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OpenPose - Installation

Contents

  1. Windows Portable Demo
  2. Operating Systems
  3. Requirements
  4. Clone OpenPose
  5. Update OpenPose
  6. Installation
  7. Reinstallation
  8. Uninstallation
  9. Optional Settings
    1. Profiling Speed
    2. MPI Model
    3. CPU Version
    4. 3D Reconstruction Module
    5. Compiling without cuDNN
    6. Custom Caffe (Ubuntu Only)
    7. Custom OpenCV (Ubuntu Only)
    8. Doxygen Documentation Autogeneration (Ubuntu Only)
    9. CMake Command Line Configuration (Ubuntu Only)

Windows Portable Demo

This installation section is only intended if you plan to modify the OpenPose code or integrate it with another library or project. If you just want to use the OpenPose demo in Windows, simply use the latest version of the OpenPose binaries which you can find in the Releases section.

Operating Systems

  • Ubuntu 14 and 16.
  • Windows 8 and 10.
  • Nvidia Jetson TX2, installation instructions in doc/installation_jetson_tx2.md.
  • OpenPose has also been used on Windows 7, Mac, CentOS, and Nvidia Jetson (TK1 and TX1) embedded systems. However, we do not officially support them at the moment.

Requirements

Requirements for the default configuration (you might need more resources with a greater --net_resolution and/or scale_number or less resources by reducing the net resolution and/or using the MPI and MPI_4 models):

  • Nvidia GPU version:
    • NVIDIA graphics card with at least 1.6 GB available (the nvidia-smi command checks the available GPU memory in Ubuntu).
    • At least 2 GB of free RAM memory.
    • Highly recommended: cuDNN.
  • CPU version:
    • Around 8GB of free RAM memory.
  • Highly recommended: a CPU with at least 8 cores.

Clone OpenPose

The first step is to clone the OpenPose repository.

  1. Windows: You might use GitHub Desktop.
  2. Ubuntu:
git clone https://github.com/CMU-Perceptual-Computing-Lab/openpose

Update OpenPose

OpenPose can be easily updated by:

  1. Download the latest changes:
    1. Windows: Clicking the synchronization button at the top-right part in GitHub Desktop in Windows.
    2. Ubuntu: running git pull origin master.
  2. Perform the Reinstallation section described below.

Installation

The instructions in this section describe the steps to build OpenPose using CMake (GUI). There are 3 main steps:

  1. Prerequisites
  2. OpenPose Configuration
  3. OpenPose Building
  4. OpenPose from other Projects (Ubuntu Only)
  5. Run OpenPose

Prerequisites

  1. Download and install CMake GUI:
    • Ubuntu: run the command sudo apt-get install cmake-qt-gui. Note: If you prefer to use CMake through the command line, see Cmake Command Line Build.
    • Windows: download and install the latest CMake win64-x64 msi installer from the CMake website, called cmake-X.X.X-win64-x64.msi.
  2. Nvidia GPU version prerequisites:
    1. CUDA 8:
      • Ubuntu: Run sudo ubuntu/install_cuda.sh or alternatively download and install it from their website.
      • Windows: Install CUDA 8.0 after Visual Studio 2015 is installed to assure that the CUDA installation will generate all necessary files for VS. If CUDA was already installed, re-install CUDA after installing VS!
      • IMPORTANT: As of a recent Windows update, you have to download the Nvidia drivers drivers first, and then install CUDA without the Graphics Driver flag or else your system might hang.
    2. cuDNN 5.1:
      • Ubuntu: Run sudo ubuntu/install_cudnn.sh or alternatively download and install it from their website.
      • Windows (and Ubuntu if manual installation): In order to manually install it, just unzip it and copy (merge) the contents on the CUDA folder, usually /usr/local/cuda/ in Ubuntu and C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0 in Windows.
  3. Ubuntu - Other prerequisites:
    • Caffe prerequisites: By default, OpenPose uses Caffe under the hood. If you have not used Caffe previously, install its dependencies by running sudo bash ./ubuntu/install_cmake.sh.
    • OpenCV must be already installed on your machine. It can be installed with apt-get install libopencv-dev. You can also use your own compiled OpenCV version.
  4. Windows - Microsoft Visual Studio (VS) 2015 Enterprise Update 3:
    • If Visual Studio 2017 Community is desired, we do not officially support it, but it might be compiled by firstly enabling CUDA 8.0 in VS2017 or use VS2017 with CUDA 9 by checking the .vcxproj file and changing the necessary paths from CUDA 8 to 9.
    • VS 2015 Enterprise Update 1 will give some compiler errors and VS 2015 Community has not been tested.
  5. Windows - Caffe, OpenCV, and Caffe prerequisites:
    • CMake automatically downloads all the Windows DLLs. Alternatively, you might prefer to download them manually:
      • Models:
      • Dependencies:
        • Note: Leave the zip files in 3rdparty/windows/ so that CMake does not try to download them again.
        • Caffe: Unzip as 3rdparty/windows/caffe/.
        • Caffe dependencies: Unzip as 3rdparty/windows/caffe3rdparty/.
        • OpenCV 3.1: Unzip as 3rdparty/windows/opencv/.

OpenPose Configuration

  1. Open CMake GUI and select the OpenPose directory as project source directory, and a non-existing or empty sub-directory (e.g., build) where the Makefile files (Ubuntu) or Visual Studio solution (Windows) will be generated. If build does not exist, it will ask you whether to create it. Press Yes.

  1. Press the Configure button, keep the generator in Unix Makefile (Ubuntu) or set it to Visual Studio 14 2015 Win64 (Windows), and press Finish.

  1. If this step is successful, the Configuring done text will appear in the bottom box in the last line. Otherwise, some red text will appear in that same bottom box.

  1. Press the Generate button and proceed to OpenPose Building. You can now close CMake.

Note: If you prefer to use your own custom Caffe or OpenCV versions, see Custom Caffe or Custom OpenCV respectively.

OpenPose Building

Ubuntu

Finally, build the project by running the following commands.

cd build/
make -j`nproc`

Windows

In order to build the project, open the Visual Studio solution (Windows), called build/OpenPose.sln. Then, set the configuration from Debug to Release and press the green triangle icon (alternatively press F5).

OpenPose from other Projects (Ubuntu Only)

If you only intend to use the OpenPose demo, you might skip this step. This step is only recommended if you plan to use the OpenPose API from other projects.

To install the OpenPose headers and libraries into the system environment path (e.g. /usr/local/ or /usr/), run the following command.

cd build/
sudo make install

Once the installation is completed, you can use OpenPose in your other project using the find_package cmake command. Below, is a small example CMakeLists.txt. In order to use this script, you also need to copy FindGFlags.cmake and FindGlog.cmake into your <project_root_directory>/cmake/Modules/ (create the directory if necessary).

cmake_minimum_required(VERSION 2.8.7)

add_definitions(-std=c++11)

list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/Modules")

find_package(GFlags)
find_package(Glog)
find_package(OpenCV)
find_package(OpenPose REQUIRED)

include_directories(${OpenPose_INCLUDE_DIRS} ${GFLAGS_INCLUDE_DIR} ${GLOG_INCLUDE_DIR} ${OpenCV_INCLUDE_DIRS})

add_executable(example.bin example.cpp)

target_link_libraries(example.bin ${OpenPose_LIBS} ${GFLAGS_LIBRARY} ${GLOG_LIBRARY} ${OpenCV_LIBS})

If Caffe was built with OpenPose, it will automatically find it. Otherwise, you will need to link Caffe again as shown below (otherwise, you might get an error like /usr/bin/ld: cannot find -lcaffe).

link_directories(<path_to_caffe_installation>/caffe/build/install/lib)

Run OpenPose

Check OpenPose was properly installed by running it on the default images, video, or webcam: doc/quick_start.md#quick-start.

Reinstallation

In order to re-install OpenPose:

  1. (Ubuntu only) If you ran sudo make install, then run sudo make uninstall in build/.
  2. Delete the build/ folder.
  3. In CMake GUI, click on File --> Delete Cache.
  4. Follow the Installation steps again.

Uninstallation

In order to uninstall OpenPose:

  1. (Ubuntu only) If you ran sudo make install, then run sudo make uninstall in build/.
  2. Remove the OpenPose folder.

Optional Settings

Profiling Speed

OpenPose displays the FPS in the basic GUI. However, more complex speed metrics can be obtained from the command line while running OpenPose. In order to obtain those, compile OpenPose with the PROFILER_ENABLED flag. OpenPose will automatically display time measurements for each subthread after processing F frames (by default F = 1000, but it can be modified with the --profile_speed flag).

  • Time measurement for 1 graphic card: The FPS will be the slowest time displayed in your terminal command line (as OpenPose is multi-threaded). Times are in milliseconds, so FPS = 1000/millisecond_measurement.
  • Time measurement for >1 graphic cards: Assuming n graphic cards, you will have to wait up to n x F frames to visualize each graphic card speed (as the frames are splitted among them). In addition, the FPS would be: FPS = minFPS(speed_per_GPU/n, worst_time_measurement_other_than_GPUs). For < 4 GPUs, this is usually FPS = speed_per_GPU/n.

MPI Model

By default, the body MPI model is not downloaded. You can download it by turning on the DOWNLOAD_MPI_MODEL. It's slightly faster but less accurate and has less keypoints than the COCO body model.

CPU Version

To manually select the CPU Version, open CMake GUI mentioned above, and set the GPU_MODE flag to CPU_ONLY. NOTE: Accuracy of the CPU version is ~1% higher than CUDA version, so the results will vary.

  • On Ubuntu, OpenPose will link against the Intel MKL version (Math Kernel Library) of Caffe. Alternatively, the user can choose his own Caffe version, by unselecting USE_MKL and selecting his own Caffe path.
  • On Windows, it will use the default version of Caffe or one provided by the user on the CPU.

The default CPU version takes ~0.2 seconds per image on Ubuntu (~50x slower than GPU) while the MKL version provides a roughly 2x speedup at ~0.4 seconds. As of now OpenPose does not support MKL on Windows but will at a later date. Also, MKL version does not support unfixed resolution. So a folder of images of different resolutions with openpose, requires the --net_resolution 656x368 flag for example.

The user can configure the environmental variables MKL_NUM_THREADS and OMP_NUM_THREADS. They are set at an optimum parameter level by default (i.e., to the number of threads of the machine). However, they can be tweak by running the following commands into the terminal window, right before running any OpenPose application. Eg:

# Optimal number = Number of threads (used by default)
export MKL_NUM_THREADS="8"
export OMP_NUM_THREADS="8"

Do note that increasing the number of threads results in more memory use. You can check the OpenPose benchmark for more information about speed and memory requirements in several CPUs and GPUs.

3D Reconstruction Module

You can include the 3D reconstruction module by:

  1. Install the FLIR camera software, Spinnaker SDK. It is a propietary software, so we cannot provide direct download link. Note: You might skip this step if you intend to use the 3-D OpenPose module with a different camera brand.
    1. Ubuntu: Get and install the latest Spinnaker SKD version in their default path. OpenPose will automatically find it. Otherwise, set the right path with CMake.
    2. Windows: Donwload the latest Spinnaker SKD version from https://www.ptgrey.com/support/downloads.
      • Copy {PointGreyParentDirectory}\Point Grey Research\Spinnaker\bin64\vs2015\ as {OpenPoseDirectory}\3rdparty\windows\spinnaker\bin\. You can remove all the *.exe files.
      • Copy {PointGreyParentDirectory}\Point Grey Research\Spinnaker\include\ as {OpenPoseDirectory}\3rdparty\windows\spinnaker\include\.
      • Copy Spinnaker_v140.lib and Spinnakerd_v140.lib from {PointGreyParentDirectory}\Point Grey Research\Spinnaker\lib64\vs2015\ into {OpenPoseDirectory}\3rdparty\windows\spinnaker\lib\.
      • (Optional) Spinnaker SDK overview: https://www.ptgrey.com/spinnaker-sdk.
  2. Install the 3D visualizer, FreeGLUT:
    1. Ubuntu: run sudo apt-get update && sudo apt-get install build-essential freeglut3 freeglut3-dev libxmu-dev libxi-dev and reboot your PC.
    2. Windows:
      1. It is automatically downloaded by the CMake installer.
      2. Alternatively, if you prefer to download it yourself, you could either:
        1. Double click on 3rdparty\windows\getFreeglut.bat.
        2. Download this version from our server and unzip it in {OpenPoseDirectory}\3rdparty\windows\freeglut\.
        3. Download the latest MSVC Package from http://www.transmissionzero.co.uk/software/freeglut-devel/.
          • Copy {freeglutParentDirectory}\freeglut\bin\x64\ as {OpenPoseDirectory}\3rdparty\windows\freeglut\bin\.
          • Copy {freeglutParentDirectory}\freeglut\include\ as {OpenPoseDirectory}\3rdparty\windows\freeglut\include\.
          • Copy {freeglutParentDirectory}\freeglut\lib\x64\ as {OpenPoseDirectory}\3rdparty\windows\freeglut\lib\.
  3. Follow the CMake installation steps. In addition, set the WITH_FLIR_CAMERA (only if Spinnaker was installed) and WITH_3D_RENDERER options.
  4. Increased accuracy with Ceres solver (Ubuntu only): For extra 3-D reconstruction accuracy, run sudo apt-get install libeigen3-dev, install Ceres solver, and enable WITH_CERES in CMake when installing OpenPose. Ceres is harder to install in Windows, so we have not tested it so far in there. Feel free to make a pull request if you do.

After installation, check the doc/3d_reconstruction_demo.md instructions.

Compiling without cuDNN

The cuDNN library is not mandatory, but required for full keypoint detection accuracy. In case your graphics card is not compatible with cuDNN, you can disable it by unchecking USE_CUDNN in CMake.

Then, you would have to reduce the --net_resolution flag to fit the model into the GPU memory. You can try values like 640x320, 320x240, 320x160, or 160x80 to see your GPU memory capabilities. After finding the maximum approximate resolution that your GPU can handle without throwing an out-of-memory error, adjust the net_resolution ratio to your image or video to be processed (see the --net_resolution explanation from doc/demo_overview.md), or use -1 (e.g. --net_resolution -1x320).

Custom Caffe (Ubuntu Only)

We only modified some Caffe compilation flags and minor details. You can use your own Caffe distribution, simply specify the Caffe include path and the library as shown below. You will also need to turn off the BUILD_CAFFE variable. Note that cuDNN is required in order to get the maximum possible accuracy in OpenPose.

Custom OpenCV (Ubuntu Only)

If you have built OpenCV from source and OpenPose cannot find it automatically, you can set the OPENCV_DIR variable to the directory where you build OpenCV.

Doxygen Documentation Autogeneration (Ubuntu Only)

You can generate the documentation by setting the BUILD_DOCS flag. The documentation will be generated in doc/doxygen/html/index.html. You can simply open it with double-click (your default browser should automatically display it).

CMake Command Line Configuration (Ubuntu Only)

Note that this step is unnecessary if you already used the CMake GUI alternative.

Create a build folder in the root OpenPose folder, where you will build the library --

cd openpose
mkdir build
cd build

The next step is to generate the Makefiles. Now there can be multiple scenarios based on what the user already has e.x. Caffe might be already installed and the user might be interested in building OpenPose against that version of Caffe instead of requiring OpenPose to build Caffe from scratch.

SCENARIO 1 -- Caffe not installed and OpenCV installed using apt-get

In the build directory, run the below command --

cmake ..
SCENARIO 2 -- Caffe installed and OpenCV build from source

In this example, we assume that Caffe and OpenCV are already present. The user needs to supply the paths of the libraries and the include directories to CMake. For OpenCV, specify the include directories and the libraries directory using OpenCV_INCLUDE_DIRS and OpenCV_LIBS_DIR variables respectively. Alternatively, the user can also specify the path to the OpenCVConfig.cmake file by setting the OpenCV_CONFIG_FILE variable. For Caffe, specify the include directory and library using the Caffe_INCLUDE_DIRS and Caffe_LIBS variables. This will be where you installed Caffe. Below is an example of the same.

cmake -DOpenCV_INCLUDE_DIRS=/home/"${USER}"/softwares/opencv/build/install/include \
  -DOpenCV_LIBS_DIR=/home/"${USER}"/softwares/opencv/build/install/lib \
  -DCaffe_INCLUDE_DIRS=/home/"${USER}"/softwares/caffe/build/install/include \
  -DCaffe_LIBS=/home/"${USER}"/softwares/caffe/build/install/lib/libcaffe.so -DBUILD_CAFFE=OFF ..
cmake -DOpenCV_CONFIG_FILE=/home/"${USER}"/softwares/opencv/build/install/share/OpenCV/OpenCVConfig.cmake \
  -DCaffe_INCLUDE_DIRS=/home/"${USER}"/softwares/caffe/build/install/include \
  -DCaffe_LIBS=/home/"${USER}"/softwares/caffe/build/install/lib/libcaffe.so -DBUILD_CAFFE=OFF ..
SCENARIO 3 -- OpenCV already installed

If Caffe is not already present but OpenCV is, then use the below command.

cmake -DOpenCV_INCLUDE_DIRS=/home/"${USER}"/softwares/opencv/build/install/include \
  -DOpenCV_LIBS_DIR=/home/"${USER}"/softwares/opencv/build/install/lib ..
cmake -DOpenCV_CONFIG_FILE=/home/"${USER}"/softwares/opencv/build/install/share/OpenCV/OpenCVConfig.cmake ..