stable-diffusion-2-gui
MultiDiffusion
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604 | 911 | |
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3.9 | 4.8 | |
9 months ago | 8 months ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | - |
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stable-diffusion-2-gui
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You don't need a fancy PC to get speedy results (4.6 it/s with SD 2.1 on 7 year old hardware, only 8GB RAM, used RTX 2060))
I tried many of the GUI installers listed in the wiki here but most require a minimum of 16GB system RAM. I found a very useful SD 2.1 colab on github, which once I'd installed the dependencies generated images at the typical rates for a 2060 without using up all the system RAM.
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depth2img support added to Stability AI's Stable Diffusion v 2.1 web UI
Stable Diffusion v 2.1 web UI github repo and a colab notebook.
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question on UI for 2.1
Stability.ai has their own GUI for SD 2.x but you don't need to use it. A1111 webui works fine with 2.1 for me. It generally gets updated very quickly whenever something new comes out.
- Can we start a list of Stable Diffusion 2.0 compatible UI's?
MultiDiffusion
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Opendream: A Non-Destructive UI for Stable Diffusion
For composing this approach works pretty well
https://multidiffusion.github.io/
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Messing with the denoising loop can allow you to reach new places in latent space. Over 8+ different research papers/Auto1111 extension ideas in a single pipe. Load once and do lots of different things (SD 2.1 or 1.5)
So I've continued to experiment with how many papers I can fit into a single pipe and have them play nicely together. The images below were created by combining the panorama code from omerbt/MultiDiffusion with the ideas from albarji/mixture-of-diffusers. Also turns out nateraw/stable-diffusion-videos can be seen as a special case of a panorama (in latent space rather than prompt space).
- MultiDiffusion Region Control, a prompt on each mask webui extension is out.
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Hubble Diffusion with MultiDiffusion
Essentially, I fine-tuned Stable Diffusion 2.1 base (the 512x512) model on the ESA Hubble Deep Space Images & Captions dataset I collected from public Hubble images & captions. After around 33,000 training steps, I saved the model and was really impressed by the results. But I really wanted to be able to generate wallpaper-level quality space images, so I stumbled upon MultiDiffusion: a new project for generating massive panorama images using stable diffusion models. I then used hubble-diffusion-2 along with MultiDiffusion to generate each one of these amazing 2560x1536 images. Each image took a little over an hour to generate on a Google Colab T4 GPU. I used the following prompts for each of these images:
- MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation
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What is the maximum size a 3090 24gb can produce?
If you need generated and not upscaled 4k for some reason, try something like https://github.com/omerbt/MultiDiffusion
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[R] [N] "MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation" enables controllable image generation without any further training or finetuning of diffusion models.
Project: https://multidiffusion.github.io/ Paper: https://arxiv.org/abs/2302.08113 GitHub: https://github.com/omerbt/MultiDiffusion
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Meet MultiDiffusion: A Unified AI Framework That Enables Versatile And Controllable Image Generation Using A Pre-Trained Text-to-Image Diffusion Model
Quick Read: https://www.marktechpost.com/2023/02/24/meet-multidiffusion-a-unified-ai-framework-that-enables-versatile-and-controllable-image-generation-using-a-pre-trained-text-to-image-diffusion-model/ Paper: https://arxiv.org/abs/2302.08113 Github: https://github.com/omerbt/MultiDiffusion Project: https://multidiffusion.github.io/
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You to can create Panorama images 512x10240+ (not a typo) using less then 6GB VRAM (Vertorama works too). A modification of the MultiDiffusion code to pass the image through the VAE in slices then reassemble. Potato computers of the world rejoice.
So I haven't made many images with Stable Diffusion despite using it heavily. The reason is I've been messing with the internals of the diffusion pipe, to interfere with the diffusion process in different ways. Todays fun result is based on omerbt/MultiDiffusion for making panoramas.
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First version of Stable Diffusion was released on August 22, 2022
If we combine Mixture of Diffusers + MultiDiffusion+ Composer+ cross-domain-compositing and probably some more I'm not thinking of.
What are some alternatives?
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion-webui-two-shot - Latent Couple extension (two shot diffusion port)
Stable-Diffusion-2.0-CPU-or-GPU-Colab-Gradio - Config files for my GitHub profile.
sd-webui-controlnet - WebUI extension for ControlNet
sd_lite - set-up Stable Diffusion with minimal dependencies and a single multi-function pipe
mixture-of-diffusers - Mixture of Diffusers for scene composition and high resolution image generation
Dreambooth-Stable-Diffusion - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) by way of Textual Inversion (https://arxiv.org/abs/2208.01618) for Stable Diffusion (https://arxiv.org/abs/2112.10752). Tweaks focused on training faces, objects, and styles.
Diffusion-Models-Papers-Survey-Taxonomy - Diffusion model papers, survey, and taxonomy
stable-diffusion-videos - Create 🔥 videos with Stable Diffusion by exploring the latent space and morphing between text prompts
openpose-editor - Openpose Editor for AUTOMATIC1111's stable-diffusion-webui
stable-diffusion-webui-sonar - Wrapped k-diffuison samplers with tricks to improve the generated image quality (maybe?), extension script for AUTOMATIC1111/stable-diffusion-webui
blended-latent-diffusion - Official implementation for "Blended Latent Diffusion" [SIGGRAPH 2023]