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Stable Diffusion web UI. A browser interface based on Gradio library for Stable Diffusion. Features. Detailed feature showcase with images: Original txt2img and img2img modes. One click install and run script (but you still must install python and git) Outpainting. Inpainting. Color Sketch. Prompt Matrix. Stable Diffusion Upscale.
- Stable Diffusion 2-1 - a Hugging Face Space by stabilityai
Discover amazing ML apps made by the community....
- nolanaatama/stable-diffusion-webui · Hugging Face
Stable Diffusion web UI. A browser interface based on Gradio...
- Stable Diffusion 2-1 - a Hugging Face Space by stabilityai
- More documentation about features, troubleshooting, common issues very soon
- Important
- Stable Diffusion web UI
- Features
- Stable Diffusion
- Stable Diffusion v1
- Comments
Want to help with documentation? Documented something? Use Discussions GFPGAN
If you want to use GFPGAN to improve generated faces, you need to install it separately. Download GFPGANv1.3.pth and put it into the /stable-diffusion/src/gfpgan/experiments/pretrained_models directory.
RealESRGAN
Download RealESRGAN_x4plus.pth and RealESRGAN_x4plus_anime_6B.pth . Put them into the stable-diffusion/src/realesrgan/experiments/pretrained_models directory.
Web UI
When launching, you may get a very long warning message related to some weights not being used. You may freely ignore it. After a while, you will get a message like this: Open the URL in browser, and you are good to go.
🔥 NEW! My fork implemented! This means that now you can generate even bigger-res images, and with low vram mode, up to 1216x1216 on 8 gb vram.
🔥 NEW! webui.cmd updates with any changes in environment.yaml file so the environment will always be up to date as long as you get the new environment.yaml file 🔥
🔥 no need to remove environment, delete src folder and create again, MUCH simpler! 🔥
Features:
•Gradio GUI: Idiot-proof, fully featured frontend for both txt2img and img2img generation
•No more manually typing parameters, now all you have to do is write your prompt and adjust sliders
A browser interface based on Gradio library for Stable Diffusion.
Original script with Gradio UI was written by a kind anonymous user. This is a modification.
GFPGAN
Lets you improve faces in pictures using the GFPGAN model. There is a checkbox in every tab to use GFPGAN at 100%, and also a separate tab that just allows you to use GFPGAN on any picture, with a slider that controls how strongthe effect is.
RealESRGAN
Lets you double the resolution of generated images. There is a checkbox in every tab to use RealESRGAN, and you can choose between the regular upscaler and the anime version. There is also a separate tab for using RealESRGAN on any picture.
Sampling method selection
txt2img samplers: "DDIM", "PLMS", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a', 'k_euler', 'k_heun', 'k_lms' img2img samplers: " DDIM", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a', 'k_euler', 'k_heun', 'k_lms'
Stable Diffusion was made possible thanks to a collaboration with Stability AI and Runway and builds upon our previous work:
High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach*, Andreas Blattmann*, Dominik Lorenz, Patrick Esser, Björn Ommer
CVPR '22 Oral
which is available on GitHub. PDF at arXiv. Please also visit our Project page.
Stable Diffusion is a latent text-to-image diffusion model. Thanks to a generous compute donation from Stability AI and support from LAION, we were able to train a Latent Diffusion Model on 512x512 images from a subset of the LAION-5B database. Similar to Google's Imagen, this model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text prompts. With its 860M UNet and 123M text encoder, the model is relatively lightweight and runs on a GPU with at least 10GB VRAM. See this section below and the model card.
Stable Diffusion v1 refers to a specific configuration of the model architecture that uses a downsampling-factor 8 autoencoder with an 860M UNet and CLIP ViT-L/14 text encoder for the diffusion model. The model was pretrained on 256x256 images and then finetuned on 512x512 images.
*Note: Stable Diffusion v1 is a general text-to-image diffusion model and therefore mirrors biases and (mis-)conceptions that are present in its training data. Details on the training procedure and data, as well as the intended use of the model can be found in the corresponding model card.
•Our codebase for the diffusion models builds heavily on OpenAI's ADM codebase and https://github.com/lucidrains/denoising-diffusion-pytorch . Thanks for open-sourcing!
•The implementation of the transformer encoder is from x-transformers by lucidrains.
Hugging Face Stable Diffusion. Hugging Face is an AI community and platform that promotes open-source contributions. Though it’s highly recognized for its transformer models, hugging face also provides access to the latest Stable diffusion model; and like a true lover of open-source, it’s free.
Stable Diffusion Web UI ( SDUI) is a user-friendly browser interface for the powerful Generative AI model known as Stable Diffusion. This is an advanced AI model capable of generating images from text descriptions or modifying existing images based on textual prompts.
I created a video explaining how to install Stable Diffusion web ui, an open source UI that allows you to run various models that generate images as well as tweak their input params.
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