| opencv/cvat |
10,831 |
|
0 |
3 |
about 2 years ago |
23 |
November 27, 2023 |
504 |
mit |
TypeScript |
| Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. |
| qubvel/segmentation_models.pytorch |
8,226 |
|
2 |
49 |
over 2 years ago |
13 |
September 19, 2019 |
27 |
mit |
Python |
| Segmentation models with pretrained backbones. PyTorch. |
| Cadene/pretrained-models.pytorch |
8,094 |
|
52 |
42 |
over 4 years ago |
16 |
October 29, 2018 |
91 |
bsd-3-clause |
Python |
| Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc. |
| lukemelas/EfficientNet-PyTorch |
6,577 |
|
7 |
36 |
over 4 years ago |
13 |
April 15, 2021 |
133 |
apache-2.0 |
Python |
| A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!) |
| facebookresearch/moco |
4,401 |
|
0 |
0 |
over 2 years ago |
0 |
|
55 |
mit |
Python |
| PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722 |
| huawei-noah/Efficient-AI-Backbones |
4,393 |
|
0 |
0 |
about 1 year ago |
0 |
|
71 |
|
Python |
| Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab. |
| Deci-AI/super-gradients |
4,125 |
|
0 |
5 |
about 2 years ago |
38 |
November 23, 2023 |
94 |
apache-2.0 |
Jupyter Notebook |
| Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS. |
| facebookresearch/deit |
3,603 |
|
0 |
0 |
over 2 years ago |
0 |
|
17 |
apache-2.0 |
Python |
| Official DeiT repository |
| tinyvision/DAMO-YOLO |
3,598 |
|
0 |
0 |
over 2 years ago |
0 |
|
18 |
apache-2.0 |
Python |
| DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement. |
| POSTECH-CVLab/PyTorch-StudioGAN |
3,226 |
|
0 |
0 |
over 2 years ago |
0 |
|
32 |
other |
Python |
| StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation. |
