deep-daze
clip-glass
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deep-daze | clip-glass | |
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49 | 13 | |
4,379 | 177 | |
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0.0 | 0.0 | |
about 2 years ago | over 2 years ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 only |
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deep-daze
- Besides Gaming - for what can be a 4080 useful?
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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
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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.
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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.
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AI generated visualization of Meat Grinder lyrics
Some people are wondering what I used to make it. I used the create_story feature of https://github.com/lucidrains/deep-daze. I then set the framerate such that it lined up with the length of the song and that was it :)
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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
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An image created by an AI with keywords "Abandoned prison covered in fog"
If you're technologically savvy someone created a similar thing in Python, that runs locally on your computer. https://github.com/lucidrains/deep-daze
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9 Command-Line Tools to Go to Infinity & Beyond
2. Deep Daze
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I put the words “playboi carti” into Deep Daze artificial intelligence (creates art from words) and this is the result after 70 renders
If you have a pc head over to https://github.com/lucidrains/deep-daze and they tell you how to
clip-glass
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test
(Added Feb. 5, 2021) CLIP-GLaSS.ipynb - Colaboratory by Galatolo. Uses BigGAN (default) or StyleGAN to generate images. The GPT2 config is for image-to-text, not text-to-image. GitHub.
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Image to text models
After a cursory search I found CLIP-GLaSS and CLIP-cap. I've used CLIP-GLaSS in a previous experiment, but found the captions for digital/CG images quite underwhelming. This is understandable since this is not what the model was trained on, but still I'd like to use a better model.
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[R] end-to-end image captioning
CLIP-GLaSS
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
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
starcli - :sparkles: Browse trending GitHub projects from your command line
a-PyTorch-Tutorial-to-Image-Captioning - Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
meshed-memory-transformer - Meshed-Memory Transformer for Image Captioning. CVPR 2020
nettu-scheduler - A self-hosted calendar and scheduler server.
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
theme.sh - A script which lets you set your $terminal theme.
pyp - Easily run Python at the shell! Magical, but never mysterious.