deep-daze
feed_forward_vqgan_clip
Our great sponsors
deep-daze | feed_forward_vqgan_clip | |
---|---|---|
49 | 4 | |
4,379 | 136 | |
- | - | |
0.0 | 3.7 | |
about 2 years ago | 4 months ago | |
Python | Python | |
MIT License | MIT License |
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.
deep-daze
- Besides Gaming - for what can be a 4080 useful?
-
Master hacker used “AI via command prompt” to ask what “after death looks like”
it's not nessecary to specify the model with the tool he is using also known as deep daze
-
AI image transformation. New drop, Proto-Cubism art watch the magic below.
If you want do the same thing for free yourself: https://github.com/lucidrains/deep-daze
- GitHub - lucidrains/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
-
List of sites/programs/projects that use OpenAI's CLIP neural network for steering image/video creation to match a text description
(Added Mar. 15, 2021) deep-daze Fourier Feature Map - Colaboratory by afiaka87. Uses SIREN to generate images. Reference. Reddit post.
-
test
(Added Feb. 5, 2021) Deep Daze - Colaboratory by lucidrains. Uses SIREN to generate images. The GitHub repo has a local machine version. GitHub. Notebook copy by levindabhi.
- AI generated visualization of Meat Grinder lyrics
-
Let's play Guess That Chandrian! (Round one) All images are generated by AI using the Chandrian's "Deep Names and Signs" as the prompt. Who does your sleeping mind see? Let me know in the comments!
Thanks! I'll be posting more over the week. I run these on Python. Here's the link for the program https://github.com/lucidrains/deep-daze
-
Told an AI to generate Linux. Looks about right
In case you have some damn good gamer-level GPU, you can try this FOSS alternative locally instead: https://github.com/lucidrains/deep-daze
-
AI-generated image using "Israel" as a keyword
I'm not sure exactly what they used, but deep-daze can be used to generate similar things that turn out quite cool
feed_forward_vqgan_clip
-
[D] Hosting AI Art Generative ML Model
WOMBO I suspect uses the feed forward inferential approach to VQGAN + CLIP (instead of finetuning, predict the final z latent vector for a given text input) which is why their outputs are less sophisticated: as a result there are many deployment optimizations you can do to speed that up, which may be complicated.
-
A small experiment on how changes in a text prompt may affect output image in a CLIP-based system
The system used to produce these images is unlike most other VQGAN+CLIP systems because it uses a neural network trained by the developer(s) instead of an iterative process. This system is known to have a "formula" for image layout.
-
Get a VQGAN output image for a given text description almost instantly (not including time for one-time setup) using Colab notebook "Feed Forward VQGAN CLIP - Using a pretrained model" from mehdidc. Here are 20 non-cherry picked images from the notebook. Details in a comment.
Hello, some news. For those who are interested, I released new models (release 0.2) that you could try and you might find them better (depending on the prompt) than the current one(s), also the problem that was mentioned by /u/Wiskkey is less visible (object parts appearing systematically on top-left), but still not 100% solved, there is still a common global structure that can be identified, but it's more centered on the image. The Colab notebook was updated to use the new models.
What are some alternatives?
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
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
Story2Hallucination
Text-to-Image-Synthesis - Pytorch implementation of Generative Adversarial Text-to-Image Synthesis paper
DALLE-pytorch - Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
CLIP-Guided-Diffusion - Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab.
starcli - :sparkles: Browse trending GitHub projects from your command line
VQGAN-CLIP-Video - Traditional deepdream with VQGAN+CLIP and optical flow. Ready to use in Google Colab.