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wang-xinyu 2021-03-05 15:10:42 +08:00
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README.md
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@ -10,6 +10,7 @@ All the models are implemented in pytorch/mxnet/tensorflown first, and export a
## News
- `5 Mar 2021`. [chgit0214](https://github.com/chgit0214) added the LPRNet.
- `31 Jan 2021`. RepVGG added by [upczww](https://github.com/upczww).
- `29 Jan 2021`. U-Net added by [YuzhouPeng](https://github.com/YuzhouPeng).
- `24 Jan 2021`. IBN-Net added by [TCHeish](https://github.com/TCHeish), PSENet optimized, YOLOv5 v4.0 INT8, etc.
@ -24,7 +25,6 @@ All the models are implemented in pytorch/mxnet/tensorflown first, and export a
- `16 Sep 2020`. [hwh-hit](https://github.com/hwh-hit) added ufld(Ultra-Fast-Lane-Detection, ECCV2020).
- `13 Sep 2020`. Add crnn, and got 1000fps on GTX1080.
- `28 Aug 2020`. [BaofengZan](https://github.com/BaofengZan) added a tutorial for compiling and running tensorrtx on windows.
- `16 Aug 2020`. [upczww](https://github.com/upczww) added a python wrapper for yolov5.
## Tutorials
@ -81,6 +81,7 @@ Following models are implemented.
|[ibnnet](./ibnnet)| IBN-Net, pytorch implementation from [XingangPan/IBN-Net](https://github.com/XingangPan/IBN-Net), ECCV2018 |
|[unet](./unet)| U-Net, pytorch implementation from [milesial/Pytorch-UNet](https://github.com/milesial/Pytorch-UNet) |
|[repvgg](./repvgg)| RepVGG, pytorch implementation from [DingXiaoH/RepVGG](https://github.com/DingXiaoH/RepVGG) |
|[lprnet](./lprnet)| LPRNet, pytorch implementation from [xuexingyu24/License_Plate_Detection_Pytorch](https://github.com/xuexingyu24/License_Plate_Detection_Pytorch) |
## Model Zoo

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lprnet/README.md
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#
# LPRNet
The Pytorch implementation is [xuexingyu24/License_Plate_Detection_Pytorch](https://github.com/xuexingyu24/License_Plate_Detection_Pytorch).
## How to Run
```
1. generate LPRnet.wts from pytorch
```
git clone https://github.com/wang-xinyu/tensorrtx.git
git clone https://github.com/xuexingyu24/License_Plate_Detection_Pytorch.git
// copy tensorrtx/LRPnet/gen_wts.py License_Plate_Detection_Pytorch
// copy tensorrtx/LRPnet/gen_wts.py to License_Plate_Detection_Pytorch/
// go to License_Plate_Detection_Pytorch/
python genwts.py
// a file 'LPRnet.wts' will be generated.
```
2. build LPRnet and run
```
// put LPRnet.wts into tensorrtx/LPRnet
// go to tensorrtx/LPRnet
mkdir build
cd build
cmake ..
make
sudo ./LPRnet -s // serialize model to plan file i.e. 'LPRnet.engine'
do inference
sudo ./LPRnet -d // deserialize plan file and run inference
sudo ./LPRnet -s // serialize model to file i.e. 'LPRnet.engine'
sudo ./LPRnet -d // deserialize model and run inference
```