VQGAN-CLIP
CLIP-Guided-Diffusion
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| VQGAN-CLIP | CLIP-Guided-Diffusion | |
|---|---|---|
| 67 | 4 | |
| 2,563 | 377 | |
| - | - | |
| 0.0 | 0.0 | |
| over 1 year ago | over 1 year ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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VQGAN-CLIP
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📚 Tutorials & 🎨 AI Art Generation Tool List Mega Thread
VQGAN-CLIP
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Which is your favorite text to image model overall?
I've screwed with many text-to-image models over the past couple of years, and I found that while I currently enjoy Stable Diffusion's coherency, I have a soft spot for the ImageNet model used by default for VQGAN+CLIP. It easily approaches the uncanny valley when generating people or animals, but makes for great abstract backgrounds and wallpapers. I already have nostalgia for generating images with it on my CPU overnight.
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Stable Diffusion Announcement
For someone only tangentially familiar with this space, how is this different than e.g. https://github.com/nerdyrodent/VQGAN-CLIP which you can also run at home? Is it the quality of the generated images?
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Medieval Noir - VQGAN-CLIP - COCO Checkpoint
Used https://github.com/nerdyrodent/VQGAN-CLIP
- Once have access, do you run it on your computer or over the internet on Open-AI's computers?
- How to get AI imaging effect in Premiere pro
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A Guide to Asking Robots to Design Stained Glass Windows
I don't have any of the DALL-Es but I do have a couple from github [1], [2] which gave these outputs[3]
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How not to waste $1600?
If you want to try your hand at buggering your whole system - try playing with AI image generation as it uses all possible computer assets :D . There is a lot of forms and installations for those but I VQGANs from github the easiest. Problem is that some require familarity with shell, python and in some cases - you need to enable the Linux subsystem in Windows (is it called a subsystem? it is not exactly a VM). This one is the easiest to install out of all I tried. But I liked the results of Pixray most but I wrecked it. I use this one nowadays.
- Ask HN: Is there a publicly available (not private beta) text-to-image API?
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Got a Machine Learning Algorithm to depict Aphex
For those that are interested, I used VQGAN-CLIP, specifically this GitHub repository
CLIP-Guided-Diffusion
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Which is your favorite text to image model overall?
Runner-ups are Craiyon (for being more "creative" than SD), Disco Diffusion, minDALL-E, and CLIP Guided Diffusion.
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Once have access, do you run it on your computer or over the internet on Open-AI's computers?
-clip guided diffusion https://github.com/nerdyrodent/CLIP-Guided-Diffusion
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how would i go about running disco diffusion locally?
Nerdy Rodent has a Github repo for this; it should work fine from the Anaconda command line: https://github.com/nerdyrodent/CLIP-Guided-Diffusion
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PLAYING AGAIN (CLIP GUIDED DIFFUSION) (VQGAN + CLIP) (Beksinski)
As far as I understand, VQGAN is not a guided diffusion model. I've been using a slightly tweaked version of https://github.com/nerdyrodent/CLIP-Guided-Diffusion for diffusion. Once you get it set up the interface is pretty much what you might expect:
What are some alternatives?
DALLE-mtf - Open-AI's DALL-E for large scale training in mesh-tensorflow.
image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
disco-diffusion
deep-daze - Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). Technique was originally created by https://twitter.com/advadnoun
big-sleep - A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Technique was originally created by https://twitter.com/advadnoun
waifu2x - Image Super-Resolution for Anime-Style Art
vqgan-clip-app - Local image generation using VQGAN-CLIP or CLIP guided diffusion
stable-diffusion - A latent text-to-image diffusion model
feed_forward_vqgan_clip - Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt
stylegan2-pytorch - Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
mindall-e - PyTorch implementation of a 1.3B text-to-image generation model trained on 14 million image-text pairs