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@ -11,7 +11,7 @@ All the models are implemented in pytorch/mxnet/tensorflown first, and export a
## News
- `23 May 2022`. [yhpark](https://github.com/yester31): Real-ESRGAN, Practical Algorithms for General Image/Video Restoration.
- `15 Mar 2022`. [sky_hole](https://github.com/wdhao): Swin Transform - Semantic Segmentation.
- `15 Mar 2022`. [sky_hole](https://github.com/wdhao): Swin Transformer - Semantic Segmentation.
- `19 Oct 2021`. [liuqi123123](https://github.com/liuqi123123) added cuda preprossing for yolov5, preprocessing + inference is 3x faster when batchsize=8.
- `18 Oct 2021`. [xupengao](https://github.com/xupengao): YOLOv5 updated to v6.0, supporting n/s/m/l/x/n6/s6/m6/l6/x6.
- `31 Aug 2021`. [FamousDirector](https://github.com/FamousDirector): update retinaface to support TensorRT 8.0.
@ -91,7 +91,7 @@ Following models are implemented.
|[centernet](./centernet)| CenterNet DLA-34, pytorch from [xingyizhou/CenterNet](https://github.com/xingyizhou/CenterNet) |
|[efficientnet](./efficientnet)| EfficientNet b0-b8 and l2, pytorch from [lukemelas/EfficientNet-PyTorch](https://github.com/lukemelas/EfficientNet-PyTorch) |
|[detr](./detr)| DE⫶TR, pytorch from [facebookresearch/detr](https://github.com/facebookresearch/detr) |
|[swin-transformer](./swin-transformer)| Swin Transform - Semantic Segmentation, only support Swin-T. The Pytorch implementation is [microsoft/Swin-Transformer](https://github.com/microsoft/Swin-Transformer.git) |
|[swin-transformer](./swin-transformer)| Swin Transformer - Semantic Segmentation, only support Swin-T. The Pytorch implementation is [microsoft/Swin-Transformer](https://github.com/microsoft/Swin-Transformer.git) |
|[real-esrgan](./real-esrgan)| Real-ESRGAN. The Pytorch implementation is [real-esrgan](https://github.com/xinntao/Real-ESRGAN) |
## Model Zoo