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@ -10,6 +10,7 @@ All the models are implemented in pytorch/mxnet/tensorflown first, and export a
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## News
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- `2 Apr 2021`. [mingyu6yang](https://github.com/mingyu6yang) added a python wrapper for retinaface, [makaveli10](https://github.com/makaveli10) added DenseNet-121.
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- `17 Mar 2021`. [wuzuowuyou](https://github.com/wuzuowuyou) added refinedet, which utilized libtorch to do postprocessing.
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- `5 Mar 2021`. [chgit0214](https://github.com/chgit0214) added the LPRNet.
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- `31 Jan 2021`. RepVGG added by [upczww](https://github.com/upczww).
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@ -82,6 +83,7 @@ Following models are implemented.
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|[repvgg](./repvgg)| RepVGG, pytorch implementation from [DingXiaoH/RepVGG](https://github.com/DingXiaoH/RepVGG) |
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|[lprnet](./lprnet)| LPRNet, pytorch implementation from [xuexingyu24/License_Plate_Detection_Pytorch](https://github.com/xuexingyu24/License_Plate_Detection_Pytorch) |
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|[refinedet](./refinedet)| RefineDet, pytorch implementation from [luuuyi/RefineDet.PyTorch](https://github.com/luuuyi/RefineDet.PyTorch) |
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|[densenet](./densenet)| DenseNet-121, from torchvision.models |
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## Model Zoo
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@ -1,6 +1,6 @@
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# Densenet121
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The Pytorch implementation is [makaveli10/densenet](https://github.com/makaveli10/torchtrtz/tree/main/densenet).
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The Pytorch implementation is [makaveli10/densenet](https://github.com/makaveli10/torchtrtz/tree/main/densenet). Model from torchvision.
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The tensorrt implemenation is taken from [makaveli10/cpptensorrtz](https://github.com/makaveli10/cpptensorrtz/).
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## How to Run
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@ -13,8 +13,8 @@ git clone https://github.com/makaveli10/torchtrtz.git
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// go to torchtrtz/densenet
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// Enter these two commands to create densenet121.wts
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$ python models.py
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$ python gen_trtwts.py
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python models.py
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python gen_trtwts.py
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```
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2. build densenet and run
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@ -26,11 +26,12 @@ mkdir build
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cd build
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cmake ..
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make
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sudo ./densenet -s // serialize model to file i.e. 'LPRnet.engine'
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sudo ./densenet -s // serialize model to file i.e. 'densenet.engine'
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sudo ./densenet -d // deserialize model and run inference
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```
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3. Verify output from [torch impl](https://github.com/makaveli10/torchtrtz/blob/main/densenet/README.md)
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TensorRT output[:5]:
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```
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[-0.587389, -0.329202, -1.83404, -1.89935, -0.928404]
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@ -3,6 +3,7 @@
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For the Pytorch implementation, you can refer to [luuuyi/RefineDet.PyTorch](https://github.com/luuuyi/RefineDet.PyTorch)
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## How to run
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```
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1. generate wts file. from pytorch
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python gen_wts_refinedet.py
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@ -19,21 +20,22 @@ make
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```
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## dependence
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```
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TensorRT7.0.0.11
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OpenCV >= 3.4
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libtorch >=1.1.0
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```
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## feature
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1.tensorrt Multi output
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2.L2norm
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3.Postprocessing with libtorch
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## More Information
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See the readme in [home page.](https://github.com/wang-xinyu/tensorrtx)
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[tensorrt tutorials](https://github.com/wang-xinyu/tensorrtx/tree/master/tutorials)
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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.
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3. check the images generated, as follows. 0_result.jpg
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4. we also provide a tensorrt model in python
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4. we also provide a python wrapper
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```
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// install python-tensorrt, pycuda, etc.
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// ensure the retina_r50.engine and libdecodeplugin.so have been built
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python retinaface_trt.py
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```
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```
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// install python-tensorrt, pycuda, etc.
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// ensure the retina_r50.engine and libdecodeplugin.so have been built
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python retinaface_trt.py
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```
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# INT8 Quantization
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@ -70,4 +68,5 @@ sudo ./retina_r50 -d // deserialize model file and run inference.
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## More Information
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See the readme in [home page.](https://github.com/wang-xinyu/tensorrtx)
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Check the readme in [home page.](https://github.com/wang-xinyu/tensorrtx)
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