updated example

modules/dnn/samples/alexnet.cpp

@@ -2,9 +2,45 @@
 #include <opencv2/dnn.hpp>
 #include <opencv2/imgproc.hpp>
 #include <opencv2/highgui.hpp>
+#include <algorithm>
+#include <fstream>
 using namespace cv;
 using namespace cv::dnn;
 
+typedef std::pair<int, double> ClassProb;
+
+ClassProb getMaxClass(Blob &probBlob, int sampleNum = 0)
+{
+    int numClasses = (int)probBlob.total(1);
+    Mat probMat(1, numClasses, CV_32F, probBlob.ptr<float>(sampleNum));
+
+    double prob;
+    Point probLoc;
+    minMaxLoc(probMat, NULL, &prob, NULL, &probLoc);
+
+    return std::make_pair(probLoc.x, prob);
+}
+
+std::vector<String> CLASES_NAMES;
+
+void initClassesNames()
+{
+    std::ifstream fp("ILSVRC2012_synsets.txt");
+    CV_Assert(fp.is_open());
+
+    std::string name;
+    while (!fp.eof())
+    {
+        std::getline(fp, name);
+        CLASES_NAMES.push_back(name);
+    }
+
+    CV_Assert(CLASES_NAMES.size() == 1000);
+
+    fp.close();
+}
+
+
 int main(void)
 {
     Net net;
@@ -13,16 +49,28 @@ int main(void)
         importer->populateNet(net);
     }
 
-    Mat img = imread("alexnet.png");
+    Mat img = imread("zebra.jpg");
     CV_Assert(!img.empty());
-    img.convertTo(img, CV_32F, 1.0 / 255);
+    cvtColor(img, img, COLOR_BGR2RGB);
+    img.convertTo(img, CV_32F);
+    subtract(img, cv::mean(img), img);
     Blob imgBlob(img);
 
     net.setBlob("data", imgBlob);
-
     net.forward();
 
-    Blob res = net.getBlob("prob");
+    Blob probBlob = net.getBlob("prob");
+    ClassProb bc = getMaxClass(probBlob);
+    
+    initClassesNames();
+    std::string className = (bc.first < (int)CLASES_NAMES.size()) ? CLASES_NAMES[bc.first] : "unnamed";
+
+    std::cout << "Best class:";
+    std::cout << " #" << bc.first;
+    std::cout << " (from " << probBlob.total(1) << ")";
+    std::cout << " \"" + className << "\"";
+    std::cout <<  std::endl;
+    std::cout << "Prob: " << bc.second * 100 << "%" << std::endl;
     
     return 0;
 }