Generate<\/em>. Now you can navigate to the build folder, I’ll do so with cd ~\/opencv-3.0.0\/build\/ <\/i>and run make<\/i> to build OpenCV.<\/p>\n\u00a0\u00a0\u00a0 Installing OpenCV<\/h3>\n
If everything goes well, after the build finishes, run make install <\/i>to add the OpenCV includes to the \/usr\/local\/include <\/i>folder and the libraries to the \/usr\/local\/lib <\/i>and \/usr\/local\/share\/OpenCV\/3rdparty\/lib <\/i>folders.<\/p>\n
After that’s done, you should be able to build your own C++ applications that link against OpenCV.<\/p>\n
\u00a0\u00a0\u00a0 The Face Detector Application<\/h3>\n
Now let’s try to build our first application with OpenCV<\/p>\n
Here’s the code and comments that explain how to do just that :<\/p>\n
#include <iostream>\r\n\r\n\/\/Include OpenCV\r\n#include <opencv2\/opencv.hpp>\r\n\r\nint main(void )\r\n{\r\n \/\/Capture stream from webcam.\r\n cv::VideoCapture capture(0);\r\n\r\n \/\/Check if we can get the webcam stream.\r\n if(!capture.isOpened())\r\n {\r\n std::cout << \"Could not open camera\" << std::endl;\r\n return -1;\r\n }\r\n\r\n \/\/OpenCV saves detection rules as something called a CascadeClassifier which\r\n \/\/ can be used to detect objects in images.\r\n cv::CascadeClassifier faceCascade;\r\n\r\n \/\/We'll load the lbpcascade_frontalface.xml containing the rules to detect faces.\r\n \/\/The file should be right next to the binary.\r\n if(!faceCascade.load(\"lbpcascade_frontalface.xml\"))\r\n {\r\n std::cout << \"Failed to load cascade classifier\" << std::endl;\r\n return -1;\r\n }\r\n\r\n while (true)\r\n {\r\n \/\/This variable will hold the image from the camera.\r\n cv::Mat cameraFrame;\r\n\r\n \/\/Read an image from the camera.\r\n capture.read(cameraFrame);\r\n\r\n \/\/This vector will hold the rectangle coordinates to a detection inside the image.\r\n std::vector<cv::Rect> faces;\r\n\r\n \/\/This function detects the faces in the image and\r\n \/\/ places the rectangles of the faces in the vector.\r\n \/\/See the detectMultiScale() documentation for more details\r\n \/\/ about the rest of the parameters.\r\n faceCascade.detectMultiScale(\r\n cameraFrame, \r\n faces, \r\n 1.09, \r\n 3,\r\n 0 | CV_HAAR_SCALE_IMAGE,\r\n cv::Size(30, 30));\r\n\r\n \/\/Here we draw the rectangles onto the image with a red border of thikness 2.\r\n for( size_t i = 0; i < faces.size(); i++ )\r\n cv::rectangle(cameraFrame, faces[i], cv::Scalar(0, 0, 255), 2);\r\n\r\n \/\/Here we show the drawn image in a named window called \"output\".\r\n cv::imshow(\"output\", cameraFrame);\r\n\r\n \/\/Waits 50 miliseconds for key press, returns -1 if no key is pressed during that time\r\n if (cv::waitKey(50) >= 0)\r\n break;\r\n }\r\n\r\n return 0;\r\n}<\/pre>\n <\/p>\n
I saved this as main.cpp<\/i>. To build it I used the following command :<\/p>\ng++ -o main main.cpp -I\/usr\/local\/include \\\r\n-L\/usr\/local\/lib -lopencv_core -lopencv_imgproc -lopencv_objdetect \\\r\n-lopencv_imgcodecs -lopencv_highgui -lopencv_hal -lopencv_videoio \\\r\n-L\/usr\/local\/share\/OpenCV\/3rdparty\/lib -llibpng -llibjpeg -llibwebp \\\r\n-llibtiff -lzlib -lIlmImf -llibjasper -framework AVFoundation -framework QuartzCore \\\r\n-framework CoreMedia -framework Cocoa -framework QTKit<\/pre>\nHopefully, no errors should occur.<\/p>\n
\u00a0\u00a0\u00a0 Conclusions<\/h3>\n
Build a Face Detector on OS X Using OpenCV and C? Before running the application, you have to copy the lbpcascade_frontalface.xml <\/i>next to the main<\/i> file. \u00a0You can find this file in the OpenCV source folder under \/data\/lbpcascades\/<\/i>. You can also find some other cascades to detect eyes, cat faces, etc.<\/p>\n
Now just run the .\/main<\/i> and enjoy!<\/p>\n","protected":false},"excerpt":{"rendered":"
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