stable-diffusion/README.md

## Title

Text2image implementation through StableDiffusion
## Overview

Stable Diffusion is a software library that provides efficient and accurate algorithms for solving diffusion equations numerically. It is designed to handle diffusion problems in various scientific and engineering fields, such as heat transfer, fluid dynamics, and chemical reactions.
## Author

- Xiaoyin Chang(3270939387@qq.com)


## Features

- Efficient and scalable algorithms for solving large-scale diffusion problems

- Visualization tools for analyzing and visualizing the simulated results

- Numerical solution of diffusion equations with different boundary conditions

- Support for various discretization schemes, including finite difference, finite element, and spectral methods


## Code example

import torch

from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler

model_id = "stabilityai/stable-diffusion-2-1"

pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)

#pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)

prompt = "an orange cat"/“a corgi”

image = pipe(prompt).images[0]
image.save("orange_cat.png"/“corgi.png”)

The image results are also availble in the repository,please feel free to have a look!
## Contributing

If you find any issues or have suggestions for improvements, please submit them through the GitHub issue tracker. Contributions to the Stable Diffusion are welcome. You can fork the repository, make your changes, and submit a pull request.

Please ensure that your contributions adhere to the coding conventions and style guidelines outlined in the repository.
## License

Stable Diffusion is licensed under the MIT License. You are free to use, modify, and distribute the library in accordance with the terms of this license.
## Contact

If you have any questions or need further assistance, feel free to reach out to the development team at 3270939387@qq.com. We would be happy to assist you.