/3DCenterNet_GTX3090

Primary LanguageC++MIT LicenseMIT

TensorRT-CenterNet-3D

Most parts of this Repo are based on CaoWGG, Thanks for that great work.

Attention:::

mv /usr/lib/libcuda.so /usr/lib/libcuda.so.bak then run program!

1. Enviroments

ubuntu 18.04
TensorRT 8.2GA
onnx-tensorrt for tensorrt8,please refer to other repos, onnx-tensorrt repo
cuda 11.2

pip show torch
Name: torch
Version: 1.7.0+cu110
Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
Home-page: https://pytorch.org/
Author: PyTorch Team
Author-email: packages@pytorch.org
License: BSD-3
Location: /home/{Path}/anaconda3/envs/CenterTrack/lib/python3.6/site-packages
Requires: numpy, typing-extensions, future, dataclasses
Required-by: torchvision, torchaudio

GTX3090

-- The C compiler identification is GNU 7.5.0
-- The CXX compiler identification is GNU 7.5.0
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: /usr/bin/cc - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: /usr/bin/c++ - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Found Protobuf: /usr/local/lib/libprotobuf.so;-lpthread (found version "3.15.8") 
Generated: /home/{Path}/TensorRT-CenterNet-3D-master/build/onnx-tensorrt/third_party/onnx/onnx/onnx_onnx2trt_onnx-ml.proto
Generated: /home/{Path}/TensorRT-CenterNet-3D-master/build/onnx-tensorrt/third_party/onnx/onnx/onnx-operators_onnx2trt_onnx-ml.proto
Generated: /home/{Path}/TensorRT-CenterNet-3D-master/build/onnx-tensorrt/third_party/onnx/onnx/onnx-data_onnx2trt_onnx.proto
-- 
-- ******** Summary ********
--   CMake version         : 3.22.2
--   CMake command         : /snap/cmake/1005/bin/cmake
--   System                : Linux
--   C++ compiler          : /usr/bin/c++
--   C++ compiler version  : 7.5.0
--   CXX flags             :  -Wall -Wno-deprecated-declarations -Wno-unused-function -Wnon-virtual-dtor
--   Build type            : Release
--   Compile definitions   : SOURCE_LENGTH=42;ONNX_NAMESPACE=onnx2trt_onnx
--   CMAKE_PREFIX_PATH     : 
--   CMAKE_INSTALL_PREFIX  : /usr/local
--   CMAKE_MODULE_PATH     : 
-- 
--   ONNX version          : 1.8.0
--   ONNX NAMESPACE        : onnx2trt_onnx
--   ONNX_BUILD_TESTS      : OFF
--   ONNX_BUILD_BENCHMARKS : OFF
--   ONNX_USE_LITE_PROTO   : OFF
--   ONNXIFI_DUMMY_BACKEND : OFF
--   ONNXIFI_ENABLE_EXT    : OFF
-- 
--   Protobuf compiler     : /usr/local/bin/protoc
--   Protobuf includes     : /usr/local/include
--   Protobuf libraries    : /usr/local/lib/libprotobuf.so;-lpthread
--   BUILD_ONNX_PYTHON     : OFF
-- Found CUDA headers at /usr/local/cuda/include
-- Found TensorRT headers at /usr/include/x86_64-linux-gnu
-- Find TensorRT libs at /usr/lib/x86_64-linux-gnu/libnvinfer.so;/usr/lib/x86_64-linux-gnu/libnvinfer_plugin.so
-- Found TENSORRT: /usr/include/x86_64-linux-gnu  
-- Found Threads: TRUE  
-- Found CUDA: /usr/local/cuda-11.2 (found version "11.2") 
-- Found TensorRT headers at /usr/include/x86_64-linux-gnu
-- Found TensorRT libs /usr/lib/x86_64-linux-gnu/libnvinfer.so
-- Found OpenCV: /usr/local (found version "4.5.1") 
-- Configuring done
-- Generating done
-- Build files have been written to: /home/{Path}/TensorRT-CenterNet-3D-master/build

    And i use CenterTrack virtual environments to compile the programs, py3.6 version

2. Performance

3. How to use

  • download the ddd_3dop.pth from here
  • Convert CenterNet-3D model to onnx. See here for details, Use netron to observe whether the output of the converted onnx model is (('hm', 3), ('dep', 1), ('rot', 8), ('dim', 3), ('wh', 2), ('reg', 2))
  • set the OPENCV path in ./src/CMakeLists.txt ,set the TENSORRT path in ./CMakeLists.txt
  • uncomment the configs of 3-D model in ./include/ctdetConfig.h and comment others.
  • build
git clone https://github.com/Qjizhi/TensorRT-CenterNet-3D.git
cd TensorRT-CenterNet-3D
mkdir build
cd build && cmake .. && make
cd ..
  • build the engie and do the inference
./buildEngine -i model/ddd_3dop.onnx -o model/ddd_3dop.engine
./runDet -e model/ddd_3dop.engine -i 000292.png -c test.h264

4. Good to know

  • This codes are just for testing and will not be well maintained, for any suggestions and improvements, please propose an issue.
  • With the help of TensorRT, the inference time has been shortened from 0.227s to 98.89ms.
  • The functions of previous Repo are still remained, for exmaple, centerface...

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