raulqf/Install_OpenCV3_CUDA9.md

## Install_OpenCV3_CUDA9.md

      
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              Install_OpenCV3_CUDA9.md
            
          
    How to install OpenCV 3.4.1 with CUDA on Ubuntu distro

First of all install update and upgrade your system:
    $ sudo apt-get update
    $ sudo apt-get upgrade

Then, install required libraries:


Developers tools:
  $ sudo apt-get install build-essential cmake pkg-config unzip yasm git gfortran


Image I/O libs
$ sudo apt-get install libjpeg8-dev libtiff5-dev libjasper-dev libpng12-dev


Video Libs - FFMPEG, GSTREAMER, x264 and so on.
$ sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev
$ sudo apt-get install libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev
$ sudo apt-get install libxvidcore-dev x264 libx264-dev libfaac-dev libmp3lame-dev libtheora-dev libvorbis-dev


Cameras programming interface libs
$ sudo apt-get install libdc1394-22 libdc1394-22-dev libxine-dev libv4l-dev v4l-utils


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 python-dev python-pip python3-dev python3-pip
$ sudo -H pip2 install -U pip numpy
$ sudo -H pip3 install -U pip numpy


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).
$ git clone https://github.com/opencv/opencv.git
$ cd opencv 
$ git checkout 3.4.1 
$ cd ..
$ git clone https://github.com/opencv/opencv_contrib.git
$ cd opencv_contrib
$ git checkout 3.4.1
$ cd ..
$ cd opencv
$ mkdir build
$ cd build

$ cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules -D WITH_CUDA=ON -D WITH_TBB=ON -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D WITH_CUBLAS=1 -D WITH_QT=OFF ..

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 WITH_CUDA=ON -D WITH_TBB=ON -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D WITH_CUBLAS=1 -D WITH_QT=OFF -D BUILD_SHARED_LIBS=OFF ..

(In case you do not want to include include CUDA:)
$ cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_CUDA=OFF -D WITH_TBB=ON -D ENABLE_FAST_MATH=1 -D WITH_QT=OFF -D BUILD_SHARED_LIBS=OFF ..

Before the compilation you must check that CUDA has been enabled in the configuration summary printed on the screen.
--   NVIDIA CUDA
--     Use CUFFT:                   YES
--     Use CUBLAS:                  YES
--     USE NVCUVID:                 NO
--     NVIDIA GPU arch:             20 30 35 37 50 52 60 61
--     NVIDIA PTX archs:
--     Use fast math:               YES

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

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

#include <opencv2/core/cuda.hpp>
#include <opencv2/cudaarithm.hpp>
#include <opencv2/cudaimgproc.hpp>

#define TestCUDA true

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

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

        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.
Addendum to compile 3.4.3 with CUDA 9.0 in Ubuntu 18.04

Cuda 9.0 only works with gcc & g++ vesion 6.0 and you likley have 7.0. So, you must install them and create the respective symlinks:
# CUDA 9 requires gcc 6
$ sudo apt install gcc-6
$ sudo apt install g++-6

# set up symlinks for gcc/g++
sudo ln -s /usr/bin/gcc-6 /usr/local/cuda/bin/gcc
sudo ln -s /usr/bin/g++-6 /usr/local/cuda/bin/g++

cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib-3.4.3/modules -D WITH_CUDA=ON -D WITH_TBB=ON -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D WITH_CUBLAS=1 -D PYTHON_EXECUTABLE=~/.virtualenvs/cv/bin/python -D WITH_QT=OFF -D BUILD_EXAMPLES=OFF -D INSTALL_C_EXAMPLES=OFF -D INSTALL_PYTHON_EXAMPLES=OFF -D CUDA_NVCC_FLAGS=--expt-relaxed-constexpr -D CUDA_GENERATION=Maxwell ..

Source


pyimagesearch
rodrigoberriel
https://gist.github.com/bikz05/a8aa07adf89cd5fb89fb
https://gist.github.com/Brainiarc7/470a57e5c9fc9ab9f9c4e042d5941a40