Txt2Vectorgraphics
Txt2Vectorgraphics | SD-Regularization-Images-Style-Dreambooth | |
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30 | 7 | |
361 | 29 | |
- | - | |
3.7 | 10.0 | |
about 1 year ago | over 1 year ago | |
Python | ||
GNU General Public License v3.0 only | - |
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Txt2Vectorgraphics
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If you'd told me a few years ago that one day I would use a 3d printer to create artwork generated by an AI for a robot vacuum. The future is now.
I use the earlier version of this https://github.com/GeorgLegato/Txt2Vectorgraphics and it's great for output destined for cricut, laser, or 2-color z-hop graphics on 3D printer.
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How to mimic the flash effect in SD
Indeed. Same guy who created this cool extension: https://github.com/GeorgLegato/Txt2Vectorgraphics
- SD-webui: Beta for Vectorstudio-extension, please test; check video
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Preview: Vectorstudio extension for SD-Webui, Part I
https://github.com/GeorgLegato/Txt2Vectorgraphics the repo will be renamed to vectorstudio containing the features of this video (svg editor, sendto controlnet:img2img )
- Best model for black line illustrated art
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Question: is it possible to create such illustrations with stable diffusion?
In addition I used my Txt2Vectorgraphics script to produce svg graphics as side effect and to ensure b/w only GeorgLegato/Txt2Vectorgraphics: Custom Script for Automatics1111 StableDiffusion-WebUI. (github.com)
- Logos
- Update: Txt2Vectorgraphics 0.3 - ControlNet + SVG preview
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Update: Txt2Vectorgraphics 0.3
Release 0.3: SVG in gallery, controlnet support ยท GeorgLegato/Txt2Vectorgraphics (github.com)
- Any good models or ideas for single line art/scribbles?
SD-Regularization-Images-Style-Dreambooth
- 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?
deforum-for-automatic1111-webui - Deforum extension script for AUTOMATIC1111's Stable Diffusion webui [Moved to: https://github.com/deforum-art/sd-webui-deforum]
Stable-Diffusion-Regularization-Images - For use with fine-tuning, especially the current implementation of "Dreambooth".
vtracer - Raster to Vector Graphics Converter
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.
stablediffusion - High-Resolution Image Synthesis with Latent Diffusion Models
Dreambooth-Regularization - All the regs
SHARK - SHARK - High Performance Machine Learning Distribution
Dreambooth-SD-optimized - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
sd-multi - Run multiple forks of Stable Diffusion
Dreambooth-Stable-Diffusion - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion (tweaks focused on training faces)
stable-diffusion-webui-vectorstudio
DreamArtist-sd-webui-extension - DreamArtist for Stable-Diffusion-webui extension