Getting started with open cv in raspberry pi
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OpenCV is an open source computer vision library that can be used for image processing and computer vision. It contains over 500 functions and supports Windows, Linux, and MacOS. The OpenCV library consists of three main modules: CV for computer vision algorithms, HighGUI for GUI and image/video input and output, and CXCore for basic data structures. To use OpenCV, developers need a C/C++ compiler like GCC and dependencies like CMake, Git, and Python. OpenCV can then be installed from source by cloning the GitHub repository, configuring with CMake, and building and installing with Make. Useful OpenCV functions and more information sources are also provided.
![ffmpeg or libav development packages:
libavcodec-dev, libavformat-dev, libswscale-
dev
[optional] libtbb2 libtbb-dev
[optional] libdc1394 2.x
[optional] libjpeg-dev, libpng-dev, libtiff-dev,
libjasper-dev, libdc1394-22-de](https://image.slidesharecdn.com/gettingstartedwithopencvinraspberrypi-140729053757-phpapp01/85/Getting-started-with-open-cv-in-raspberry-pi-6-320.jpg)
![1. #include <cvcore.h>
2. #include <highgui.h>
3. #include <math.h>
4. int main( int argc, char** argv ) {
5. CvPoint center;
6. double scale=-3;
7. IplImage* image = argc==2 ? cvLoadImage(argv[1]) : 0;
8. if(!image) return -1;
9. center = cvPoint(image->width/2,image->height/2);
10. for(int i=0;i<image->height;i++)
11. for(int j=0;j<image->width;j++) {
12. double dx=(double)(j-center.x)/center.x;
13. double dy=(double)(i-center.y)/center.y;
14. double weight=exp((dx*dx+dy*dy)*scale);
15. uchar* ptr = &CV_IMAGE_ELEM(image,uchar,i,j*3);
16. ptr[0] = cvRound(ptr[0]*weight);
17. ptr[1] = cvRound(ptr[1]*weight);
18. ptr[2] = cvRound(ptr[2]*weight); }
19. cvSaveImage( “copy.png”, image );
20. cvNamedWindow( "test", 1 );
21. cvShowImage( "test", image );
22. cvWaitKey();
23. return 0; }](https://image.slidesharecdn.com/gettingstartedwithopencvinraspberrypi-140729053757-phpapp01/85/Getting-started-with-open-cv-in-raspberry-pi-7-320.jpg)
![Create a temporary directory, which we denote as
<cmake_binary_dir>, where you want to put the generated
Makefiles, project filesas well the object files and output binaries.
Enter the <cmake_binary_dir> and type
cmake [<some optional parameters>] <path to the OpenCV source
directory>
For example
cd ~/opencv mkdir release cd release cmake -D
CMAKE_BUILD_TYPE=RELEASE -D
CMAKE_INSTALL_PREFIX=/usr/local ..](https://image.slidesharecdn.com/gettingstartedwithopencvinraspberrypi-140729053757-phpapp01/85/Getting-started-with-open-cv-in-raspberry-pi-11-320.jpg)
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Getting started with open cv in raspberry pi
- 2. OpenCV facts and overall structure First steps Almighty HighGUI Using OpenCV within your program Dynamic structures Save your data Some useful OpenCV tips & tricks Where to get more information
- 3. OpenCV stands for Open Source Computer Vision Library Being developed at Intel since 1999 Written in C/C++; Contains over 500 functions. Available on Windows, Linux and MacOSX. So far is extensively used in many companies and research centers
- 4. CV Image processing and vision algorithms HighGUI GUI, Image and Video I/O CXCORE basic structures and algoritms, XML support, drawing functions
- 5. GCC 4.4.x or later CMake 2.8.7 or higher Git GTK+2.x or higher, including headers (libgtk2.0-dev) pkg-config Python 2.6 or later and Numpy 1.5 or later with developer packages (python-dev, python-numpy)
- 6. ffmpeg or libav development packages: libavcodec-dev, libavformat-dev, libswscale- dev [optional] libtbb2 libtbb-dev [optional] libdc1394 2.x [optional] libjpeg-dev, libpng-dev, libtiff-dev, libjasper-dev, libdc1394-22-de
- 7. 1. #include <cvcore.h> 2. #include <highgui.h> 3. #include <math.h> 4. int main( int argc, char** argv ) { 5. CvPoint center; 6. double scale=-3; 7. IplImage* image = argc==2 ? cvLoadImage(argv[1]) : 0; 8. if(!image) return -1; 9. center = cvPoint(image->width/2,image->height/2); 10. for(int i=0;i<image->height;i++) 11. for(int j=0;j<image->width;j++) { 12. double dx=(double)(j-center.x)/center.x; 13. double dy=(double)(i-center.y)/center.y; 14. double weight=exp((dx*dx+dy*dy)*scale); 15. uchar* ptr = &CV_IMAGE_ELEM(image,uchar,i,j*3); 16. ptr[0] = cvRound(ptr[0]*weight); 17. ptr[1] = cvRound(ptr[1]*weight); 18. ptr[2] = cvRound(ptr[2]*weight); } 19. cvSaveImage( “copy.png”, image ); 20. cvNamedWindow( "test", 1 ); 21. cvShowImage( "test", image ); 22. cvWaitKey(); 23. return 0; }
- 8. Download latest opencv version 2.4.9 Update Sudo apt-get update Sudo apt-get upgrade Install dependencies sudo apt-get -y install build-essential cmake cmake-curses-gui pkg-config etc...
- 9. git clone https://github.com/Itseez/opencv.git Unzip and prepare for build unzip opencv-2.4.8.zip cd opencv-2.4.8 mkdir release cd release ccmake ../
- 10. Press C to configure It will take 6-10 hours press ‘c’ again to configure with your new settings press ‘g’ to generate the Makefile. And finally, build. This will take a long time (about 10 hours!). make sudo make install
- 11. Create a temporary directory, which we denote as <cmake_binary_dir>, where you want to put the generated Makefiles, project filesas well the object files and output binaries. Enter the <cmake_binary_dir> and type cmake [<some optional parameters>] <path to the OpenCV source directory> For example cd ~/opencv mkdir release cd release cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local ..
- 12. make -j8 # -j8 runs 8 jobs in parallel. # Change 8 to number of hardware threads available. sudo make install Enter the created temporary directory (<cmake_binary_dir>) and proceed with: