StyleCLIPDraw
deep-learning-v2-pytorch
StyleCLIPDraw | deep-learning-v2-pytorch | |
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4 | 1 | |
274 | 5,188 | |
- | 0.7% | |
0.0 | 0.0 | |
over 1 year ago | 11 months ago | |
Jupyter Notebook | Jupyter Notebook | |
GNU General Public License v3.0 only | MIT License |
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StyleCLIPDraw
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2 CLIP-guided systems that are similar to CLIPDraw: StyleCLIPDraw from pschaldenbrand, and DIFFVG_Play from johnowhitaker
StyleCLIPDraw.
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[R] StyleCLIPDraw: Coupling Content and Style in Text-to-Drawing Synthesis
Code for https://arxiv.org/abs/2111.03133 found: https://github.com/pschaldenbrand/StyleCLIPDraw
deep-learning-v2-pytorch
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how can i activate the cells in this github
in this link deep-learning-v2-pytorch/StudentAdmissions.ipynb at master · udacity/deep-learning-v2-pytorch · GitHub
What are some alternatives?
animegan2-pytorch - PyTorch implementation of AnimeGANv2
cs231n - Note and Assignments for CS231n: Convolutional Neural Networks for Visual Recognition
DualStyleGAN - [CVPR 2022] Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer
stable-diffusion-reference-only - img2img version of stable diffusion. Anime Character Remix. Line Art Automatic Coloring. Style Transfer.
torchdyn - A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
monodepth2 - [ICCV 2019] Monocular depth estimation from a single image
hyperlearn - 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
glasses - High-quality Neural Networks for Computer Vision 😎
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
fast-artistic-videos - Video style transfer using feed-forward networks.