OpenCV CMake package version error


I was compiling OpenCV using CMake and it threw up this error:

CMake Warning at cmake/OpenCVPackaging.cmake:23 (message):
  CPACK_PACKAGE_VERSION does not match version provided by version.hpp
Call Stack (most recent call first):
  CMakeLists.txt:1105 (include)


Open cmake/OpenCVPackaging.cmake file and add the version of OpenCV using a line set(OPENCV_VCSVERSION "2.4.13"). Place the line anywhere above the first use of OPENCV_VCSVERSION.

OpenCV CUDA CMake error


I was building OpenCV using CMake and got this error:

CMake Error: The following variables are used in this project, but they are set to NOTFOUND.
Please set them or make sure they are set and tested correctly in the CMake files:


The error was related to CUDA and probably some dependency on the NVIDIA Performance Primitives (NPP) library. Since, I needed neither, I rebuilt OpenCV without CUDA support as described here by setting WITH_CUDA=OFF.

OpenCV IlmImf linker error


I had compiled OpenCV and when I linked my application with OpenCV libraries, I got this error:

undefined reference to `Imf_2_2::globalThreadCount()'


The Imf in the symbol above seems to be from the IlmImf library that is used to read and write OpenEXR images. Since I had no need for OpenEXR, I recompiled OpenCV with the setting WITH_OPENEXR=OFF. Linking with the resulting OpenCV libraries worked fine.

How to show images in split window in OpenCV

A typical scenario in computer vision is to show multiple images in different parts of a single window, like a split window. However, OpenCV can only display a single cv::Mat in a single window using cv::imshow(). So, to achieve what we want, we create a single cv::Mat whose size is equal to the window. We copy our multiple images into this mat at the locations we want and just display the big mat.

(Note that this is far easier than the ROI regions you would need to use with IplImage.)

This sample illustrates showing two 640x480 images side-by-side in a single window:

// 640x480 images
cv::Mat mat_1;
cv::Mat mat_2;

// Create 1280x480 mat for window
cv::Mat win_mat(cv::Size(1280, 480), CV_8UC3);

// Copy small images into big mat
mat_1.copyTo(win_mat(cv::Rect(  0, 0, 640, 480)));
mat_2.copyTo(win_mat(cv::Rect(640, 0, 640, 480)));

// Display big mat
cv::imshow("Images", win_mat);

Tried with: OpenCV 2.4.8 and Ubuntu 14.04

Depth and type of matrix in OpenCV

cv::Mat is the most fundamental datatype used in OpenCV. It can be used to store 2D images with 1-4 channels of data.

When your code receives a cv::Mat from an external library or code, the most common question you have is what is the data type of the elements of this image? There seem to be two methods in the cv::Mat class that answer this: depth() and type().


Depth is the more fundamental of the two queries. It is the data type of each individual element in the image data. It can take one of these 8 values:

#define CV_8U   0
#define CV_8S   1
#define CV_16U  2
#define CV_16S  3
#define CV_32S  4
#define CV_32F  5
#define CV_64F  6
#define CV_USRTYPE1 7

For example, an image with 2 channels of unsigned short data will have depth of CV_16U.


Type combines the data type of the elements along with the number of channels in the image. Since images in OpenCV can have 1-4 channels, it can take one of these 28 values:

#define CV_8UC1 CV_MAKETYPE(CV_8U,1)
#define CV_8UC2 CV_MAKETYPE(CV_8U,2)
#define CV_8UC3 CV_MAKETYPE(CV_8U,3)
#define CV_8UC4 CV_MAKETYPE(CV_8U,4)

#define CV_8SC1 CV_MAKETYPE(CV_8S,1)
#define CV_8SC2 CV_MAKETYPE(CV_8S,2)
#define CV_8SC3 CV_MAKETYPE(CV_8S,3)
#define CV_8SC4 CV_MAKETYPE(CV_8S,4)

#define CV_16UC1 CV_MAKETYPE(CV_16U,1)
#define CV_16UC2 CV_MAKETYPE(CV_16U,2)
#define CV_16UC3 CV_MAKETYPE(CV_16U,3)
#define CV_16UC4 CV_MAKETYPE(CV_16U,4)

#define CV_16SC1 CV_MAKETYPE(CV_16S,1)
#define CV_16SC2 CV_MAKETYPE(CV_16S,2)
#define CV_16SC3 CV_MAKETYPE(CV_16S,3)
#define CV_16SC4 CV_MAKETYPE(CV_16S,4)

#define CV_32SC1 CV_MAKETYPE(CV_32S,1)
#define CV_32SC2 CV_MAKETYPE(CV_32S,2)
#define CV_32SC3 CV_MAKETYPE(CV_32S,3)
#define CV_32SC4 CV_MAKETYPE(CV_32S,4)

#define CV_32FC1 CV_MAKETYPE(CV_32F,1)
#define CV_32FC2 CV_MAKETYPE(CV_32F,2)
#define CV_32FC3 CV_MAKETYPE(CV_32F,3)
#define CV_32FC4 CV_MAKETYPE(CV_32F,4)

#define CV_64FC1 CV_MAKETYPE(CV_64F,1)
#define CV_64FC2 CV_MAKETYPE(CV_64F,2)
#define CV_64FC3 CV_MAKETYPE(CV_64F,3)
#define CV_64FC4 CV_MAKETYPE(CV_64F,4)

For example, an image with 2 channels of unsigned short data will have type of CV_16UC2.

Here are two simple functions that are handy to get the depth and type of image as a string:

Reference: modules/core/include/opencv2/core/hal/interface.h in OpenCV source code

How to rotate point in OpenCV

It is common to use the cv::Point types for points in C++ code that uses OpenCV. Rotating such a point around origin or rotating it around another center point is straightforward. Remember that positive angle is counter-clockwise.

Tried with: OpenCV 2.4.9 and Ubuntu 14.04

Eigenvectors and eigenvalues in OpenCV

There are many libraries for C++ that can be used to compute Eigenvectors and Eigenvalues. However, if you are already using OpenCV in your project, then it can be used to get these values easily by using the PCA class. This class is declared in opencv2/core/core.hpp header file and defined in the modules/core/src/matmul.cpp source file.

Here is an example:

Tried with: OpenCV 2.4.9 and Ubuntu 14.04