This repository contains a stable diffusion costumed pipeline for generating images from images. The project aims to develop a robust system that leverages image-to-image generation techniques to create new images based on existing images. The pipeline utilizes a diffusion model and provides a stable and reliable approach to image generation.
Image-to-image generation is a challenging task that involves generating new images based on existing ones. This project focuses on developing a stable diffusion costumed pipeline for image generation. By utilizing diffusion models and other techniques, the pipeline provides a reliable and effective approach to generate high-quality images from given input images.
To use the code in this repository, follow these steps:
- Clone the repository:
git clone https://github.com/your-username/img-2-img-generation.git - Navigate to the project directory:
cd img-2-img-generation - Install the required dependencies:
pip install -r requirements.txt
- Ensure you have installed the required dependencies.
- Prepare your input images and save them in the appropriate format.
- Modify the code to load and process your input images.
- Run the pipeline script to generate new images based on the provided inputs.
- View and analyze the generated images.
- Experiment with different model configurations and parameters to achieve desired results.
The project is implemented using the following technologies and libraries:
- Python
- PyTorch
- Diffusers
- NumPy
- Transformers
- PIL (Python Imaging Library)
- Matplotlib
- Scipy
- Ftfy
- Accelerate
Contributions to this project are welcome. To contribute, follow these steps:
- Fork the repository.
- Create a new branch:
git checkout -b feature/your-feature - Make your changes and commit them:
git commit -m 'Add some feature' - Push to the branch:
git push origin feature/your-feature - Submit a pull request.
This project is licensed under the MIT License.