MultiDiffusion
stable-diffusion-webui-two-shot
MultiDiffusion | stable-diffusion-webui-two-shot | |
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13 | 29 | |
911 | 412 | |
- | - | |
4.8 | 3.7 | |
8 months ago | 6 months ago | |
Jupyter Notebook | Python | |
- | MIT License |
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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.
stable-diffusion-webui-two-shot
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How do I create widescreen images (21:9) and tell SD to paint the person in the middle?
I tried Regional Prompter and Latent Couple (https://github.com/ashen-sensored/stable-diffusion-webui-two-shot) extension but they don't seem to work properly (latter has awful documentation/examples).
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Consistent environment setup for multiple scenes
Option 5 is to buy a smallish GPU farm and simply rely on good specific and regional prompting pushed through brute forced generations to extract similar looking places out of the thousands of hallucinations. Some loras, checkpoints, regional prompting with the Latent Couple extension in A1111, and an abundant abuse of ControlNet could also help.
- “Elon Musk and Mark Zuckerberg in a cage fight.” (SDXL 0.9)
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Multi-diffusion with LORAs?
Use Latent Couple with Composable LoRA instead
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Why can't it generate people separately? It always seems to combine them. How do I fix this? In this case it is Dwayne Johnson and Kevin Hart.
The solution to this is to use the 'Latent Couple' plugin.
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[Frostveil Series] Up the mountain trail...
All three used the same prompt, which requires the Latent Couple extension.
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MultiDiffusion Region Control plugin for A1111 not installing
git clone -b feature/mask_selection https://github.com/ashen-sensored/stable-diffusion-webui-two-shot.git
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A Simple Comparison of 4 Latest Image Upscaling Strategy in Stable Diffusion WebUI
There are some extensions that break things even when they're disabled. If you're using Latent Couple (two shot), uninstall / delete the folder and and use this fork: https://github.com/ashen-sensored/stable-diffusion-webui-two-shot
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Frostveil, the Nordic realm
I used the Latent Couple extension with the following mask:
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How do I describe an object without those properties being applied to a different part of my image.
I was thinking about this extension.
What are some alternatives?
sd-webui-controlnet - WebUI extension for ControlNet
sd-webui-latent-couple - Latent Couple extension (two shot diffusion port)
mixture-of-diffusers - Mixture of Diffusers for scene composition and high resolution image generation
sd-webui-regional-prompter - set prompt to divided region
Diffusion-Models-Papers-Survey-Taxonomy - Diffusion model papers, survey, and taxonomy
multidiffusion-upscaler-for-automatic1111 - Tiled Diffusion and VAE optimize, licensed under CC BY-NC-SA 4.0
stable-diffusion-videos - Create 🔥 videos with Stable Diffusion by exploring the latent space and morphing between text prompts
stable-diffusion-webui-two-shot - Latent Couple extension (two shot diffusion port)
openpose-editor - Openpose Editor for AUTOMATIC1111's stable-diffusion-webui
sd-webui-stablesr - StableSR for Stable Diffusion WebUI - Ultra High-quality Image Upscaler
stable-diffusion-webui-sonar - Wrapped k-diffuison samplers with tricks to improve the generated image quality (maybe?), extension script for AUTOMATIC1111/stable-diffusion-webui
InvokeAI - InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.