stable-diffusion-2-gui
Lightweight Stable Diffusion v 2.1 web UI: txt2img, img2img, depth2img, inpaint and upscale4x. (by qunash)
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. (by JoePenna)
| stable-diffusion-2-gui | Dreambooth-Stable-Diffusion | |
|---|---|---|
| 4 | 100 | |
| 604 | 3,167 | |
| - | - | |
| 3.9 | 6.8 | |
| 9 months ago | 4 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
stable-diffusion-2-gui
Posts with mentions or reviews of stable-diffusion-2-gui.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-12-22.
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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?
Dreambooth-Stable-Diffusion
Posts with mentions or reviews of Dreambooth-Stable-Diffusion.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-09.
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Will there be comprehensive tutorials for fine-tuning SD XL when it comes out?
Tons of stuff here, no? https://github.com/JoePenna/Dreambooth-Stable-Diffusion/
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Useful Links
Joe Penna's Dreambooth (Tutorial|24GB) Most popular DB repo with great results.
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Dreambooth / Custom Training / Model - what's the state of the art?
1) The https://github.com/JoePenna/Dreambooth-Stable-Diffusion instructions say to use the 1.5 checkpoints - is that the latest? Can I use the 2+ models or?
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My Experience with Training Real-Person Models: A Summary
I quickly turned to the second library, https://github.com/JoePenna/Dreambooth-Stable-Diffusion, because its readme was very encouraging, and its results were the best. Unfortunately, to use it on Colab, you need to sign up for Colab Pro to use advanced GPUs (at least 24GB of VRAM), and training a model requires at least 14 compute units. As a poor Chinese person, I could only buy Colab Pro from a proxy. The results from JoePenna/Dreambooth-Stable-Diffusion were fantastic, and the preparation was straightforward, requiring only <=20 512*512 photos without writing captions. I used it to create many beautiful photos.
- I Used Stable Diffusion and Dreambooth to Create an Art Portrait of My Dog
- training
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Training a model on Iwanaga Kotoko (from in/spectre), which step do you guys think the model is at its best?
I've found EveryDream to be brilliant and have switched from JoePenna's Dreambooth because I've found I get better results so long as I provide good captions for all the images, even if preparing the dataset takes 3x as long (took me 2 hours to crop and label the 54 images).
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Dreambooth training results for face, object and style datasets with various prior regularization settings.
From what I know you can train with whatever size you want. But you need software that will support it. For example, ShivamShrirao/diffusers repo seems to allow a change of dimension. Also, you need HW that would support the training, because bigger images need more VRAM, for example,Joe Penna repo is using ~23GB with 512x512px so probably it's not a valid option. But the ShivamShrirao repo has optimizations that allow to run it with less VRAM.
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Starting to get quite good results with Dreambooth. What do you think? (Follow @RokStrnisa on Twitter for more.)
This is a good starting place: https://github.com/JoePenna/Dreambooth-Stable-Diffusion
- I'm a N00b with training stuff. Trying to get runpod with Dreambooth training some images (80 total) and I'm getting this error. Help?
What are some alternatives?
When comparing stable-diffusion-2-gui and Dreambooth-Stable-Diffusion you can also consider the following projects:
stable-diffusion-webui - Stable Diffusion web UI
Dreambooth-SD-optimized - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
Stable-Diffusion-2.0-CPU-or-GPU-Colab-Gradio - Config files for my GitHub profile.
Stable-Diffusion-Regularization-Images - For use with fine-tuning, especially the current implementation of "Dreambooth".
sd_lite - set-up Stable Diffusion with minimal dependencies and a single multi-function pipe
A1111-Web-UI-Installer - Complete installer for Automatic1111's infamous Stable Diffusion WebUI
MultiDiffusion - Official Pytorch Implementation for "MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation" presenting "MultiDiffusion" (ICML 2023)
civitai - A repository of models, textual inversions, and more
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-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.
SD-Regularization-Images-Style-Dreambooth
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
stable-diffusion-2-gui vs stable-diffusion-webui
Dreambooth-Stable-Diffusion vs Dreambooth-SD-optimized
stable-diffusion-2-gui vs Stable-Diffusion-2.0-CPU-or-GPU-Colab-Gradio
Dreambooth-Stable-Diffusion vs Stable-Diffusion-Regularization-Images
stable-diffusion-2-gui vs sd_lite
Dreambooth-Stable-Diffusion vs A1111-Web-UI-Installer
stable-diffusion-2-gui vs MultiDiffusion
Dreambooth-Stable-Diffusion vs civitai
Dreambooth-Stable-Diffusion vs stable-diffusion-webui
Dreambooth-Stable-Diffusion vs InvokeAI
Dreambooth-Stable-Diffusion vs SD-Regularization-Images-Style-Dreambooth
Dreambooth-Stable-Diffusion vs fast-stable-diffusion