stylegan2-clip-approach
TediGAN
stylegan2-clip-approach | TediGAN | |
---|---|---|
1 | 1 | |
55 | 361 | |
- | 0.0% | |
1.8 | 0.0 | |
over 2 years ago | about 1 year ago | |
Python | Python | |
- | MIT License |
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stylegan2-clip-approach
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test
(Added Mar. 7, 2021) StyleGAN2-CLIP-approach.ipynb - Colaboratory by l4rz. Uses StyleGAN to generate images. GitHub. Twitter reference.
TediGAN
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test
(Added Feb. 23, 2021) TediGAN - Colaboratory by weihaox. Uses StyleGAN to generate images. GitHub. I got error "No pre-trained weights found for perceptual model!" when I used the Colab notebook, which was fixed when I made the change mentioned here. After this change, I still got an error in the cell that displays the images, but the results were in the remote file system. Use the "Files" icon on the left to browse the remote file system.
What are some alternatives?
DALLECLIP
StyleCLIP - Using CLIP and StyleGAN to generate faces from prompts.
Colab-BigGANxCLIP
Colab-deep-daze - Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
aphantasia - CLIP + FFT/DWT/RGB = text to image/video
VectorAscent - Generate vector graphics from a textual caption
AuViMi - AuViMi stands for audio-visual mirror. The idea is to have CLIP generate its interpretation of what your webcam sees, combined with the words thare are spoken.
Story2Hallucination
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
clipping-CLIP-to-GAN