Opencv with ffmpeg and cuda support
Opencv with ffmpeg and cuda support
our goal is make opencv cuda support python2, python3 and C++
env:
- Ubuntu 14.04
- OpenCV 3.0.0
- ffmpeg version N-80901-gfebc862
- CUDA tookit 7.5
requirement:
- NVIDIA graphic card(capable with cuda)
- webcam(if you want to develop with opencv)
install dependency
- cuda tookit
sudo dpkg -i cuda-repo-ubuntu1404_7.5-18_amd64.deb
sudo apt-get update
sudo apt-get install cuda
add path to system env variables, and nvidia-352 may not the same as you
it depend on what your graphic card is.
echo '\nexport PATH=/usr/local/cuda-7.5/bin:$PATH\nLD_LIBRARY_PATH="/usr/local/cuda/lib64"\n' >> ~/.bashrc
su -c 'ln -s /usr/lib/nvidia-352/libnvcuvid.so /usr/lib/libnvcuvid.so && ln -s /usr/lib/nvidia-352/libnvcuvid.so.1 /usr/lib/libnvcuvid.so.1'
add to path, that make system can find and use it
add in ``~/.bashrc`
PATH="...:/usr/local/cuda/bin"
LD_LIBRARY_PATH="/usr/local/cuda/lib64"
and reload it
source ~/.bashrc
- install dependency packages
sudo apt-get install build-essential git pkg-config libopencv-dev build-essential checkinstall cmake yasm libtiff4-dev libjpeg-dev libjasper-dev libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev libxine-dev libv4l-dev python-dev python-numpy libtbb-dev libqt4-dev libgtk2.0-dev libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils libjpeg8-dev libpng12-dev
opengl
sudo apt-get install freeglut3 freeglut3-dev libglew1.5 libglew1.5-dev libglu1-mesa libglu1-mesa-dev libgl1-mesa-glx libgl1-mesa-dev -y
FFMPEG
sudo add-apt-repository ppa:mc3man/trusty-media
sudo apt-get update
sudo sudo apt-get install libatlas-base-dev ffmpeg -y
QT5
wget http://download.qt.io/official_releases/qt/5.7/5.7.0/qt-opensource-linux-x64-5.7.0.run
chmod +x qt-opensource-linux-x64-5.7.0.run
./qt-opensource-linux-x64-5.7.0.run
sudo apt-get install build-essential
sudo apt-get install libfontconfig1
sudo apt-get install mesa-common-dev
sudo apt-get install libglu1-mesa-dev -y
- python config
sudo apt-get install python-pip python3-pip
sudo apt-get install python-dev python-numpy
sudo apt-get install python3-dev python3-numpy
sudo pip3 install virtualenv virtualenvwrapper
add below in ~/.bashrc
export VIRTUALENVWRAPPER_PYTHON=/usr/bin/python3
export WORKON_HOME=$HOME/.virtualenvs
source /usr/local/bin/virtualenvwrapper.sh
reload
source ~/.bashrc
mkvirtualenv virtualenv_name
- compile and install opencv
cd && git clone https://github.com/Itseez/opencv.git && cd opencv && git checkout 3.0.0
# extra module
cd && git clone https://github.com/Itseez/opencv_contrib.git && cd opencv_contrib && git checkout 3.0.0
cd && cd opencv && mkdir build
cd build
we are in the build folder, ready to build
cmake -D CMAKE_BUILD_TYPE=RELEASE \
-D CMAKE_INSTALL_PREFIX=/usr/local \
-D INSTALL_C_EXAMPLES=ON \
-D INSTALL_PYTHON_EXAMPLES=ON \
-D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib/modules \
-D WITH_CUDA=ON \
-D ENABLE_FAST_MATH=1 \
-D CUDA_FAST_MATH=1 \
-D WITH_CUBLAS=1 \
-D WITH_TBB=ON \
-D WITH_V4L=ON \
-D WITH_QT=ON \
-D WITH_OPENGL=ON \
-D WITH_IPP=ON \
-D BUILD_NEW_PYTHON_SUPPORT=ON \
-D WITH_NVCUVID=ON \
-D BUILD_EXAMPLES=ON ..
build and install, the -j “with processor core number”, that make the build process faster,
I spend around 15 mins to build undert the enviorments CPU i7-5820
sudo make -j12 install
after installed, we need to add path to system envriorments variable
sudo /bin/bash -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf'
sudo ldconfig
printf '# OpenCV\nPKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig\nexport PKG_CONFIG_PATH\n' >> ~/.bashrc
source ~/.bashrc
compile source code, that use cuda
#include <iostream>
#include "opencv2/opencv_modules.hpp"
#if defined(HAVE_OPENCV_CUDACODEC)
#include <string>
#include <vector>
#include <algorithm>
#include <numeric>
#include <opencv2/core.hpp>
#include <opencv2/core/opengl.hpp>
#include <opencv2/cudacodec.hpp>
#include <opencv2/highgui.hpp>
#include "tick_meter.hpp"
int main(int argc, const char* argv[])
{
if (argc != 2)
return -1;
const std::string fname(argv[1]);
cv::namedWindow("CPU", cv::WINDOW_NORMAL);
cv::namedWindow("GPU", cv::WINDOW_OPENGL);
cv::cuda::setGlDevice();
cv::Mat frame;
cv::VideoCapture reader(fname);
cv::cuda::GpuMat d_frame;
cv::Ptr<cv::cudacodec::VideoReader> d_reader = cv::cudacodec::createVideoReader(fname);
TickMeter tm;
std::vector<double> cpu_times;
std::vector<double> gpu_times;
for (;;)
{
tm.reset(); tm.start();
if (!reader.read(frame))
break;
tm.stop();
cpu_times.push_back(tm.getTimeMilli());
tm.reset(); tm.start();
if (!d_reader->nextFrame(d_frame))
break;
tm.stop();
gpu_times.push_back(tm.getTimeMilli());
cv::imshow("CPU", frame);
cv::imshow("GPU", d_frame);
if (cv::waitKey(3) > 0)
break;
}
if (!cpu_times.empty() && !gpu_times.empty())
{
std::cout << std::endl << "Results:" << std::endl;
std::sort(cpu_times.begin(), cpu_times.end());
std::sort(gpu_times.begin(), gpu_times.end());
double cpu_avg = std::accumulate(cpu_times.begin(), cpu_times.end(), 0.0) / cpu_times.size();
double gpu_avg = std::accumulate(gpu_times.begin(), gpu_times.end(), 0.0) / gpu_times.size();
std::cout << "CPU : Avg : " << cpu_avg << " ms FPS : " << 1000.0 / cpu_avg << std::endl;
std::cout << "GPU : Avg : " << gpu_avg << " ms FPS : " << 1000.0 / gpu_avg << std::endl;
}
return 0;
}
#else
int main()
{
std::cout << "OpenCV was built without CUDA Video decoding support\n" << std::endl;
return 0;
}
#endif
g++ source -o output -L/usr/local/cuda/lib64/ -lcuda -lcudart `pkg-config --cflags --libs opencv`
Note:
this manner is also apply to version3.1,
but I switch to 3.1, occur compiling code with opencv - /usr/bin/ld: cannot find -lippicv
that compile don’t know the path of lib ippicv, so either link or copy to well know path, or add to path
sudo cp /usr/local/share/OpenCV/3rdparty/lib/libippicv.a /usr/local/lib/