cycle-diffusion
[ICCV 2023] A latent space for stochastic diffusion models (by ChenWu98)
prompt-to-prompt | cycle-diffusion | |
---|---|---|
18 | 8 | |
2,860 | 518 | |
2.1% | - | |
3.7 | 6.1 | |
3 months ago | 4 months ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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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.
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.
prompt-to-prompt
Posts with mentions or reviews of prompt-to-prompt.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-24.
- Has google prompt-to-prompt / Cross Attention Control ever been implemented as a plugin for ComfyUI or Automatic1111?
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[D] CFG role in diffusion vs autoregressive transformers
Found relevant code at https://github.com/google/prompt-to-prompt + all code implementations here
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Auto1111 Fork with pix2pix
Null text inversion produces almost a perfect textual inversion, and then allows you to edit it with a prompt, like instruct2pix. https://github.com/google/prompt-to-prompt
- Are there ways to use img2img without manually inpainting the clothes of a person I order to change the type of clothing or color of it, etc. I saw a few people here who were able to detect clothing automatically, any advice is welcome 🙏🏼
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Artists Tomorrow
First we had Google's prompt to prompt https://github.com/google/prompt-to-prompt
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Backgrounds HATE me?
Narratives can also work, like "walking down forest path". However, it'll be difficult to keep the character positioned the way you want with that. If you're a techie somewhat, you can try to use https://github.com/google/prompt-to-prompt to generate someone you like and then see if you can get a better background without changing the character.
- Anybody here looked into and wanna share the major deviations (if any) between Google's implementation of prompt2prompt vs Doggettx's implementation (which was included in Automatic1111's repo as "Prompt Editing" feature)?
- I did not expect it, but that's the reality now
- Prompt-to-Prompt: Latent Diffusion and Stable Diffusion Implementation
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[R] can diffusion model be used for domain adaptation?
Google has a nice paper on text-guided image2image translation by inferring the (random) init image and changing the prompt: https://github.com/google/prompt-to-prompt
cycle-diffusion
Posts with mentions or reviews of cycle-diffusion.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-13.
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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
What are some alternatives?
When comparing prompt-to-prompt and cycle-diffusion you can also consider the following projects:
jukebox - Code for the paper "Jukebox: A Generative Model for Music"
Anti-DreamBooth - Anti-DreamBooth: Protecting users from personalized text-to-image synthesis (ICCV'23)
StyleGAN-nada
stable-diffusion-webui - Stable Diffusion web UI
PITI - PITI: Pretraining is All You Need for Image-to-Image Translation
stylegan2-pytorch - Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
stable-dreambooth - Dreambooth implementation based on Stable Diffusion with minimal code.