Colab-BigGANxCLIP VS clip-glass

Compare Colab-BigGANxCLIP vs clip-glass and see what are their differences.

clip-glass

Repository for "Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search" (by galatolofederico)
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Colab-BigGANxCLIP clip-glass
1 13
2 177
- -
10.0 0.0
over 3 years ago over 2 years ago
Jupyter Notebook Python
- GNU General Public License v3.0 only
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Colab-BigGANxCLIP

Posts with mentions or reviews of Colab-BigGANxCLIP. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-03.
  • test
    21 projects | /r/u_Wiskkey | 3 Apr 2022
    (Added Feb. 24, 2021) Colab-BigGANxCLIP.ipynb - Colaboratory by styler00dollar. Uses BigGAN to generate images. "Just a more compressed/smaller version of that [advadnoun's] notebook". GitHub.

clip-glass

Posts with mentions or reviews of clip-glass. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-03.

What are some alternatives?

When comparing Colab-BigGANxCLIP and clip-glass you can also consider the following projects:

StyleCLIP - Using CLIP and StyleGAN to generate faces from prompts.

a-PyTorch-Tutorial-to-Image-Captioning - Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning

aphantasia - CLIP + FFT/DWT/RGB = text to image/video

meshed-memory-transformer - Meshed-Memory Transformer for Image Captioning. CVPR 2020

stylegan2-clip-approach - Navigating StyleGAN2 w latent space using CLIP

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

Story2Hallucination

Colab-deep-daze - Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)

stylized-neural-painting - Official Pytorch implementation of the preprint paper "Stylized Neural Painting", in CVPR 2021.

VectorAscent - Generate vector graphics from a textual caption