fixed brocken tests by classifier loger from r9027

modules/gpu/src/cascadeclassifier.cpp

@@ -97,13 +97,15 @@ void cv::gpu::CascadeClassifier_GPU_LBP::allocateBuffers(cv::Size frame)
         Ncv32u bufSize;
         ncvSafeCall( nppiStIntegralGetSize_8u32u(roiSize, &bufSize, prop) );
         integralBuffer.create(1, bufSize, CV_8UC1);
-    }
 
-    candidates.create(1 , frame.width >> 1, CV_32SC4);
+        candidates.create(1 , frame.width >> 1, CV_32SC4);
+    }
 }
 
-bool cv::gpu::CascadeClassifier_GPU_LBP::empty() const { return stage_mat.empty(); }
-Size cv::gpu::CascadeClassifier_GPU_LBP::getClassifierSize() const { return NxM; }
+bool cv::gpu::CascadeClassifier_GPU_LBP::empty() const
+{
+    return stage_mat.empty();
+}
 
 bool cv::gpu::CascadeClassifier_GPU_LBP::load(const string& classifierAsXml)
 {
@@ -301,7 +303,6 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp
     else
         objects.create(1 , image.cols >> 4, CV_32SC4);
 
-    // GpuMat candidates(1 , defaultObjSearchNum, CV_32SC4);
     // used for debug
     // candidates.setTo(cv::Scalar::all(0));
     // objects.setTo(cv::Scalar::all(0));
@@ -314,7 +315,6 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp
     GpuMat dclassified(1, 1, CV_32S);
     cudaSafeCall( cudaMemcpy(dclassified.ptr(), &classified, sizeof(int), cudaMemcpyHostToDevice) );
 
-    //int step = 2;
     // cv::gpu::device::lbp::bindIntegral(integral);
 
     Size scaledImageSize(image.cols, image.rows);

modules/gpu/test/test_objdetect.cpp

@@ -357,14 +357,18 @@ TEST_P(LBP_classify, Accuracy)
     {
         cv::Rect r = faces[i];
 
+#if defined (LOG_CASCADE_STATISTIC)
 		std::cout << r.x << " " << r.y  << " " << r.width << " " << r.height << std::endl;
+#endif
         cv::rectangle(markedImage, r , CV_RGB(255, 0, 0));
     }
 
+#if defined (LOG_CASCADE_STATISTIC)
 	cv::imshow("Res", markedImage); cv::waitKey();
+#endif
 }
 
-INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_classify, 
+INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_classify,
 						testing::Combine(ALL_DEVICES, testing::Values<int>(0)));
 
 } // namespace

modules/objdetect/src/cascadedetect.cpp

@@ -49,64 +49,64 @@
 
 struct Logger
 {
-	enum { STADIES_NUM = 20 };
+    enum { STADIES_NUM = 20 };
 
-	int gid;	
-	cv::Mat mask;
-	cv::Size sz0;
-	int step;
-	
+    int gid;
+    cv::Mat mask;
+    cv::Size sz0;
+    int step;
 
-	Logger() : gid (0), step(2) {}
-	void setImage(const cv::Mat& image) 
-	{   
+
+    Logger() : gid (0), step(2) {}
+    void setImage(const cv::Mat& image)
+    {
      if (gid == 0)
-		 sz0 = image.size();
-
-	  mask.create(image.rows, image.cols * (STADIES_NUM + 1) + STADIES_NUM, CV_8UC1);
-	  mask = cv::Scalar(0);
-	  cv::Mat roi = mask(cv::Rect(cv::Point(0,0), image.size()));
-	  image.copyTo(roi);
-
-	  printf("%d) Size = (%d, %d)\n", gid, image.cols, image.rows);
-
-	  for(int i = 0; i < STADIES_NUM; ++i)
-	  {
-		  int x = image.cols + i * (image.cols + 1);
-		  cv::line(mask, cv::Point(x, 0), cv::Point(x, mask.rows-1), cv::Scalar(255));
-	  }
-
-	  if (sz0.width/image.cols > 2 && sz0.height/image.rows > 2)
-		  step = 1;
-	}
-
-	void setPoint(const cv::Point& p, int passed_stadies)		
-	{
-		int cols = mask.cols / (STADIES_NUM + 1);
-
-		passed_stadies = -passed_stadies;
-		passed_stadies = (passed_stadies == -1) ? STADIES_NUM : passed_stadies;
-		
-		unsigned char* ptr = mask.ptr<unsigned char>(p.y) + cols + 1 + p.x;
-		for(int i = 0; i < passed_stadies; ++i, ptr += cols + 1)
-		{
-			*ptr = 255;
-
-			if (step == 2)
-			{
-				ptr[1] = 255;
-				ptr[mask.step] = 255;
-				ptr[mask.step + 1] = 255;
-			}
-		}
-	};
-
-	void write()
-	{		
-		char buf[4096];
-		sprintf(buf, "%04d.png", gid++);
-		cv::imwrite(buf, mask);
-	}
+         sz0 = image.size();
+
+      mask.create(image.rows, image.cols * (STADIES_NUM + 1) + STADIES_NUM, CV_8UC1);
+      mask = cv::Scalar(0);
+      cv::Mat roi = mask(cv::Rect(cv::Point(0,0), image.size()));
+      image.copyTo(roi);
+
+      printf("%d) Size = (%d, %d)\n", gid, image.cols, image.rows);
+
+      for(int i = 0; i < STADIES_NUM; ++i)
+      {
+          int x = image.cols + i * (image.cols + 1);
+          cv::line(mask, cv::Point(x, 0), cv::Point(x, mask.rows-1), cv::Scalar(255));
+      }
+
+      if (sz0.width/image.cols > 2 && sz0.height/image.rows > 2)
+          step = 1;
+    }
+
+    void setPoint(const cv::Point& p, int passed_stadies)
+    {
+        int cols = mask.cols / (STADIES_NUM + 1);
+
+        passed_stadies = -passed_stadies;
+        passed_stadies = (passed_stadies == -1) ? STADIES_NUM : passed_stadies;
+
+        unsigned char* ptr = mask.ptr<unsigned char>(p.y) + cols + 1 + p.x;
+        for(int i = 0; i < passed_stadies; ++i, ptr += cols + 1)
+        {
+            *ptr = 255;
+
+            if (step == 2)
+            {
+                ptr[1] = 255;
+                ptr[mask.step] = 255;
+                ptr[mask.step + 1] = 255;
+            }
+        }
+    };
+
+    void write()
+    {
+        char buf[4096];
+        sprintf(buf, "%04d.png", gid++);
+        cv::imwrite(buf, mask);
+    }
 
 } logger;
 
@@ -978,7 +978,10 @@ struct CascadeClassifierInvoker
                 double gypWeight;
                 int result = classifier->runAt(evaluator, Point(x, y), gypWeight);
 
-				logger.setPoint(Point(x, y), result);
+#if defined (LOG_CASCADE_STATISTIC)
+
+                logger.setPoint(Point(x, y), result);
+#endif
                 if( rejectLevels )
                 {
                     if( result == 1 )
@@ -1019,8 +1022,9 @@ bool CascadeClassifier::detectSingleScale( const Mat& image, int stripCount, Siz
     if( !featureEvaluator->setImage( image, data.origWinSize ) )
         return false;
 
+#if defined (LOG_CASCADE_STATISTIC)
     logger.setImage(image);
-	
+#endif
 
     Mat currentMask;
     if (!maskGenerator.empty()) {
@@ -1044,8 +1048,11 @@ bool CascadeClassifier::detectSingleScale( const Mat& image, int stripCount, Siz
     }
     candidates.insert( candidates.end(), concurrentCandidates.begin(), concurrentCandidates.end() );
 
-	logger.write();
-    return true;	
+#if defined (LOG_CASCADE_STATISTIC)
+    logger.write();
+#endif
+
+    return true;
 }
 
 bool CascadeClassifier::isOldFormatCascade() const