jupyter notebook and follow the instructions.

📂 Data Organization

Your data should be organized in the following structure:

├───Database
│   ├───cache # This folder will be created by the program
│   └───Data # Put all the folders with images here
#       Example ⬎
│       ├───battery
│       ├───biological
│       ├───brown-glass
│       ...
│       └───white-glass

Each subfolder in the Data directory represents a class, and should contain the images for that class. For example, the battery folder should contain images of batteries, the biological folder should contain images of biological items, and so on.

📃 READMEs in Folders

Each folder contains a README file that explains the contents of the folder. Please read these files for more information about the data.

📦 Running the Code

To run the code, simply open the main.ipynb Jupyter notebook and execute the cells in order.

📚 Citing

@software{Hamedi_PyTorch-Project-Template,
author = {Aydin Hamedi},
license = {MIT},
title = {PyTorch-Project-Template},
url = {https://github.com/Aydinhamedi/PyTorch-Project-Template}
}

License

This project is licensed under the MIT License. See the LICENSE file for details.

 Copyright (c) 2024 Aydin Hamedi
 
 This software is released under the MIT License.
 https://opensource.org/licenses/MIT