cycle-diffusion
Anti-DreamBooth
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| cycle-diffusion | Anti-DreamBooth | |
|---|---|---|
| 8 | 1 | |
| 516 | 180 | |
| - | 5.6% | |
| 6.1 | 6.8 | |
| 4 months ago | 6 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 only |
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cycle-diffusion
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[D] CycleGAN Diffusion equivalent
CycleDiffusion
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[R] Unifying Diffusion Models' Latent Space, with Applications to CycleDiffusion and Guidance + Diffusers and Gradio Demo
github: https://github.com/chenwu98/cycle-diffusion
- Artists say AI image generators are copying their style to make thousands of new images — and it's completely out of their control
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How long until language model prompting?
Oh... Right after I wrote that reply, I found this. https://github.com/ChenWu98/cycle-diffusion Probably even closer to what you wanted. :)
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Google has opensourced Prompt-to-Prompt
CycleDiffusion which apparently somehow infers the random seed for any arbitrary image
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CycleDiffusion: Text-to-Image Diffusion Models Are Image-to-Image Editors via Inferring "Random Seed"
can't say I've seen a project with 468 dependencies before
Anti-DreamBooth
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Anti-DreamBooth: Protecting users from personalized text-to-image synthesis
The authors claim it was strong enough to withstand Ilyasviel's anti-Glaze code https://github.com/VinAIResearch/Anti-DreamBooth/issues/1
What are some alternatives?
jukebox - Code for the paper "Jukebox: A Generative Model for Music"
kohya-sd-scripts-webui - Gradio wrapper for sd-scripts by kohya
prompt-to-prompt
Dreambooth - Fine-tuning of diffusion models
PITI - PITI: Pretraining is All You Need for Image-to-Image Translation
sd-easy-mode - Easy Mode Stable Diffusion process allows you to generate images based on your own photos in just three steps
stable-dreambooth - Dreambooth implementation based on Stable Diffusion with minimal code.
dreambooth-training-action - Train your custom Stable Diffusion model using Tiyaro Dreambooth training API and Github Action
RelayDiffusion - The official implementation of "Relay Diffusion: Unifying diffusion process across resolutions for image synthesis" [ICLR 2024 Spotlight]
Lora-for-Diffusers - The most easy-to-understand tutorial for using LoRA (Low-Rank Adaptation) within diffusers framework for AI Generation Researchers🔥
concept-ablation - Ablating Concepts in Text-to-Image Diffusion Models (ICCV 2023)
e4t-diffusion - Implementation of Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models