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1 OpenCV OpenCV Tutorials OpenCV User Guide OpenCV API Reference docs.opencv.org F. Xabier Albizuri

2 OpenCV Tutorials OpenCV Tutorials: Introduction to OpenCV The Core Functionality (core module) Image Processing (imgproc module) High Level GUI and Media (highgui module) Camera calibration and 3D reconstruction (calib3d module) 2D Features framework (feature2d module) Video analysis (video module) Object Detection (objdetect module) Machine Learning (ml module) GPU-Accelerated Computer Vision (gpu module) Additional contributions (contrib module)

3 Introduction to OpenCV Introduction to OpenCV: Installation in Linux / Windows Using OpenCV with gcc and CMake Using OpenCV with Eclipse Introduction to Java Development Introduction into Android Development Common: Load, Display, Load, Modify, Save an Image

4 Introduction: Load and Display an Image #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include <iostream> #include <string> using namespace cv; using namespace std; int main( int argc, char** argv ) { if( argc!= 2) { cout << "Usage: display_image ImageToLoadAndDisplay" << endl; return -1; } Mat image;

5 Introduction: Load and Display an Image } image = imread(argv[1], CV_LOAD_IMAGE_COLOR); // Read the file if(! image.data ) // Check for invalid input { cout << "Could not open or find the image" << endl ; return -1; } namedwindow( "Display window", CV_WINDOW_AUTOSIZE ); // Create a window for display. imshow( "Display window", image ); // Show our image inside it waitkey(0); // Wait for a keystroke in the window return 0;

6 Introduction: Load and Display an Image In OpenCV 2 we have multiple modules. Each one takes care of a different area or approach towards image processing. Before you use any of them you first need to include the header files where the content of each individual module is declared. You ll almost always end up using the: core module, as here are defined the basic building blocks of the library highgui module, as this contains the functions for input and output operations We also include <iostream> to facilitate console line output and input. To avoid data structure and function name conflicts with other libraries, OpenCV has its own namespace: cv.

7 Introduction: Load and Display an Image Now, let s analyze the main function. We start up assuring that we acquire a valid image name argument from the command line. Then create a Mat object that will store the data of the loaded image. Now we call the imread function which loads the image name specified by the first argument. The second argument specifies the format in what we want the image. This may be: CV_LOAD_IMAGE_UNCHANGED (< 0) loads the image as is (including the alpha channel if present) CV_LOAD_IMAGE_GRAYSCALE (0) loads the image as an intensity one CV_LOAD_IMAGE_COLOR (> 0) loads the image in the RGB format

8 Introduction: Load and Display an Image After checking that the image data was loaded correctly (pointer to the data uchar* data), we want to display our image, so we create an OpenCV window using the namedwindow function. You need to specify its name and how it should handle the change of the image it contains from a size point of view. It may be: CV_WINDOW_AUTOSIZE is the only supported one if you do not use the Qt backend. In this case the window size will take up the size of the image it shows. CV_WINDOW_NORMAL on Qt you may use this to allow window resize. The image will resize itself according to the current window size. By using the operator you also need to specify if you would like the image to keep its aspect ratio (CV_WINDOW_KEEPRATIO) or not (CV_WINDOW_FREERATIO).

9 Introduction: Load and Display an Image Finally, to update the content of the OpenCV window with a new image use the imshow function. Specify the OpenCV window name to update and the image to use during this operation. Because we want our window to be displayed until the user presses a key, we use the waitkey function whose only parameter is just how long should it wait for a user input (measured in milliseconds). Zero means to wait forever.

10 Introduction: Modify and Save an Image #include <cv.h> #include <highgui.h> using namespace cv; int main( int argc, char** argv ) { char* imagename = argv[1]; Mat image; image = imread( imagename, 1 ); if( argc!= 2!image.data ) { printf( " No image data \n " ); return -1; }

11 Introduction: Modify and Save an Image Mat gray_image; cvtcolor( image, gray_image, CV_BGR2GRAY ); imwrite( "../../images/gray_image.jpg", gray_image ); namedwindow( imagename, CV_WINDOW_AUTOSIZE ); namedwindow( "Gray image", CV_WINDOW_AUTOSIZE ); imshow( imagename, image ); imshow( "Gray image", gray_image ); waitkey(0); return 0; }

12 Introduction: Modify and Save an Image Now we are going to convert our image from BGR to Grayscale format. OpenCV has the function cvtcolor to convert an image from one color space to another, it takes as arguments: a source image, a destination image, in which we will save the converted image, an additional parameter that indicates what kind of transformation will be performed, in this case we use CV_BGR2GRAY (because of imread has BGR default channel order in case of color images). So now we have our new image and want to save it on disk. To save it, we will use the function imwrite. We create two windows and use them to show the original image as well as the new one.

13 The Core Functionality Tutorials: Mat - The Basic Image Container How to scan images, lookup tables and time measurement with OpenCV Mask operations on matrices Adding (blending) two images using OpenCV Changing the contrast and brightness of an image Basic Drawing Random generator and text with OpenCV Discrete Fourier Transform File Input and Output using XML and YAML files

14 Image Processing Tutorials: Smoothing Images Eroding and Dilating More Morphology Transformations Image Pyramids Basic Thresholding Operations Making your own linear filters Adding borders to your images Sobel Derivatives Laplace Operator Canny Edge Detector Hough Line Transform Hough Circle Transform

15 Image Processing Remapping Affine Transformations Histogram Equalization Histogram Calculation Histogram Comparison Back Projection Template Matching Finding contours in your image Convex Hull Creating Bounding boxes and circles for contours Image Moments Point Polygon Test

16 Additional Tutorials High Level GUI and Media Camera calibration and 3D reconstruction 2D Features framework Video analysis Object Detection Machine Learning GPU-Accelerated Computer Vision Additional contributions

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