This project provides a lightweight Gradio-based web UI for Stable Diffusion v2.1, enabling users to perform text-to-image, image-to-image, inpainting, upscaling, and depth-to-image generation. It targets users who want a simple, accessible interface for exploring Stable Diffusion's capabilities without complex setup.

How It Works

The UI leverages the Hugging Face Diffusers library, a popular and robust implementation of diffusion models. It integrates the DPM-Solver for potentially faster and higher-quality sampling, offering a streamlined workflow for various image generation tasks.

Quick Start & Requirements

• Install via pip install -r requirements.txt and run with python app.py.
• Requires Python 3.8+, PyTorch, and Hugging Face Diffusers.
• GPU with CUDA support is highly recommended for reasonable performance.
• Official Colab notebook available: https://colab.research.google.com/github/anzorq/stable-diffusion-2-gui/blob/main/stable_diffusion_2_gui.ipynb

Highlighted Details

• Supports Stable Diffusion v2.1.
• Implements txt2img, img2img, depth2img, inpaint, and upscale4x.
• Built with Gradio for an interactive web interface.
• Utilizes Hugging Face Diffusers library.

Maintenance & Community

• Maintained by qunash.
• Project relies on Hugging Face and CompVis for core components.

Licensing & Compatibility

• The repository does not explicitly state a license. The underlying Stable Diffusion model has its own license, and Hugging Face Diffusers is typically Apache 2.0. Users should verify compatibility for commercial use.

Limitations & Caveats

The project is described as "lightweight" and focuses on Stable Diffusion v2.1, meaning support for other models or advanced features found in more comprehensive UIs may be limited. The lack of an explicit license requires careful consideration for commercial applications.