Yume: Image Generation with Diffusion model using PyTorch

Overview

Yume is a project for image generation using Diffusion model implemented in PyTorch.

Features

• Diffusion model for image generation.
• Separate scripts for training and generating images.
• Easy-to-use command-line interface.

Installation

1. Clone the repository:

   git clone https://github.com/zaibutcooler/yume.git
   cd yume

2. Install dependencies:

   pip install -r requirements.txt

Usage

Training

To train the GAN model, use the following command:

```bash
yume-train
```

Generating Images

To generate images with the trained model, use the following command:

```bash
yume-generate
```

Project Structure

• yume/: Python package containing GAN implementation and utilities.
  • generator.py: Implementation of the GAN generator.
  • discriminator.py: Implementation of the GAN discriminator.
  • utils.py: Utility functions.
• requirements.txt: List of project dependencies.
• setup.py: Setup script for installing the package.
• main.py: Example script for using the yume package.

Contributing

Contributions are welcome! Please follow the Contribution Guidelines.

License

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

Acknowledgments

Mention any contributors or libraries that you used or were inspired by.

Contact

• Zai
• zaiyellyintaung@gmail.com
• Project Link: https://github.com/zaibutcooler/yume