openpose/doc/installation_deprecated.md

OpenPose - Installation (deprecated)

Contents

1. Operating Systems
2. Requirements
3. Clone OpenPose
4. Update OpenPose
5. Ubuntu
6. Windows
7. Doxygen Documentation Autogeneration
8. Custom Caffe
9. Compiling without cuDNN

Operating Systems

See doc/installation.md#operating-systems.

Requirements

See doc/installation.md#requirements.

Clone OpenPose

See doc/installation.md#clone-openpose.

Update OpenPose

See doc/installation.md#update-openpose.

Ubuntu

Installation - CMake

Recommended installation method, it is simpler and offers more customization settings. See doc/installation.md.

Prerequisites (Script Compilation or Manual Compilation)

CUDA, cuDNN, OpenCV and Atlas must be already installed on your machine:

1. [CUDA](https://developer.nvidia.com/cuda-80-ga2-download-archive) must be installed. You should reboot your machine after installing CUDA.
2. [cuDNN](https://developer.nvidia.com/cudnn): Once you have downloaded it, just unzip it and copy (merge) the contents on the CUDA folder, e.g., `/usr/local/cuda-8.0/`. Note: We found OpenPose working ~10% faster with cuDNN 5.1 compared to cuDNN 6. Otherwise, check [Compiling without cuDNN](#compiling-without-cudnn).
3. OpenCV can be installed with `apt-get install libopencv-dev`. If you have compiled OpenCV 3 by your own, follow [Manual Compilation](#manual-compilation). After both Makefile.config files have been generated, edit them and uncomment the line `# OPENCV_VERSION := 3`. You might alternatively modify all `Makefile.config.UbuntuXX` files and then run the scripts in step 2.
4. In addition, OpenCV 3 does not incorporate the `opencv_contrib` module by default. Assuming you have OpenCV 3 compiled with the contrib module and you want to use it, append `opencv_contrib` at the end of the line `LIBRARIES += opencv_core opencv_highgui opencv_imgproc` in the `Makefile` file.
5. Atlas can be installed with `sudo apt-get install libatlas-base-dev`. Instead of Atlas, you can use OpenBLAS or Intel MKL by modifying the line `BLAS := atlas` in the same way as previosuly mentioned for the OpenCV version selection.

Installation - Script Compilation

Build Caffe & the OpenPose library + download the required Caffe models for Ubuntu 14.04 or 16.04 (auto-detected for the script) and CUDA 8:

bash scripts/ubuntu_deprecated/install_caffe_and_openpose_if_cuda8.sh

Highly important: This script only works with CUDA 8 and Ubuntu 14 or 16. Otherwise, see doc/installation.md or Installation - Manual Compilation.

Installation - Manual Compilation

Alternatively to the script installation, if you want to use CUDA 7, avoid using sh scripts, change some configuration labels (e.g., OpenCV version), etc., then:

1. Install the Caffe prerequisites.

2. Compile Caffe and OpenPose by running these lines:

   ### Install Caffe ###
   git submodule update --init --recursive --remote
   cd 3rdparty/caffe/
   # Select your desired Makefile file (run only one of the next 4 commands)
   cp Makefile.config.Ubuntu14_cuda7.example Makefile.config # Ubuntu 14, cuda 7
   cp Makefile.config.Ubuntu14_cuda8.example Makefile.config # Ubuntu 14, cuda 8
   cp Makefile.config.Ubuntu16_cuda7.example Makefile.config # Ubuntu 16, cuda 7
   cp Makefile.config.Ubuntu16_cuda8.example Makefile.config # Ubuntu 16, cuda 8
   # Change any custom flag from the resulting Makefile.config (e.g., OpenCV 3, Atlas/OpenBLAS/MKL, etc.)
   # Compile Caffe
   make all -j`nproc` && make distribute -j`nproc`
   
   ### Install OpenPose ###
   cd ../../models/
   bash ./getModels.sh # It just downloads the Caffe trained models
   cd ..
   cp scripts/ubuntu/Makefile.example Makefile
   # Same file cp command as the one used for Caffe
   cp scripts/ubuntu_deprecated/Makefile.config.Ubuntu14_cuda7.example Makefile.config
   # Change any custom flag from the resulting Makefile.config (e.g., OpenCV 3, Atlas/OpenBLAS/MKL, etc.)
   make all -j`nproc`
   

   NOTE: If you want to use your own Caffe distribution, follow the steps on Custom Caffe section and later re-compile the OpenPose library:

   bash ./install_openpose_if_cuda8.sh
   

   Note: These steps only need to be performed once. If you are interested in making changes to the OpenPose library, you can simply recompile it with:

   make clean
   make all -j`nproc`
   

Highly important: There are 2 Makefile.config.Ubuntu##.example analogous files, one in the main folder and one in 3rdparty/caffe/, corresponding to OpenPose and Caffe configuration files respectively. Any change must be done to both files (e.g., OpenCV 3 flag, Atlab/OpenBLAS/MKL flag, etc.). E.g., for CUDA 8 and Ubuntu16: 3rdparty/caffe/Makefile.config.Ubuntu16_cuda8.example and scripts/ubuntu_deprecated/Makefile.config.Ubuntu16_cuda8.example.

Reinstallation

If you updated some software that our library or 3rdparty use, or you simply want to reinstall it:

1. Clean the OpenPose and Caffe compilation folders:

make clean && cd 3rdparty/caffe && make clean

2. Repeat the Installation steps. You do not need to download the models again.

Uninstallation

You just need to remove the OpenPose folder, by default called openpose/. E.g., rm -rf openpose/.

Windows

Installation - Library

1. Install the pre-requisites:
   1. 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.
   2. CUDA 8: Install it on the default location, C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0. Otherwise, modify the Visual Studio project solution accordingly. 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 it after installing VS!
   3. cuDNN 5.1: Once you have downloaded it, just unzip it and copy (merge) the contents on the CUDA folder, C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0.

CMake Installer

Recommended installation method, it is simpler and offers more customization settings. See doc/installation.md. Note that it is a beta version, post in GitHub any issue you find.

Deprecated Windows Installer

Note: This installer will not incorporate any new features, we recommend to use the CMake installer.

1. Download the OpenPose dependencies and models (body, face and hand models) by double-clicking on {openpose_path}\windows\download_3rdparty_and_models.bat. Alternatively, you might prefer to download them manually:
   • Models:
     • COCO model: download in models/pose/coco/.
     • MPI model: download in models/pose/mpi/.
     • Face model: download in models/face/.
     • Hands model: download in models/hand/.
   • Dependencies:
     • Caffe: Unzip as 3rdparty/windows/caffe/.
     • Caffe dependencies: Unzip as 3rdparty/windows/caffe3rdparty/.
     • OpenCV 4.1.1: Unzip as 3rdparty/windows/opencv/.
2. Open the Visual Studio project sln file by double-cliking on {openpose_path}\windows\OpenPose.sln.
3. In order to verify OpenPose is working, try compiling and executing the demo:
   1. Right click on OpenPoseDemo --> Set as StartUp Project.
   2. Change Debug by Release mode.
   3. Compile it and run it with F5 or the green play icon.
4. If you have a webcam connected, OpenPose will automatically start after being compiled.
5. In order to use the created exe file from the command line (i.e., outside Visual Studio), you have to:
   1. Copy all the DLLs located on {openpose_folder}\3rdparty\windows\caffe\bin\ on the exe folder: {openpose_folder}\windows\x64\Release.
   2. Copy all the DLLs located on {openpose_folder}\3rdparty\windows\opencv\x64\vc14\bin\ on the exe folder: {openpose_folder}\windows\x64\Release.
   3. Open the Windows cmd (Windows button + X, then A).
   4. Go to the OpenPose directory, assuming OpenPose has been downloaded on C:\openpose: cd C:\openpose\.
   5. Run the tutorial commands.
6. Check OpenPose was properly installed by running it on the default images, video or webcam: doc/quick_start.md#quick-start.

Uninstallation

You just need to remove the OpenPose or portable demo folder.

Reinstallation

If you updated some software that our library or 3rdparty use, or you simply want to reinstall it:

1. Open the Visual Studio project sln file by double-cliking on {openpose_path}\windows\OpenPose.sln.
2. Clean the OpenPose project by right-click on Solution 'OpenPose' and Clean Solution.
3. Compile it and run it with F5 or the green play icon.

Doxygen Documentation Autogeneration

You can generate the documentation by running the following command. 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).

cd doc/
doxygen doc_autogeneration.doxygen

Custom Caffe

We only modified some Caffe compilation flags and minor details. You can use your own Caffe distribution, these are the files we added and modified:

1. Added files: install_caffe.sh; as well as Makefile.config.Ubuntu14.example, Makefile.config.Ubuntu16.example, Makefile.config.Ubuntu14_cuda_7.example and Makefile.config.Ubuntu16_cuda_7.example (extracted from Makefile.config.example). Basically, you must enable cuDNN.
2. Edited file: Makefile. Search for "# OpenPose: " to find the edited code. We basically added the C++11 flag to avoid issues in some old computers.
3. Optional - deleted Caffe file: Makefile.config.example.
4. In order to link it to OpenPose:
   1. Run make all && make distribute in your Caffe version.
   2. Open the OpenPose Makefile config file: ./Makefile.config.UbuntuX.example (where X depends on your OS and CUDA version).
   3. Modify the Caffe folder directory variable (CAFFE_DIR) to your custom Caffe distribute folder location in the previous OpenPose Makefile config file.

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:

• Ubuntu: Disable USE_CUDNN in the Makefile.config file in 3rdparty/caffe, and recompiling Caffe.
• Windows: Compiling Caffe by your own with without cuDNN support and replacing the 3rdparty/windows/caffe) folder by your own implementation.

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).