TediGAN
stylegan2-clip-approach
TediGAN | stylegan2-clip-approach | |
---|---|---|
1 | 1 | |
361 | 55 | |
0.0% | - | |
0.0 | 1.8 | |
about 1 year ago | over 2 years ago | |
Python | Python | |
MIT License | - |
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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.
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.
What are some alternatives?
StyleCLIP - Using CLIP and StyleGAN to generate faces from prompts.
DALLECLIP
Colab-deep-daze - Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
Colab-BigGANxCLIP
VectorAscent - Generate vector graphics from a textual caption
aphantasia - CLIP + FFT/DWT/RGB = text to image/video
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
clipping-CLIP-to-GAN
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