OpenCV 3.0 was released recently, and you might be thinking of upgrading your code base. OpenCV 2 code will most likely not compile with OpenCV 3 because the new version is not backwardly compatible. So you need a mechanism to make sure your code is compatible with both OpenCV 3 and OpenCV 2. This post explains how to detect the version of OpenCV inside your code. Example C++ and Python code is shown below.
How to Detect OpenCV Version in Python
Everything is easy in Python. cv2.__version__ gives you the version string. You can extract major and minor version from it as shown in the example below.
import cv2 # Print version string print "OpenCV version : {0}".format(cv2.__version__) # Extract major, minor, and subminor version numbers (major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.') print "Major version : {0}".format(major_ver) print "Minor version : {0}".format(minor_ver) print "Submior version : {0}".format(subminor_ver) if int(major_ver) < 3 : ''' Old OpenCV 2 code goes here ''' else : ''' New OpenCV 3 code goes here ''' How to Detect OpenCV Version in C++
In C++ several macros are defined to easily detect the version — CV_VERSION, CV_MAJOR_VERSION, CV_MINOR_VERSION, CV_SUBMINOR_VERSION. See the sample code below as an example.
#include "opencv2/opencv.hpp" using namespace cv; using namespace std; int main( int argc, char** argv ) { cout << "OpenCV version : " << CV_VERSION << endl; cout << "Major version : " << CV_MAJOR_VERSION << endl; cout << "Minor version : " << CV_MINOR_VERSION << endl; cout << "Subminor version : " << CV_SUBMINOR_VERSION << endl; if ( CV_MAJOR_VERSION < 3) { // Old OpenCV 2 code goes here. } else { // New OpenCV 3 code goes here. } } You can see another example at my post about Blob Detector.
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