8.[CMake Command Line Configuration (Ubuntu Only)](#cmake-command-line-configuration-ubuntu-only)
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@@ -37,11 +38,15 @@ This installation section is only intended if you plan to modify the OpenPose co
## Requirements
- 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 and a CPU with at least 8 cores.
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):
Note: These requirements assume the default configuration (i.e. `--net_resolution "656x368"` and `scale_number 1`). You might need more (with a greater net resolution and/or number of scales) or less resources (with smaller 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.
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@@ -87,17 +92,18 @@ The instructions in this section describe the steps to build OpenPose using CMak
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](#cmake-command-line-build-ubuntu-only).
- Windows: download and install the latest CMake win64-x64 msi installer from the [CMake website](https://cmake.org/download/), called `cmake-X.X.X-win64-x64.msi`.
- 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](http://www.nvidia.com/Download/index.aspx) drivers first, and then install CUDA without the Graphics Driver flag or else your system might hang.
- 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.
- 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](http://www.nvidia.com/Download/index.aspx) drivers first, and then install CUDA without the Graphics Driver flag or else your system might hang.
- 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.
5. Windows - **Microsoft Visual Studio (VS) 2015 Enterprise Update 3**:
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](https://stackoverflow.com/questions/43745099/using-cuda-with-visual-studio-2017?answertab=active#tab-top) 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**:
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@@ -214,6 +220,25 @@ By default, the body MPI model is not downloaded. You can download it by turning
#### 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](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/faq.md#speed-up-and-benchmark) for more information about speed and memory requirements in several CPUs and GPUs.
@@ -67,6 +67,8 @@ There are 2 alternatives to save the OpenPose output.
2. (Deprecated) The `write_keypoint` flag uses the OpenCV cv::FileStorage default formats, i.e. JSON (available after OpenCV 3.0), XML, and YML. Note that it does not include any other information othern than keypoints.
Both of them follow the keypoint ordering described in the [Keypoint Ordering](#keypoint-ordering) section.
