Dreambooth-Stable-Diffusion
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion (tweaks focused on training faces) (by kanewallmann)
Dreambooth-Stable-Diffusion | SD-Regularization-Images-Style-Dreambooth | |
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12 | 7 | |
144 | 29 | |
- | - | |
10.0 | 10.0 | |
over 1 year ago | over 1 year ago | |
Jupyter Notebook | ||
MIT License | - |
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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.
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 2022-11-07.
- DreamBooth Tutorial (using filewords)
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Comic Diffusion V2. This is a culmination of everything worked towards so far. Trained on 6 styles at the same time, mix and match any number of them to create multiple different unique and consistent styles.
Run !git clone https://github.com/kanewallmann/Dreambooth-Stable-Diffusion.git in a separate notebook to clone kane’s repo.
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how to train person and (several) styles at the same time?
Unfortunately I tried the kanewallmann's ( https://github.com/kanewallmann/Dreambooth-Stable-Diffusion ) fork without success. I followed the instructions for a person and a style (20+20 images), I created folders with the correct naming convention in training_images (/person/ name_person xxx, style/ name_style xxx) and downloaded the regularization images for person and for style. I tried 3 times with different steps (3000, 4000, 5000) and the training stopped at 70 - 95% and the reason is ''isadirectoryerror: [Errno 21]'' Any idea about this? I ran this on runpod because on
- cyberpunk police in snowy streets using a custom trained model 👮
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ConceptsDreambooth [MEGATHREAD] Live now! Including the new steps formula! Link to the repo and instructions inside.
We sure can! Somebody actually already figured that one out here. I've had some success with that method, but we're trying to implement a way that has less interference between the tokens and sort out the optimal steps for training in multiples with varying amounts of training images.
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Understanding Dreambooth Correctly?
there is a dreambooth repo fork that helps with training two tokens. maybe give it a try
- Multiple dreambooth tokens on a single checkpoint file
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Train Model with 2 persons!?
You have to use this: https://github.com/kanewallmann/Dreambooth-Stable-Diffusion
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Struggling with an issue producing two separate prompts in Dreambooth - and was hoping someone might have some insight.
This is the only repo I know of that can train more than one subject for Dreambooth: https://github.com/kanewallmann/Dreambooth-Stable-Diffusion
- Dreambooth repo that may allow training of multiple people
SD-Regularization-Images-Style-Dreambooth
Posts with mentions or reviews of SD-Regularization-Images-Style-Dreambooth.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-07.
- Comic Diffusion V2. This is a culmination of everything worked towards so far. Trained on 6 styles at the same time, mix and match any number of them to create multiple different unique and consistent styles.
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Question about training styles
I'm using the Joe Penna's repo on runpod and using only 20 training images and 1700 reg images from https://github.com/aitrepreneur/SD-Regularization-Images-Style-Dreambooth to trin styles. I'm getting very good results.
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Classic Disney animation dreambooth model
I'm new to using dreambooth, but I followed the steps in some of the recent trending examples to make a "classic disney" art style. I pulled/cropped/reframed about 50 reference images, and used the style examples [from here](https://github.com/aitrepreneur/SD-Regularization-Images-Style-Dreambooth), trained with 6400 steps. Colors are typically oversaturated, and it's really hard to control. I've also found that adding artists helps balance the composition out a lot. Here are some of the sample outputs!
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Fine-tuned the model on Kurzgesagt videos with DreamBooth. Here are some results.
I've used this repository for regularization images. And these options for training: --class_word "style" --token "kurzgesagt"
- 2D Illustration Styles are scarce on Stable Diffusion so i created a dreambooth model inspired by Hollie Mengert's work
- Hello, i saw that you can train dreambooth for a style, I tried taring dreambooth on vast.ai for a children book illustration style but I got pretty awful result, any ideas what went wrong.
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I've further refined my Studio Ghilbi Model
I used around 20,000 steps (I forgot to look at number of steps when I stopped training). The regulation images I used can be obtained at https://github.com/aitrepreneur/SD-Regularization-Images-Style-Dreambooth
What are some alternatives?
When comparing Dreambooth-Stable-Diffusion and SD-Regularization-Images-Style-Dreambooth you can also consider the following projects:
Stable-Diffusion-Regularization-Images - For use with fine-tuning, especially the current implementation of "Dreambooth".
Dreambooth-Regularization - All the regs
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.
ConceptsDreambooth - ConceptsDreambooth
Dreambooth-SD-optimized - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
Txt2Vectorgraphics - Custom Script for Automatics1111 StableDiffusion-WebUI.
Dreambooth-Stable-Diffusion vs Stable-Diffusion-Regularization-Images
SD-Regularization-Images-Style-Dreambooth vs Stable-Diffusion-Regularization-Images
Dreambooth-Stable-Diffusion vs Dreambooth-Regularization
SD-Regularization-Images-Style-Dreambooth vs Dreambooth-Stable-Diffusion
Dreambooth-Stable-Diffusion vs ConceptsDreambooth
SD-Regularization-Images-Style-Dreambooth vs Dreambooth-Regularization
SD-Regularization-Images-Style-Dreambooth vs Dreambooth-SD-optimized
SD-Regularization-Images-Style-Dreambooth vs Txt2Vectorgraphics