TensorRT-使用TensorRT部署LaneTT模型-优质算法部署项目实战.zip

# TensorRT-GANet This repo deploys [GANet](https://github.com/Wolfwjs/GANet) using TensorRT. ## Steps 1. Install [TensorRT 8.0](https://developer.nvidia.cn/nvidia-tensorrt-8x-download) ```Shell # https://developer.nvidia.cn/nvidia-tensorrt-8x-download tar -xvzf TensorRT-8.0.3.4.Linux.x86_64-gnu.cuda-10.2.cudnn8.2.tar.gz # export TENSORRT_DIR=~/TensorRT-8.0.3.4 git clone -b release/8.0 https://github.com/Yibin122/TensorRT.git # MMCVDeformConv2d plugin cd TensorRT/ git submodule update --init --recursive mkdir -p build && cd build cmake .. -DTRT_LIB_DIR=~/TensorRT-8.0.3.4/lib -DTRT_OUT_DIR=`pwd`/out -DCUDA_VERSION=10.2 make -j$(nproc) make install ``` 2. PyTorch to ONNX ```bash git clone https://github.com/Wolfwjs/GANet.git cd GANet python setup.py develop # 用当前repo的deform_conv.py替换: GANet/mmdet/ops/dcn/deform_conv.py python ganet_pth2onnx.py ``` 3. ONNX to TensorRT ```bash cd ~/TensorRT-8.0.3.4/bin ./trtexec --workspace=4096 --onnx=${model_path}/ganet.onnx --saveEngine=${model_path}/ganet.trt8 ``` ## TODO - [ ] implement postprocessing