Auto Dynamic Deeplab
[IROS 2021] ADD: A Fine-grained Dynamic Inference Architecture for Semantic Image Segmentation
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Segmentation_models.pytorch | 8,226 |  | 2 | 49 | 5 months ago | 13 | September 19, 2019 | 27 | mit | Python |
| Segmentation models with pretrained backbones. PyTorch. | ||||||||||
| Pretrained Models.pytorch | 8,094 |  | 52 | 42 | 3 years ago | 16 | October 29, 2018 | 91 | bsd-3-clause | Python |
| Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc. | ||||||||||
| Pytorch Cifar | 5,131 | a year ago | 103 | mit | Python | |||||
| 95.47% on CIFAR10 with PyTorch | ||||||||||
| Pytorch Opcounter | 4,368 |  | 3 | 71 | 7 months ago | 49 | September 07, 2022 | 71 | mit | Python |
| Count the MACs / FLOPs of your PyTorch model. | ||||||||||
| Torch2trt | 4,267 | 4 months ago | 320 | mit | Python | |||||
| An easy to use PyTorch to TensorRT converter | ||||||||||
| Pytorch Cifar100 | 3,687 | 5 months ago | 53 | Python | ||||||
| Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet) | ||||||||||
| Flops Counter.pytorch | 2,606 |  | 5 | 19 | 3 months ago | 20 | October 27, 2023 | 30 | mit | Python |
| Flops counter for convolutional networks in pytorch framework | ||||||||||
| Efficient_densenet_pytorch | 1,462 | a year ago | 12 | mit | Python | |||||
| A memory-efficient implementation of DenseNets | ||||||||||
| Pytorch Classification | 1,244 | 3 years ago | 30 | mit | Python | |||||
| Classification with PyTorch. | ||||||||||
| Pytorch_classification | 1,055 | a year ago | 39 | mit | Jupyter Notebook | |||||
| 利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码 | ||||||||||
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