Stable-Diffusion-Regularization-Images
diffusers
Stable-Diffusion-Regularization-Images | diffusers | |
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14 | 105 | |
99 | 1,873 | |
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10.0 | 7.0 | |
over 1 year ago | 11 months ago | |
Python | ||
- | Apache License 2.0 |
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Stable-Diffusion-Regularization-Images
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Clarification regularization for Stable Diffusion
However, when I look at regularization dataset that people have created, a lot of them are composed by bad quality AI generated pictures, for instance disfigured humans, or images full or artifacts. For instance, this image of train, or this one of a woman.
- Training Picture Source
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💡 How train with locally with 1.5 Runwayml Inpainting Model?
BTW, you can find the regularization images (ready to use class images) here.
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Regularization images
Have you compared results to using regularization images from an existing repo such as https://github.com/JoePenna/Stable-Diffusion-Regularization-Images
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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.
For subjects/people, paste this into the github downloader https://github.com/JoePenna/Stable-Diffusion-Regularization-Images/tree/main/person_ddim
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Good Dreambooth Formula
If you are using person, man or woman as class, you don't need to generate the images as there are a some github repos that have a bunch of them already generated for you to use. Nitrosocke also shared some, check my initial post for the link.
- Custom Model Comparison 1.4 vs 1.5 (something broke)
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What should I do when want better results for a person that was already trained in the sd v1.4 version? Train the model, Dreambooth, or textual inversion embeddings?
I did some experiments with dreambooth training. Overall better results were when I have used 1500 "person" class and about 50 training images. It is vital to have different background and different clothes otherwise it will "bake it" into your token (e.g. same sweater will influence all the rendering with color or pattern as it will be "part of your token"). Now I need to test textual inversion and see the difference.
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Any advice on how to use the dream booth colab with automatic?
As for what kind of images to use I've tried actual photos of people and images generated with Stable Diffusion and I've had pretty good results with both. I also tried using exclusively pictures of the person I'm training for everything and even that worked pretty well. All I can really say is that it seems to pay off if you keep an eye on the framing of your images - if the majority of your reference images cut off the upper 10% of the head for example then your model will tend to also produce images that cut off the upper 10% of the head. Oh, and I haven't tried it myself but this Github repository apparently has a ton of images specifically for use in DreamBooth.
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How are you achieving decent results in DreamBooth? My images look terrible!
I've made sure all my images are only me, and clean images. I have tried using the unsplash regularization images from https://github.com/JoePenna/Stable-Diffusion-Regularization-Images. I've tried generating my own images from SD itself. I've tried 1k, 2k, 3k, 4k steps. I've tried more images of myself and fewer. I've tried using "man", "person", "face" as the class. All of it results in absolute garbage. I get outputs that consistently look like I'm 80 years old or a different ethnicity. Or just wrong... so wrong.
diffusers
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Useful Links
ShivamShrirao's Diffusers Pretrained diffusion models across multiple modalities.
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DreamBooth fine-tuning failing to get the style
Like the title say I'm trying to fine-tune a model to match a style of a popular manhwa. I'm using the ShivamShrirao Google Colab to accomplish this.
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How to resume Dreambooth training?
I am running the DreamBooth_Stable_Diffusion.ipynb notebook from ShivamShrirao locally on my machine. Let's say I have trained for 500 iterations and it hasn't converged yet. How do I make it resume training from that iteration so it can do another 500?
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Non web-ui colab
My understanding, based on messages from an (alleged) representative of colabs, is that the webui is the problem, not SD itself. This also seems to be the consensus in the comments section of other posts. I have not yet seen a link to colab based webui alternatives so here is something I found from a tutorial. I am certain that there are better alternatives. Anyone have a better idea? This will still probably be useful to other people like me who are just messing around.
- [Stablediffusion] Guide pour DreamBooth avec 8 Go de vram sous Windows
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Finally got Dreambooth running without errors... but is it even using the model I trained?
I'm running ShivamShrirao's fork of diffusers; ran into a fp16 issue and had to patch in a fix from the main branch ( #1567 ).
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Shivam Stable Diffusion: Getting same example models repeatedly (SD + Dreambooth)
I am running Shivam Stable Diffusion Jupyter notebook: diffusers/DreamBooth_Stable_Diffusion.ipynb at main · ShivamShrirao/diffusers · GitHub.
- Running Stable Diffusion locally with personalized changes
- Can't create embedding's with dreambooth ckpt
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Weird issue using Shivam's Diffuser notebook
Are you using this one? https://github.com/S
What are some alternatives?
SD-Regularization-Images-Style-Dreambooth
stable-diffusion-webui - Stable Diffusion web UI
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.
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
Dreambooth-SD-optimized - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
A1111-Web-UI-Installer - Complete installer for Automatic1111's infamous Stable Diffusion WebUI
Dreambooth-Regularization - All the regs
xformers - Hackable and optimized Transformers building blocks, supporting a composable construction.
efficient-dreambooth - [Moved to: https://github.com/smy20011/dreambooth-docker]
Dreambooth-Stable-Diffusion - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion (tweaks focused on training faces)