CLIP-Style-Transfer
Doing style transfer with linguistic features using OpenAI's CLIP. (by Zasder3)
random-colabs
By EvgenyKashin
| CLIP-Style-Transfer | random-colabs | |
|---|---|---|
| 2 | 1 | |
| 13 | 14 | |
| - | - | |
| 0.0 | 10.0 | |
| almost 3 years ago | about 3 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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.
-
test
(Added Mar. 8, 2021) CLIP Style Transfer Test.ipynb - Colaboratory by Zasder3. Uses VGG19's conv4_1 to generate images. GitHub. Twitter reference.
-
[Project] Learning Artistic Style From Language Features using CLIP
Code: https://github.com/Zasder3/CLIP-Style-Transfer
random-colabs
Posts with mentions or reviews of random-colabs.
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
(Added Mar. 23, 2021) ClipMeshOptimize.ipynb - Colaboratory by EvgenyKashin. Uses PyTorch3D to generate images. GitHub.
What are some alternatives?
When comparing CLIP-Style-Transfer and random-colabs 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)
VectorAscent - Generate vector graphics from a textual caption
StyleCLIP - Official Implementation for "StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery" (ICCV 2021 Oral)
StyleCLIP - Using CLIP and StyleGAN to generate faces from prompts.
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.
aphantasia - CLIP + FFT/DWT/RGB = text to image/video
clipping-CLIP-to-GAN
stylegan2-clip-approach - Navigating StyleGAN2 w latent space using CLIP
CLIP-Style-Transfer vs Colab-deep-daze
random-colabs vs VectorAscent
CLIP-Style-Transfer vs StyleCLIP
random-colabs vs Colab-deep-daze
CLIP-Style-Transfer vs StyleCLIP
random-colabs vs StyleCLIP
CLIP-Style-Transfer vs AuViMi
random-colabs vs aphantasia
CLIP-Style-Transfer vs clipping-CLIP-to-GAN
random-colabs vs stylegan2-clip-approach
CLIP-Style-Transfer vs aphantasia
random-colabs vs AuViMi