add results verification to facedetect and hog samples

samples/ocl/facedetect.cpp

-//This sample is inherited from facedetect.cpp in smaple/c
-
 #include "opencv2/objdetect/objdetect.hpp"
 #include "opencv2/highgui/highgui.hpp"
 #include "opencv2/imgproc/imgproc.hpp"
@@ -9,78 +7,84 @@
 
 using namespace std;
 using namespace cv;
+#define LOOP_NUM 10 
+
+const static Scalar colors[] =  { CV_RGB(0,0,255),
+        CV_RGB(0,128,255),
+        CV_RGB(0,255,255),
+        CV_RGB(0,255,0),
+        CV_RGB(255,128,0),
+        CV_RGB(255,255,0),
+        CV_RGB(255,0,0),
+        CV_RGB(255,0,255)} ;
 
-static void help()
+int64 work_begin = 0;
+int64 work_end = 0;
+
+static void workBegin() 
+{ 
+    work_begin = getTickCount();
+}
+static void workEnd()
 {
-    cout << "\nThis program demonstrates the cascade recognizer.\n"
-        "This classifier can recognize many ~rigid objects, it's most known use is for faces.\n"
-        "Usage:\n"
-        "./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]\n"
-        "   [--scale=<image scale greater or equal to 1, try 1.3 for example>\n"
-        "   [filename|camera_index]\n\n"
-        "see facedetect.cmd for one call:\n"
-        "./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --scale=1.3 \n"
-        "Hit any key to quit.\n"
-        "Using OpenCV version " << CV_VERSION << "\n" << endl;
+    work_end += (getTickCount() - work_begin);
 }
-struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
-void detectAndDraw( Mat& img,
-    cv::ocl::OclCascadeClassifier& cascade, CascadeClassifier& nestedCascade,
-    double scale);
+static double getTime(){
+    return work_end /((double)cvGetTickFrequency() * 1000.);
+}
+
+void detect( Mat& img, vector<Rect>& faces, 
+    cv::ocl::OclCascadeClassifierBuf& cascade, 
+    double scale, bool calTime);
 
-String cascadeName = "../../../data/haarcascades/haarcascade_frontalface_alt.xml";
+void detectCPU( Mat& img, vector<Rect>& faces, 
+    CascadeClassifier& cascade, 
+    double scale, bool calTime);
+
+void Draw(Mat& img, vector<Rect>& faces, double scale);
+
+// This function test if gpu_rst matches cpu_rst.
+// If the two vectors are not equal, it will return the difference in vector size
+// Else if will return (total diff of each cpu and gpu rects covered pixels)/(total cpu rects covered pixels)
+double checkRectSimilarity(Size sz, std::vector<Rect>& cpu_rst, std::vector<Rect>& gpu_rst);
 
 int main( int argc, const char** argv )
 {
-    CvCapture* capture = 0;
-    Mat frame, frameCopy, image;
-    const String scaleOpt = "--scale=";
-    size_t scaleOptLen = scaleOpt.length();
-    const String cascadeOpt = "--cascade=";
-    size_t cascadeOptLen = cascadeOpt.length();
-    String inputName;
-
-    help();
-    cv::ocl::OclCascadeClassifier cascade;
-    CascadeClassifier  nestedCascade;
-    double scale = 1;
-
-    for( int i = 1; i < argc; i++ )
+    const char* keys =
+        "{ h | help       | false       | print help message }"
+        "{ i | input      |             | specify input image }"
+        "{ t | template   | ../../../data/haarcascades/haarcascade_frontalface_alt.xml  | specify template file }"
+        "{ c | scale      |   1.0       | scale image }"
+        "{ s | use_cpu    | false       | use cpu or gpu to process the image }";
+
+    CommandLineParser cmd(argc, argv, keys);
+    if (cmd.get<bool>("help"))
     {
-        cout << "Processing " << i << " " <<  argv[i] << endl;
-        if( cascadeOpt.compare( 0, cascadeOptLen, argv[i], cascadeOptLen ) == 0 )
-        {
-            cascadeName.assign( argv[i] + cascadeOptLen );
-            cout << "  from which we have cascadeName= " << cascadeName << endl;
-        }
-        else if( scaleOpt.compare( 0, scaleOptLen, argv[i], scaleOptLen ) == 0 )
-        {
-            if( !sscanf( argv[i] + scaleOpt.length(), "%lf", &scale ) || scale < 1 )
-                scale = 1;
-            cout << " from which we read scale = " << scale << endl;
-        }
-        else if( argv[i][0] == '-' )
-        {
-            cerr << "WARNING: Unknown option %s" << argv[i] << endl;
-        }
-        else
-            inputName.assign( argv[i] );
+        cout << "Avaible options:" << endl;
+        cmd.printParams();
+        return 0;
     }
+    CvCapture* capture = 0;
+    Mat frame, frameCopy, image;
 
-    if( !cascade.load( cascadeName ) )
+    bool useCPU = cmd.get<bool>("s");
+    string inputName = cmd.get<string>("i");
+    string cascadeName = cmd.get<string>("t");
+    double scale = cmd.get<double>("c");
+    cv::ocl::OclCascadeClassifierBuf cascade;
+    CascadeClassifier  cpu_cascade;
+
+    if( !cascade.load( cascadeName ) || !cpu_cascade.load(cascadeName) )
     {
         cerr << "ERROR: Could not load classifier cascade" << endl;
-        cerr << "Usage: facedetect [--cascade=<cascade_path>]\n"
-            "   [--scale[=<image scale>\n"
-            "   [filename|camera_index]\n" << endl ;
         return -1;
     }
 
-    if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0') )
+    if( inputName.empty() )
     {
-        capture = cvCaptureFromCAM( inputName.empty() ? 0 : inputName.c_str()[0] - '0' );
-        int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;
-        if(!capture) cout << "Capture from CAM " <<  c << " didn't work" << endl;
+        capture = cvCaptureFromCAM(0);
+        if(!capture) 
+            cout << "Capture from CAM 0 didn't work" << endl;
     }
     else if( inputName.size() )
     {
@@ -88,26 +92,30 @@ int main( int argc, const char** argv )
         if( image.empty() )
         {
             capture = cvCaptureFromAVI( inputName.c_str() );
-            if(!capture) cout << "Capture from AVI didn't work" << endl;
+            if(!capture) 
+                cout << "Capture from AVI didn't work" << endl;
+            return -1;
         }
     }
     else
     {
         image = imread( "lena.jpg", 1 );
-        if(image.empty()) cout << "Couldn't read lena.jpg" << endl;
+        if(image.empty()) 
+            cout << "Couldn't read lena.jpg" << endl;
+        return -1;
     }
 
     cvNamedWindow( "result", 1 );
     std::vector<cv::ocl::Info> oclinfo;
     int devnums = cv::ocl::getDevice(oclinfo);
-    if(devnums<1)
+    if( devnums < 1 )
     {
         std::cout << "no device found\n";
         return -1;
     }
     //if you want to use undefault device, set it here
     //setDevice(oclinfo[0]);
-    //setBinpath(CLBINPATH);
+    ocl::setBinpath("./");
     if( capture )
     {
         cout << "In capture ..." << endl;
@@ -115,15 +123,20 @@ int main( int argc, const char** argv )
         {
             IplImage* iplImg = cvQueryFrame( capture );
             frame = iplImg;
+            vector<Rect> faces;
             if( frame.empty() )
                 break;
             if( iplImg->origin == IPL_ORIGIN_TL )
                 frame.copyTo( frameCopy );
             else
                 flip( frame, frameCopy, 0 );
-
-            detectAndDraw( frameCopy, cascade, nestedCascade, scale );
-
+            if(useCPU){
+                detectCPU(frameCopy, faces, cpu_cascade, scale, false);
+            }
+            else{
+                detect(frameCopy, faces, cascade, scale, false);     
+            }
+            Draw(frameCopy, faces, scale);
             if( waitKey( 10 ) >= 0 )
                 goto _cleanup_;
         }
@@ -136,42 +149,34 @@ _cleanup_:
     else
     {
         cout << "In image read" << endl;
-        if( !image.empty() )
-        {
-            detectAndDraw( image, cascade, nestedCascade, scale );
-            waitKey(0);
-        }
-        else if( !inputName.empty() )
+        vector<Rect> faces;
+        vector<Rect> ref_rst;
+        double accuracy = 0.;
+        for(int i = 0; i <= LOOP_NUM;i ++) 
         {
-            /* assume it is a text file containing the
-            list of the image filenames to be processed - one per line */
-            FILE* f = fopen( inputName.c_str(), "rt" );
-            if( f )
+            cout << "loop" << i << endl;
+            if(useCPU){
+                detectCPU(image, faces, cpu_cascade, scale, i==0?false:true);  
+            }
+            else{
+                detect(image, faces, cascade, scale, i==0?false:true);
+                if(i == 0){
+                    detectCPU(image, ref_rst, cpu_cascade, scale, false);
+                    accuracy = checkRectSimilarity(image.size(), ref_rst, faces);
+                }                    
+            }
+            if (i == LOOP_NUM)
             {
-                char buf[1000+1];
-                while( fgets( buf, 1000, f ) )
-                {
-                    int len = (int)strlen(buf), c;
-                    while( len > 0 && isspace(buf[len-1]) )
-                        len--;
-                    buf[len] = '\0';
-                    cout << "file " << buf << endl;
-                    image = imread( buf, 1 );
-                    if( !image.empty() )
-                    {
-                        detectAndDraw( image, cascade, nestedCascade, scale );
-                        c = waitKey(0);
-                        if( c == 27 || c == 'q' || c == 'Q' )
-                            break;
-                    }
-                    else
-                    {
-                        cerr << "Aw snap, couldn't read image " << buf << endl;
-                    }
-                }
-                fclose(f);
+                if (useCPU)
+                    cout << "average CPU time (noCamera) : ";
+                else
+                    cout << "average GPU time (noCamera) : ";
+                cout << getTime() / LOOP_NUM << " ms" << endl;
+                cout << "accuracy value: " << accuracy <<endl;
             }
         }
+        Draw(image, faces, scale);
+        waitKey(0);
     }
 
     cvDestroyWindow("result");
@@ -179,44 +184,44 @@ _cleanup_:
     return 0;
 }
 
-void detectAndDraw( Mat& img,
-    cv::ocl::OclCascadeClassifier& cascade, CascadeClassifier&,
-    double scale)
+void detect( Mat& img, vector<Rect>& faces, 
+    cv::ocl::OclCascadeClassifierBuf& cascade, 
+    double scale, bool calTime)
 {
-    int i = 0;
-    double t = 0;
-    vector<Rect> faces;
-    const static Scalar colors[] =  { CV_RGB(0,0,255),
-        CV_RGB(0,128,255),
-        CV_RGB(0,255,255),
-        CV_RGB(0,255,0),
-        CV_RGB(255,128,0),
-        CV_RGB(255,255,0),
-        CV_RGB(255,0,0),
-        CV_RGB(255,0,255)} ;
     cv::ocl::oclMat image(img);
     cv::ocl::oclMat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
-
+    if(calTime) workBegin();
     cv::ocl::cvtColor( image, gray, CV_BGR2GRAY );
     cv::ocl::resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
     cv::ocl::equalizeHist( smallImg, smallImg );
 
-    CvSeq* _objects;
-    MemStorage storage(cvCreateMemStorage(0));
-    t = (double)cvGetTickCount();
-    _objects = cascade.oclHaarDetectObjects( smallImg, storage, 1.1,
+    cascade.detectMultiScale( smallImg, faces, 1.1,
         3, 0
         |CV_HAAR_SCALE_IMAGE
         , Size(30,30), Size(0, 0) );
-    vector<CvAvgComp> vecAvgComp;
-    Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
-    faces.resize(vecAvgComp.size());
-    std::transform(vecAvgComp.begin(), vecAvgComp.end(), faces.begin(), getRect());
-    t = (double)cvGetTickCount() - t;
-    printf( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) );
+    if(calTime) workEnd();
+}
+
+void detectCPU( Mat& img, vector<Rect>& faces, 
+    CascadeClassifier& cascade, 
+    double scale, bool calTime)
+{
+    if(calTime) workBegin();
+    Mat cpu_gray, cpu_smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
+    cvtColor(img, cpu_gray, CV_BGR2GRAY);
+    resize(cpu_gray, cpu_smallImg, cpu_smallImg.size(), 0, 0, INTER_LINEAR);
+    equalizeHist(cpu_smallImg, cpu_smallImg);
+    cascade.detectMultiScale(cpu_smallImg, faces, 1.1,
+        3, 0 | CV_HAAR_SCALE_IMAGE,
+        Size(30, 30), Size(0, 0));
+    if(calTime) workEnd(); 
+}
+
+void Draw(Mat& img, vector<Rect>& faces, double scale)
+{
+    int i = 0;
     for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
     {
-        Mat smallImgROI;
         Point center;
         Scalar color = colors[i%8];
         int radius;
@@ -227,3 +232,42 @@ void detectAndDraw( Mat& img,
     }
     cv::imshow( "result", img );
 }
+
+double checkRectSimilarity(Size sz, std::vector<Rect>& ob1, std::vector<Rect>& ob2)
+{
+    double final_test_result = 0.0;
+    size_t sz1 = ob1.size();
+    size_t sz2 = ob2.size();
+
+    if(sz1 != sz2)
+        return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
+    else
+    {
+        cv::Mat cpu_result(sz, CV_8UC1);
+        cpu_result.setTo(0);
+
+        for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
+        {      
+            cv::Mat cpu_result_roi(cpu_result, *r);
+            cpu_result_roi.setTo(1);
+            cpu_result.copyTo(cpu_result);
+        }
+        int cpu_area = cv::countNonZero(cpu_result > 0);
+
+        cv::Mat gpu_result(sz, CV_8UC1);
+        gpu_result.setTo(0);
+        for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
+        {
+            cv::Mat gpu_result_roi(gpu_result, *r2);
+            gpu_result_roi.setTo(1);
+            gpu_result.copyTo(gpu_result);
+        }
+
+        cv::Mat result_;
+        multiply(cpu_result, gpu_result, result_);
+        int result = cv::countNonZero(result_ > 0);
+
+        final_test_result = 1.0 - (double)result/(double)cpu_area;
+    }
+    return final_test_result;
+}

samples/ocl/hog.cpp

@@ -45,7 +45,6 @@ public:
     bool gamma_corr;
 };
 
-
 class App
 {
 public:
@@ -64,6 +63,13 @@ public:
 
     string message() const;
 
+// This function test if gpu_rst matches cpu_rst.
+// If the two vectors are not equal, it will return the difference in vector size
+// Else if will return 
+// (total diff of each cpu and gpu rects covered pixels)/(total cpu rects covered pixels)
+    double checkRectSimilarity(Size sz, 
+                               std::vector<Rect>& cpu_rst, 
+                               std::vector<Rect>& gpu_rst);
 private:
     App operator=(App&);
 
@@ -290,6 +296,7 @@ void App::run()
         ocl::oclMat gpu_img;
 
         // Iterate over all frames
+        bool verify = false;
         while (running && !frame.empty())
         {
             workBegin();
@@ -316,7 +323,18 @@ void App::run()
                 gpu_img.upload(img);
                 gpu_hog.detectMultiScale(gpu_img, found, hit_threshold, win_stride,
                                          Size(0, 0), scale, gr_threshold);
-            }
+                if (!verify)
+                {
+                    // verify if GPU output same objects with CPU at 1st run
+                    verify = true;
+                    vector<Rect> ref_rst;
+                    cvtColor(img, img, CV_BGRA2BGR);
+                    cpu_hog.detectMultiScale(img, ref_rst, hit_threshold, win_stride,
+                                              Size(0, 0), scale, gr_threshold-2);
+                    double accuracy = checkRectSimilarity(img.size(), ref_rst, found);
+                    cout << "\naccuracy value: " << accuracy << endl;           
+                } 
+           }
             else cpu_hog.detectMultiScale(img, found, hit_threshold, win_stride,
                                           Size(0, 0), scale, gr_threshold);
             hogWorkEnd();
@@ -457,3 +475,45 @@ inline string App::workFps() const
     return ss.str();
 }
 
+double App::checkRectSimilarity(Size sz, 
+                                std::vector<Rect>& ob1, 
+                                std::vector<Rect>& ob2)
+{
+    double final_test_result = 0.0;
+    size_t sz1 = ob1.size();
+    size_t sz2 = ob2.size();
+
+    if(sz1 != sz2)
+        return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
+    else
+    {
+        cv::Mat cpu_result(sz, CV_8UC1);
+        cpu_result.setTo(0);
+
+        for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
+        {      
+            cv::Mat cpu_result_roi(cpu_result, *r);
+            cpu_result_roi.setTo(1);
+            cpu_result.copyTo(cpu_result);
+        }
+        int cpu_area = cv::countNonZero(cpu_result > 0);
+
+        cv::Mat gpu_result(sz, CV_8UC1);
+        gpu_result.setTo(0);
+        for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
+        {
+            cv::Mat gpu_result_roi(gpu_result, *r2);
+            gpu_result_roi.setTo(1);
+            gpu_result.copyTo(gpu_result);
+        }
+
+        cv::Mat result_;
+        multiply(cpu_result, gpu_result, result_);
+        int result = cv::countNonZero(result_ > 0);
+
+        final_test_result = 1.0 - (double)result/(double)cpu_area;
+    }
+    return final_test_result;
+
+}
+