added example_22-01

CMakeLists.txt

@@ -79,6 +79,7 @@ add_executable( example_19-04 example_19-04.cpp )
 add_executable( example_20-01 example_20-01.cpp )
 add_executable( example_20-02 example_20-02.cpp )
 add_executable( example_21-01 example_21-01.cpp )
+add_executable( example_22-01 example_22-01.cpp )
 
 # NOW COMPILE SOME ANSWERS TO EXERCISES:
 add_executable( Exercises_5   Exercises_5.cpp   )
@@ -154,6 +155,7 @@ target_link_libraries( example_19-04 ${OpenCV_LIBS} )
 target_link_libraries( example_20-01 ${OpenCV_LIBS} )
 target_link_libraries( example_20-02 ${OpenCV_LIBS} )
 target_link_libraries( example_21-01 ${OpenCV_LIBS} )
+target_link_libraries( example_22-01 ${OpenCV_LIBS} )
 
 # NOW LINK EXERCISES 
 target_link_libraries( Exercises_5 ${OpenCV_LIBS} )

example_22-01.cpp

@@ -0,0 +1,93 @@
+// Example 22-1. Detecting and drawing faces
+
+#include <vector>
+#include <iostream>
+#include <cstdlib>
+#include <fstream>
+#include <opencv2/opencv.hpp>
+#include "opencv2/objdetect.hpp"
+#include <opencv2/core/core.hpp>
+#include <opencv2/highgui/highgui.hpp>
+
+using std::cout;
+using std::cerr;
+using std::vector;
+using std::string;
+
+// Detect and draw detected object boxes on image
+//
+void detectAndDraw(
+        cv::Mat& img,                               // input image
+        cv::Ptr<cv::CascadeClassifier> classifier,  // preloaded classifier
+        double scale = 1.3) {                       // resize image by ...
+    // Just some pretty colors to draw with
+    //
+    enum { BLUE, AQUA, CYAN, GREEN };
+    static cv::Scalar colors[] = {
+        cv::Scalar(0, 0, 255),
+        cv::Scalar(0, 128, 255),
+        cv::Scalar(0, 255, 255),
+        cv::Scalar(0, 255, 0)
+    };
+    // Image preparation:
+    //
+    cv::Mat gray(img.size(), CV_8UC1);
+    cv::Mat small_img(cvSize(cvRound(img.cols / scale),
+        cvRound(img.rows / scale)), CV_8UC1);
+    cv::cvtColor(img, gray, cv::COLOR_BGR2GRAY);
+    cv::resize(gray, small_img, small_img.size(), 0.0, 0.0, cv::INTER_LINEAR);
+    cv::equalizeHist(small_img, small_img);
+    // Detect objects if any
+    //
+    vector<cv::Rect> objects;
+    classifier->detectMultiScale(
+        small_img,                  // input image
+        objects,                    // place for the results
+        1.1,                        // scale factor
+        3,                          // minimum number of neighbors
+        CV_HAAR_DO_CANNY_PRUNING,   // (old format cascades only)
+        cv::Size(30, 30));          // throw away detections smaller than this
+
+    // Loop through to found objects and draw boxes around them
+    //
+
+    int i = 0;
+    for (vector<cv::Rect>::iterator r = objects.begin();
+            r != objects.end(); r++, ++i) {
+        cv::Rect r_ = (*r);
+        r_.x *= scale;
+        r_.y *= scale;
+        r_.width *= scale;
+        r_.height *= scale;
+        cv::rectangle(img, r_, colors[i % 4]);
+    }
+}
+
+int main(int argc, char** argv) {
+    // Program expects at least two arguments:
+    //   - path to image file
+    //   - path to .xml classifier file
+    //
+    if (argc < 3) {
+        cerr << "Error: wrong number of arguments.\n";
+        cerr << "Use:\n" << argv[0] << " <image_file> <xml_classifier_file>\n"
+             << "to run this demo\n\n"
+             << "Example:\n"
+             << argv[0] << " faces.png haarcascade_frontalface_alt.xml\n"
+             << std::endl;
+        exit(1);
+    }
+
+    string image_file_name = string(argv[1]);
+    cv::Mat img = cv::imread(image_file_name, CV_LOAD_IMAGE_COLOR);
+
+    string cascade_file_name = string(argv[2]);
+    cv::Ptr<cv::CascadeClassifier> cascade(new cv::CascadeClassifier(cascade_file_name));
+
+    detectAndDraw(img, cascade);
+
+    cv::imshow("Result", img);
+    cv::waitKey(0);
+
+    return 0;
+}