dreambooth-training-guide
stablediffusion
dreambooth-training-guide | stablediffusion | |
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30 | 108 | |
595 | 36,444 | |
- | 2.1% | |
10.0 | 0.0 | |
over 1 year ago | about 1 month ago | |
Python | ||
- | MIT License |
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dreambooth-training-guide
- [Sdforall] L'extension Dreambooth pour Automatic111 est sortie
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Creating own model like the ones on civitai.com
I dont have the time right now, but the rule of thumb for me was 80 unet learning steps for 1 image. Atleast 40 regularization images. Read more about regularization images here: https://github.com/nitrosocke/dreambooth-training-guide
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Image background for LORA training images
This tutorial for dreambooth training has advice with regard to backgrounds which is probably also applicable to LORA. It recommends including images with solid, non-transparent backgrounds but not using them exclusively. Images that focus on the torso and face are probably most important unless your subject has very distinctive legs and feet. Removing other subjects is a must if you're training for a specific subject.
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Non-technical tips for ideal training of Stable Diffusion through Dreambooth?
I found this, I'm going to go through this guide. Seems like I am using far too many images. https://github.com/nitrosocke/dreambooth-training-guide
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Questions about Regularization Images to be used in Dreambooth
Nitrosocke's guide already tells how much and what kind of images to use.
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What’s going to be a problem 20 years from now that people are choosing to ignore?
Dreambooth lets you do it in less than 100 images. https://github.com/nitrosocke/dreambooth-training-guide These folks say it's 5-15 to train on a person but I've not tested myself. https://www.reddit.com/r/StableDiffusion/comments/10tqy88/were\_launching\_a\_lightningfast\_dreambooth\_service/
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We’re launching a lightning-fast Dreambooth service: finetune 1’500 steps in 5min!
See eg this tutorial for styles: https://github.com/nitrosocke/dreambooth-training-guide
- Would it be possible to pretrain generation to mimic my art style?
- Dreambooth model training : dataset labelling
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Introducing Macro Diffusion - A model fine-tuned on over 700 macro images (Link in the comments)
The first time I tried to Dreambooth a style it went poorly. Then I found Nitrosocke's Dreambooth Training Guide and realized my problems were caused by a poorly redacted dataset.
stablediffusion
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Generating AI Images from your own PC
With this tutorial's help, you can generate images with AI on your own computer with Stable Diffusion.
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Midjourney
If your PC has a GPU(Nvidia RTX 30series+ recommended) of VRAM more than 4GB then try training your own Stable Diffusion model.
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RuntimeError: Couldn't clone Stable Diffusion.
Command: "git" clone "https://github.com/Stability-AI/stablediffusion.git" "C:\Users\Naveed\Documents\A1111 Web UI Autoinstaller\stable-diffusion-webui\repositories\stable-diffusion-stability-ai"
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What is the currently most efficient distribution of Stable Diffusion?
Automatic11112 and sygil-webui aren't "distributions" of Stable Diffusion. This is a repository with some distributions of Stable Diffusion.
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Reimagine XL: this is just Controlnet with a credit system right?
New stable diffusion finetune (Stable unCLIP 2.1, Hugging Face) at 768x768 resolution, based on SD2.1-768. This model allows for image variations and mixing operations as described in Hierarchical Text-Conditional Image Generation with CLIP Latents, and, thanks to its modularity, can be combined with other models such as KARLO. Comes in two variants: Stable unCLIP-L and Stable unCLIP-H, which are conditioned on CLIP ViT-L and ViT-H image embeddings, respectively. Instructions are available here.
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Stability AI has released Reimagine XL to make copies of images in one click
This model will soon be open-sourced in StabilityAI’s GitHub.
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What am I doing wrong please?
Another question, if that's ok? Stable Diffusion 2.0 - https://github.com/Stability-AI/stablediffusion - if I wanted to use that, do I follow along their instructions and it will work on the M1 still, or you advise against it?
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Tools For AI Animation and Filmmaking , Community Rules, ect. (**FAQ**)
Stable Diffusion (2D Image Generation and Animation) https://github.com/CompVis/stable-diffusion (Stable Diffusion V1) https://huggingface.co/CompVis/stable-diffusion (Stable Diffusion Checkpoints 1.1-1.4) https://huggingface.co/runwayml/stable-diffusion-v1-5 (Stable Diffusion Checkpoint 1.5) https://github.com/Stability-AI/stablediffusion (Stable Difusion V2) https://huggingface.co/stabilityai/stable-diffusion-2-1/tree/main (Stable Diffusion Checkpoint 2.1) Stable Diffusion Automatic 1111 Webui and Extensions https://github.com/AUTOMATIC1111/stable-diffusion-webui (WebUI - Easier to use) PLEASE NOTE, MANY EXTENSIONS CAN BE INSTALLED FROM THE WEBUI BY CLICK "AVAILABLE" OR "INSTALL FROM URL" BUT YOU MAY STILL NEED TO DOWNLOAD THE MODEL CHECKPOINTS! https://github.com/Mikubill/sd-webui-controlnet (Control Net Extension - Use various models to control your image generation, useful for animation and temporal consistency) https://huggingface.co/lllyasviel/ControlNet/tree/main/models (Control Net Checkpoints -Canny, Normal, OpenPose, Depth, ect.) https://github.com/thygate/stable-diffusion-webui-depthmap-script (Depth Map Extension - Generate high-resolution depthmaps and animated videos or export to 3d modeling programs) https://github.com/graemeniedermayer/stable-diffusion-webui-normalmap-script (Normal Map Extension - Generate high-resolution normal maps for use in 3d programs) https://github.com/d8ahazard/sd_dreambooth_extension (Dream Booth Extension - Train your own objects, people, or styles into Stable Diffusion) https://github.com/deforum-art/sd-webui-deforum (Deforum - Generate Weird 2D animations) https://github.com/deforum-art/sd-webui-text2video (Deforum Text2Video - Generate videos from texts prompts using ModelScope or VideoCrafter)
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Is AI technology really the issue?
Stable Diffusion's code : https://github.com/Stability-AI/stablediffusion
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I've never seen a YAML file alongside a .ckpt or .safetensors
But if you want to run a 2.x-based model, you'll need to download the corresponding YAML file (either the standard one – v2-inference-v.yaml – from Github or the one that is distributed with the model, if it requires a special one), rename it to have the same name as the model, and place it in the models folder alongside the model.
What are some alternatives?
sd_dreambooth_extension
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
StableTuner - Finetuning SD in style.
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.
stable-diffusion-webui - Stable Diffusion web UI
MiDaS - Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2022"
dreambooth-gui
civitai - A repository of models, textual inversions, and more
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
xformers - Hackable and optimized Transformers building blocks, supporting a composable construction.
DiffusionToolkit - Metadata-indexer and Viewer for AI-generated images
Dreambooth-Stable-Diffusion - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion