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Created October 27, 2019 23:50
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How to install OpenCV 4.1 with CUDA 10.0 in Ubuntu 18.04
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Install_OpenCV4_CUDA10.md

How to install OpenCV 4.1.0 with CUDA 10.0 in Ubuntu distro 18.04

First of all install update and upgrade your system:

    $ sudo apt update
    $ sudo apt upgrade

Then, install required libraries:

  • Generic tools:

      $ sudo apt install build-essential cmake pkg-config unzip yasm git checkinstall

  • Image I/O libs

    $ sudo apt install libjpeg-dev libpng-dev libtiff-dev libjasper-dev

  • Video/Audio Libs - FFMPEG, GSTREAMER, x264 and so on.

    $ sudo apt install libavcodec-dev libavformat-dev libswscale-dev libavresample-dev
$ sudo apt install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev
$ sudo apt install libxvidcore-dev x264 libx264-dev libfaac-dev libmp3lame-dev libtheora-dev 
$ sudo apt install libfaac-dev libmp3lame-dev libvorbis-dev

  • OpenCore - Adaptive Multi Rate Narrow Band (AMRNB) and Wide Band (AMRWB) speech codec

    $ sudo apt install libopencore-amrnb-dev libopencore-amrwb-dev

  • Cameras programming interface libs

    $ sudo apt-get install libdc1394-22 libdc1394-22-dev libxine2-dev libv4l-dev v4l-utils
$ cd /usr/include/linux
$ sudo ln -s -f ../libv4l1-videodev.h videodev.h
$ cd ~

  • GTK lib for the graphical user functionalites coming from OpenCV highghui module

    $ sudo apt-get install libgtk-3-dev

  • Python libraries for python2 and python3:

    $ sudo apt-get install python3-dev python3-pip
$ sudo -H pip3 install -U pip numpy
$ sudo apt install python3-tesresources

  • Parallelism library C++ for CPU

    $ sudo apt-get install libtbb-dev

  • Optimization libraries for OpenCV

    $ sudo apt-get install libatlas-base-dev gfortran

  • Optional libraries:

    $ sudo apt-get install libprotobuf-dev protobuf-compiler
$ sudo apt-get install libgoogle-glog-dev libgflags-dev
$ sudo apt-get install libgphoto2-dev libeigen3-dev libhdf5-dev doxygen

We will now proceed with the installation (see the Qt flag that is disabled to do not have conflicts with Qt5.0).

$ cd ~
$ wget -O opencv.zip https://github.com/opencv/opencv/archive/4.1.0.zip
$ wget -O opencv_contrib.zip https://github.com/opencv/opencv_contrib/archive/4.1.0.zip
$ unzip opencv.zip
$ unzip opencv_contrib.zip

$ echo "Create a virtual environtment for the python binding module"
$ sudo pip install virtualenv virtualenvwrapper
$ sudo rm -rf ~/.cache/pip
$ echo "Edit ~/.bashrc"
$ export WORKON_HOME=$HOME/.virtualenvs
$ export VIRTUALENVWRAPPER_PYTHON=/usr/bin/python3
$ source /usr/local/bin/virtualenvwrapper.sh
$ mkvirtualenv cv -p python3
$ pip install numpy

$ echo "Procced with the installation"
$ cd opencv-4.1.0
$ mkdir build
$ cd build

$ cmake -D CMAKE_BUILD_TYPE=RELEASE \
-D CMAKE_INSTALL_PREFIX=/usr/local \
-D INSTALL_PYTHON_EXAMPLES=ON \
-D INSTALL_C_EXAMPLES=OFF \
-D WITH_TBB=ON \
-D WITH_CUDA=ON \
-D BUILD_opencv_cudacodec=OFF \
-D ENABLE_FAST_MATH=1 \
-D CUDA_FAST_MATH=1 \
-D WITH_CUBLAS=1 \
-D WITH_V4L=ON \
-D WITH_QT=OFF \
-D WITH_OPENGL=ON \
-D WITH_GSTREAMER=ON \
-D OPENCV_GENERATE_PKGCONFIG=ON \
-D OPENCV_PC_FILE_NAME=opencv.pc \
-D OPENCV_ENABLE_NONFREE=ON \
-D OPENCV_PYTHON3_INSTALL_PATH=~/.virtualenvs/cv/lib/python3.6/site-packages \
-D OPENCV_EXTRA_MODULES_PATH=~/downloads/opencv/opencv_contrib-4.1.0/modules \
-D PYTHON_EXECUTABLE=~/.virtualenvs/cv/bin/python \
-D BUILD_EXAMPLES=ON ..

If you want to build the libraries statically you only have to include the -D BUILD_SHARED_LIBS=OFF

$ cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D INSTALL_PYTHON_EXAMPLES=ON -D INSTALL_C_EXAMPLES=OFF -D WITH_TBB=ON -D WITH_CUDA=ON -D BUILD_opencv_cudacodec=OFF -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D WITH_CUBLAS=1 -D WITH_V4L=ON -D WITH_QT=OFF -D WITH_OPENGL=ON -D WITH_GSTREAMER=ON -D OPENCV_GENERATE_PKGCONFIG=ON -D OPENCV_PC_FILE_NAME=opencv.pc -D OPENCV_ENABLE_NONFREE=ON -D OPENCV_PYTHON3_INSTALL_PATH=~/.virtualenvs/cv/lib/python3.6/site-packages -D OPENCV_EXTRA_MODULES_PATH=~/downloads/opencv/opencv_contrib-4.1.0/modules -D PYTHON_EXECUTABLE=~/.virtualenvs/cv/bin/python -D BUILD_EXAMPLES=ON -D BUILD_SHARED_LIBS=OFF ..

In case you do not want to include include CUDA set -D WITH_CUDA=OFF

$ cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D INSTALL_PYTHON_EXAMPLES=ON -D INSTALL_C_EXAMPLES=OFF -D WITH_TBB=ON -D WITH_CUDA=OFF -D BUILD_opencv_cudacodec=OFF -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D WITH_CUBLAS=1 -D WITH_V4L=ON -D WITH_QT=OFF -D WITH_OPENGL=ON -D WITH_GSTREAMER=ON -D OPENCV_GENERATE_PKGCONFIG=ON -D OPENCV_PC_FILE_NAME=opencv.pc -D OPENCV_ENABLE_NONFREE=ON -D OPENCV_PYTHON3_INSTALL_PATH=~/.virtualenvs/cv/lib/python3.6/site-packages -D OPENCV_EXTRA_MODULES_PATH=~/downloads/opencv/opencv_contrib-4.1.0/modules -D PYTHON_EXECUTABLE=~/.virtualenvs/cv/bin/python -D BUILD_EXAMPLES=ON ..

Before the compilation you must check that CUDA has been enabled in the configuration summary printed on the screen.

--   NVIDIA CUDA:                   YES (ver 10.0, CUFFT CUBLAS NVCUVID FAST_MATH)
--     NVIDIA GPU arch:             30 35 37 50 52 60 61 70 75
--     NVIDIA PTX archs:

If it is fine proceed with the compilation (Use nproc to know the number of cpu cores):

$ nproc
$ make -j8
$ sudo make install

Include the libs in your environment

$ sudo /bin/bash -c 'echo "/usr/local/lib" >> /etc/ld.so.conf.d/opencv.conf'
$ sudo ldconfig

If you want to have available opencv python bindings in the system environment you should copy the created folder during the installation of OpenCV (* -D OPENCV_PYTHON3_INSTALL_PATH=~/.virtualenvs/cv/lib/python3.6/site-packages *) into the dist-packages folder of the target python interpreter:

$ sudo cp -r ~/.virtualenvs/cv/lib/python3.6/site-packages/cv2 /usr/local/lib/python3.6/dist-packages

$ echo "Modify config-3.6.py to point to the target directory" 
$ sudo nano /usr/local/lib/python3.6/dist-packages/cv2/config-3.6.py 

``` 
    PYTHON_EXTENSIONS_PATHS = [
    os.path.join('/usr/local/lib/python3.6/dist-packages/cv2', 'python-3.6')
    ] + PYTHON_EXTENSIONS_PATHS
```

** TODO ADAPT EXAMPLE TO OPENCV 4.1 in C++ ** Verify the installation by compiling and executing the following example:

#include <iostream>
#include <ctime>
#include <cmath>
#include "bits/time.h"

//#include <opencv2/opencv.hpp>
#include <core/core.hpp>
#include <highgui/highgui.hpp>
#include <imgproc/imgproc.hpp>
#include <imgcodecs/imgcodecs.hpp>

#include <core/cuda.hpp>
#include <cudaarithm.hpp>
#include <cudaimgproc.hpp>

#define TestCUDA true

int main()
{
    std::clock_t begin = std::clock();

    try {
        cv::Mat srcHost = cv::imread("image.png");

        for(int i=0; i<1000; i++) {
            if(TestCUDA) {
                cv::cuda::GpuMat dst, src;
                src.upload(srcHost);

                //cv::cuda::threshold(src,dst,128.0,255.0, CV_THRESH_BINARY);
                cv::cuda::bilateralFilter(src,dst,3,1,1);

                cv::Mat resultHost;
                dst.download(resultHost);
            } else {
                cv::Mat dst;
                cv::bilateralFilter(srcHost,dst,3,1,1);
            }
        }

        //cv::imshow("Result",resultHost);
        //cv::waitKey();

    } catch(const cv::Exception& ex) {
        std::cout << "Error: " << ex.what() << std::endl;
    }

    std::clock_t end = std::clock();
    std::cout << double(end-begin) / CLOCKS_PER_SEC  << std::endl;
}

Compile and execute:

$ g++ `pkg-config opencv --cflags --libs` -o test test.cpp
$ ./test

If you have any problem try updating the nvidia drivers.

Source

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