| lucidrains/stylegan2-pytorch |
3,147 |
|
0 |
2 |
over 3 years ago |
146 |
July 19, 2022 |
120 |
mit |
Python |
| Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement |
| BloodAxe/pytorch-toolbelt |
1,458 |
|
1 |
6 |
about 2 years ago |
27 |
June 27, 2022 |
2 |
mit |
Python |
| PyTorch extensions for fast R&D prototyping and Kaggle farming |
| jasmcaus/caer |
691 |
|
0 |
2 |
almost 3 years ago |
119 |
October 13, 2021 |
2 |
mit |
Python |
| High-performance Vision library in Python. Scale your research, not boilerplate. |
| arcelien/pba |
400 |
|
0 |
0 |
over 6 years ago |
0 |
|
9 |
apache-2.0 |
Jupyter Notebook |
| Efficient Learning of Augmentation Policy Schedules |
| PhoenixDL/rising |
300 |
|
0 |
5 |
almost 3 years ago |
8 |
December 20, 2021 |
30 |
mit |
Jupyter Notebook |
| Provides everything needed for high performance data loading and augmentation in pytorch. |
| zudi-lin/pytorch_connectomics |
151 |
|
0 |
0 |
over 2 years ago |
0 |
|
12 |
mit |
Python |
| PyTorch Connectomics: segmentation toolbox for EM connectomics |
| qsyao/cuda_spatial_deform |
110 |
|
0 |
0 |
about 4 years ago |
0 |
|
5 |
other |
Cuda |
| A fast tool to do image augmentation on GPU(especially elastic_deform), can be helpful to research on Medical Image. |
| openai/distribution_augmentation |
103 |
|
0 |
0 |
almost 3 years ago |
0 |
|
3 |
mit |
Python |
| Code for the paper, "Distribution Augmentation for Generative Modeling", ICML 2020. |
| ricvolpi/generalize-unseen-domains |
81 |
|
0 |
0 |
almost 6 years ago |
0 |
|
1 |
mit |
Python |
| Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018 |
| ZFTurbo/Keras-augmentation-layer |
48 |
|
0 |
0 |
over 4 years ago |
7 |
October 06, 2021 |
0 |
|
Python |
| Keras implementation of layer which performs augmentations of images using GPU. |
