RapidPoseTriangulation

Fast triangulation of multiple persons from multiple camera views.

Build

Clone this project with submodules:

git clone --recurse-submodules https://gitlab.com/Percipiote/RapidPoseTriangulation.git
cd RapidPoseTriangulation/

Enable GPU-access for docker building:

Run sudo nano /etc/docker/daemon.json and add:

{
  "runtimes": {
    "nvidia": {
      "args": [],
      "path": "nvidia-container-runtime"
    }
  },
  "default-runtime": "nvidia"
}

Restart docker: sudo systemctl restart docker

Build docker container:

docker build --progress=plain -t rapidposetriangulation .
./run_container.sh

Build triangulator:

cd /RapidPoseTriangulation/swig/ && make all && cd ../tests/ && python3 test_interface.py && cd ..

cd /RapidPoseTriangulation/scripts/ && \
g++ -std=c++2a -fPIC -O3 -march=native -Wall -Werror -flto=auto \
  -I /RapidPoseTriangulation/rpt/ \
  -isystem /usr/include/opencv4/ \
  -isystem /onnxruntime/include/ \
  -isystem /onnxruntime/include/onnxruntime/core/session/ \
  -isystem /onnxruntime/include/onnxruntime/core/providers/tensorrt/ \
  -L /onnxruntime/build/Linux/Release/ \
  test_skelda_dataset.cpp \
  /RapidPoseTriangulation/rpt/*.cpp \
  -o test_skelda_dataset.bin \
  -Wl,--start-group \
    -lonnxruntime_providers_tensorrt \
    -lonnxruntime_providers_shared \
    -lonnxruntime_providers_cuda \
    -lonnxruntime \
  -Wl,--end-group \
  $(pkg-config --libs opencv4) \
  -Wl,-rpath,/onnxruntime/build/Linux/Release/ \
&& cd ..

Test with samples:

python3 /RapidPoseTriangulation/scripts/test_triangulate.py

Test with skelda dataset:

export CUDA_VISIBLE_DEVICES=0
python3 /RapidPoseTriangulation/scripts/test_skelda_dataset.py

Extras

Exporting tools for 2D models are at mmdeploy directory.
For usage in combination with ROS2 see ros directory.
Running on a Nvidia Jetson is also possible with jetson directory.

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RapidPoseTriangulation

Build

Extras

2.4 KiB

Raw Blame History