update readme

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wang-xinyu 2021-04-02 09:44:28 +08:00
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@ -10,6 +10,7 @@ All the models are implemented in pytorch/mxnet/tensorflown first, and export a
## News
- `2 Apr 2021`. [mingyu6yang](https://github.com/mingyu6yang) added a python wrapper for retinaface, [makaveli10](https://github.com/makaveli10) added DenseNet-121.
- `17 Mar 2021`. [wuzuowuyou](https://github.com/wuzuowuyou) added refinedet, which utilized libtorch to do postprocessing.
- `5 Mar 2021`. [chgit0214](https://github.com/chgit0214) added the LPRNet.
- `31 Jan 2021`. RepVGG added by [upczww](https://github.com/upczww).
@ -82,6 +83,7 @@ Following models are implemented.
|[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) |
|[refinedet](./refinedet)| RefineDet, pytorch implementation from [luuuyi/RefineDet.PyTorch](https://github.com/luuuyi/RefineDet.PyTorch) |
|[densenet](./densenet)| DenseNet-121, from torchvision.models |
## Model Zoo

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# Densenet121
The Pytorch implementation is [makaveli10/densenet](https://github.com/makaveli10/torchtrtz/tree/main/densenet).
The Pytorch implementation is [makaveli10/densenet](https://github.com/makaveli10/torchtrtz/tree/main/densenet). Model from torchvision.
The tensorrt implemenation is taken from [makaveli10/cpptensorrtz](https://github.com/makaveli10/cpptensorrtz/).
## How to Run
@ -13,8 +13,8 @@ git clone https://github.com/makaveli10/torchtrtz.git
// go to torchtrtz/densenet
// Enter these two commands to create densenet121.wts
$ python models.py
$ python gen_trtwts.py
python models.py
python gen_trtwts.py
```
2. build densenet and run
@ -26,11 +26,12 @@ mkdir build
cd build
cmake ..
make
sudo ./densenet -s // serialize model to file i.e. 'LPRnet.engine'
sudo ./densenet -s // serialize model to file i.e. 'densenet.engine'
sudo ./densenet -d // deserialize model and run inference
```
3. Verify output from [torch impl](https://github.com/makaveli10/torchtrtz/blob/main/densenet/README.md)
TensorRT output[:5]:
```
[-0.587389, -0.329202, -1.83404, -1.89935, -0.928404]

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@ -3,6 +3,7 @@
For the Pytorch implementation, you can refer to [luuuyi/RefineDet.PyTorch](https://github.com/luuuyi/RefineDet.PyTorch)
## How to run
```
1. generate wts file. from pytorch
python gen_wts_refinedet.py
@ -19,21 +20,22 @@ make
```
## dependence
```
TensorRT7.0.0.11
OpenCV >= 3.4
libtorch >=1.1.0
```
## feature
1.tensorrt Multi output
2.L2norm
3.Postprocessing with libtorch
## More Information
See the readme in [home page.](https://github.com/wang-xinyu/tensorrtx)
[tensorrt tutorials](https://github.com/wang-xinyu/tensorrtx/tree/master/tutorials)
For more detailed guidance, see [yhl blog](https://www.cnblogs.com/yanghailin/p/14525128.html)

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@ -44,15 +44,13 @@ sudo ./retina_r50 -d // deserialize model file and run inference.
3. check the images generated, as follows. 0_result.jpg
4. we also provide a tensorrt model in python
4. we also provide a python wrapper
```
// install python-tensorrt, pycuda, etc.
// ensure the retina_r50.engine and libdecodeplugin.so have been built
python retinaface_trt.py
```
```
// install python-tensorrt, pycuda, etc.
// ensure the retina_r50.engine and libdecodeplugin.so have been built
python retinaface_trt.py
```
# INT8 Quantization
@ -70,4 +68,5 @@ sudo ./retina_r50 -d // deserialize model file and run inference.
## More Information
See the readme in [home page.](https://github.com/wang-xinyu/tensorrtx)
Check the readme in [home page.](https://github.com/wang-xinyu/tensorrtx)