CLIP-Style-Transfer VS aphantasia

Compare CLIP-Style-Transfer vs aphantasia and see what are their differences.

CLIP-Style-Transfer

Doing style transfer with linguistic features using OpenAI's CLIP. (by Zasder3)

aphantasia

CLIP + FFT/DWT/RGB = text to image/video (by eps696)
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CLIP-Style-Transfer aphantasia
2 21
13 769
- -
0.0 3.9
almost 3 years ago 7 months ago
Jupyter Notebook Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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CLIP-Style-Transfer

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

aphantasia

Posts with mentions or reviews of aphantasia. 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 CLIP-Style-Transfer and aphantasia you can also consider the following projects:

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

stylegan - StyleGAN - Official TensorFlow Implementation

StyleCLIP - Official Implementation for "StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery" (ICCV 2021 Oral)

DeOldify - A Deep Learning based project for colorizing and restoring old images (and video!)

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

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

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.

Colab-BigGANxCLIP

clipping-CLIP-to-GAN

Queryable - Run OpenAI's CLIP model on iOS to search photos.

clip-glass - Repository for "Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search"