updated normalization routine in the matchTemplate to avoid division by zero on black images (ticket #798), added test

modules/gpu/include/opencv2/gpu/gpu.hpp

@@ -1180,7 +1180,6 @@ namespace cv
             size_t getBlockHistogramSize() const;
 
             void setSVMDetector(const vector<float>& detector);
-            bool checkDetectorSize() const;
 
             static vector<float> getDefaultPeopleDetector();
             static vector<float> getPeopleDetector_48x96();
@@ -1212,7 +1211,9 @@ namespace cv
         protected:
             void computeBlockHistograms(const GpuMat& img);
             void computeGradient(const GpuMat& img, GpuMat& grad, GpuMat& qangle);
+
             double getWinSigma() const;
+            bool checkDetectorSize() const;
 
             static int numPartsWithin(int size, int part_size, int stride);
             static Size numPartsWithin(Size size, Size part_size, Size stride);

modules/gpu/src/cuda/match_template.cu

@@ -560,7 +560,7 @@ __global__ void matchTemplatePreparedKernel_CCOFF_NORMED_8U(
                 (image_sqsum.ptr(y + h)[x + w] - image_sqsum.ptr(y)[x + w]) -
                 (image_sqsum.ptr(y + h)[x] - image_sqsum.ptr(y)[x]));
         result.ptr(y)[x] = min(1.f, (ccorr - image_sum_ * templ_sum_scale) * 
-                           rsqrtf(templ_sqsum_scale * (image_sqsum_ - weight * image_sum_ * image_sum_)));
+                           rsqrtf(templ_sqsum_scale * (image_sqsum_ - weight * image_sum_ * image_sum_ + 1.f)));
     }
 }
 
@@ -611,7 +611,7 @@ __global__ void matchTemplatePreparedKernel_CCOFF_NORMED_8UC2(
                 (image_sqsum_g.ptr(y + h)[x] - image_sqsum_g.ptr(y)[x]));
         float ccorr = result.ptr(y)[x];
         float rdenom = rsqrtf(templ_sqsum_scale * (image_sqsum_r_ - weight * image_sum_r_ * image_sum_r_ 
-                                                   + image_sqsum_g_ - weight * image_sum_g_ * image_sum_g_));
+                                                   + image_sqsum_g_ - weight * image_sum_g_ * image_sum_g_ + 1.f));
         result.ptr(y)[x] = min(1.f, (ccorr - image_sum_r_ * templ_sum_scale_r
                                      - image_sum_g_ * templ_sum_scale_g) * rdenom);
     }
@@ -680,7 +680,7 @@ __global__ void matchTemplatePreparedKernel_CCOFF_NORMED_8UC3(
         float ccorr = result.ptr(y)[x];
         float rdenom = rsqrtf(templ_sqsum_scale * (image_sqsum_r_ - weight * image_sum_r_ * image_sum_r_ 
                                                    + image_sqsum_g_ - weight * image_sum_g_ * image_sum_g_
-                                                   + image_sqsum_b_ - weight * image_sum_b_ * image_sum_b_));
+                                                   + image_sqsum_b_ - weight * image_sum_b_ * image_sum_b_ + 1.f));
         result.ptr(y)[x] = min(1.f, (ccorr - image_sum_r_ * templ_sum_scale_r
                                      - image_sum_g_ * templ_sum_scale_g
                                      - image_sum_b_ * templ_sum_scale_b) * rdenom);
@@ -763,7 +763,7 @@ __global__ void matchTemplatePreparedKernel_CCOFF_NORMED_8UC4(
         float rdenom = rsqrtf(templ_sqsum_scale * (image_sqsum_r_ - weight * image_sum_r_ * image_sum_r_
                                                    + image_sqsum_g_ - weight * image_sum_g_ * image_sum_g_
                                                    + image_sqsum_b_ - weight * image_sum_b_ * image_sum_b_
-                                                   + image_sqsum_a_ - weight * image_sum_a_ * image_sum_a_));
+                                                   + image_sqsum_a_ - weight * image_sum_a_ * image_sum_a_ + 1.f));
         result.ptr(y)[x] = min(1.f, (ccorr - image_sum_r_ * templ_sum_scale_r
                                      - image_sum_g_ * templ_sum_scale_g
                                      - image_sum_b_ * templ_sum_scale_b
@@ -822,7 +822,7 @@ __global__ void normalizeKernel_8U(
         float image_sqsum_ = (float)(
                 (image_sqsum.ptr(y + h)[(x + w) * cn] - image_sqsum.ptr(y)[(x + w) * cn]) -
                 (image_sqsum.ptr(y + h)[x * cn] - image_sqsum.ptr(y)[x * cn]));
-        result.ptr(y)[x] = min(1.f, result.ptr(y)[x] * rsqrtf(image_sqsum_ * templ_sqsum));
+        result.ptr(y)[x] = min(1.f, result.ptr(y)[x] * rsqrtf((image_sqsum_ + 1.f) * templ_sqsum));
     }
 }
 

tests/gpu/src/match_template.cpp

@@ -124,7 +124,7 @@ struct CV_GpuMatchTemplateTest: CvTest
                     F(t = clock();)
                     gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_CCORR_NORMED);
                     F(cout << "gpu_block: " << clock() - t << endl;)
-                    if (!check(dst_gold, Mat(dst), h * w * 1e-5f)) return;
+                    if (!check(dst_gold, Mat(dst), h * w * 1e-4f)) return;
 
                     gen(image, n, m, CV_8U, cn);
                     gen(templ, h, w, CV_8U, cn);
@@ -146,7 +146,7 @@ struct CV_GpuMatchTemplateTest: CvTest
                     F(t = clock();)
                     gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_CCOEFF_NORMED);
                     F(cout << "gpu_block: " << clock() - t << endl;)
-                    if (!check(dst_gold, Mat(dst), h * w * 1e-6f)) return;
+                    if (!check(dst_gold, Mat(dst), h * w * 1e-4f)) return;
 
                     gen(image, n, m, CV_32F, cn);
                     gen(templ, h, w, CV_32F, cn);
@@ -207,66 +207,70 @@ struct CV_GpuMatchTemplateTest: CvTest
             return false;
         }
 
-        //// Debug check
-        //for (int i = 0; i < a.rows; ++i)
-        //{
-        //    for (int j = 0; j < a.cols; ++j)
-        //    {
-        //        float v1 = a.at<float>(i, j);
-        //        float v2 = b.at<float>(i, j);
-        //        if (fabs(v1 - v2) > max_err)
-        //        {
-        //            ts->printf(CvTS::CONSOLE, "%d %d %f %f\n", i, j, v1, v2);
-        //            cin.get();
-        //        }
-        //    }
-        //}
-
         return true;
     }
-
-    //void match_template_naive_SQDIFF(const Mat& a, const Mat& b, Mat& c)
-    //{
-    //    c.create(a.rows - b.rows + 1, a.cols - b.cols + 1, CV_32F);         
-    //    for (int i = 0; i < c.rows; ++i)
-    //    {
-    //        for (int j = 0; j < c.cols; ++j)
-    //        {
-    //            float delta;
-    //            float sum = 0.f;
-    //            for (int y = 0; y < b.rows; ++y)
-    //            {
-    //                const unsigned char* arow = a.ptr(i + y);
-    //                const unsigned char* brow = b.ptr(y);
-    //                for (int x = 0; x < b.cols; ++x)
-    //                {
-    //                    delta = (float)(arow[j + x] - brow[x]);
-    //                    sum += delta * delta;
-    //                }
-    //            }
-    //            c.at<float>(i, j) = sum;
-    //        }
-    //    }
-    //}
-
-    //void match_template_naive_CCORR(const Mat& a, const Mat& b, Mat& c)
-    //{
-    //    c.create(a.rows - b.rows + 1, a.cols - b.cols + 1, CV_32F);         
-    //    for (int i = 0; i < c.rows; ++i)
-    //    {
-    //        for (int j = 0; j < c.cols; ++j)
-    //        {
-    //            float sum = 0.f;
-    //            for (int y = 0; y < b.rows; ++y)
-    //            {
-    //                const float* arow = a.ptr<float>(i + y);
-    //                const float* brow = b.ptr<float>(y);
-    //                for (int x = 0; x < b.cols; ++x)
-    //                    sum += arow[j + x] * brow[x];
-    //            }
-    //            c.at<float>(i, j) = sum;
-    //        }
-    //    }
-    //}
 } match_template_test;
 
+struct CV_GpuMatchTemplateFindPatternInBlackTest: CvTest 
+{
+    CV_GpuMatchTemplateFindPatternInBlackTest()
+            : CvTest("GPU-MatchTemplateFindPatternInBlackTest", "matchTemplate") {}
+
+    void run(int)
+    {
+        try
+        {
+            Mat image = imread(std::string(ts->get_data_path()) + "matchtemplate/black.jpg");
+            if (image.empty())
+            {
+                ts->printf(CvTS::CONSOLE, "can't open file '%s'", (std::string(ts->get_data_path()) 
+                                                                   + "matchtemplate/black.jpg").c_str());
+                ts->set_failed_test_info(CvTS::FAIL_INVALID_TEST_DATA);
+                return;
+            }
+
+            Mat pattern = imread(std::string(ts->get_data_path()) + "matchtemplate/cat.jpg");
+            if (pattern.empty())
+            {
+                ts->printf(CvTS::CONSOLE, "can't open file '%s'", (std::string(ts->get_data_path()) 
+                                                                   + "matchtemplate/cat.jpg").c_str());
+                ts->set_failed_test_info(CvTS::FAIL_INVALID_TEST_DATA);
+                return;
+            }
+
+            gpu::GpuMat d_image(image);
+            gpu::GpuMat d_pattern(pattern);
+            gpu::GpuMat d_result;
+
+            double maxValue;
+            Point maxLoc;
+            Point maxLocGold(284, 12);
+
+            gpu::matchTemplate(d_image, d_pattern, d_result, CV_TM_CCOEFF_NORMED);
+            gpu::minMaxLoc(d_result, NULL, &maxValue, NULL, &maxLoc );
+            if (maxLoc != maxLocGold)
+            {
+                ts->printf(CvTS::CONSOLE, "bad match (CV_TM_CCOEFF_NORMED): %d %d, must be at: %d %d", 
+                           maxLoc.x, maxLoc.y, maxLocGold.x, maxLocGold.y);
+                ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+                return;
+            }
+
+            gpu::matchTemplate(d_image, d_pattern, d_result, CV_TM_CCORR_NORMED);
+            gpu::minMaxLoc(d_result, NULL, &maxValue, NULL, &maxLoc );
+            if (maxLoc != maxLocGold)
+            {
+                ts->printf(CvTS::CONSOLE, "bad match (CV_TM_CCORR_NORMED): %d %d, must be at: %d %d", 
+                           maxLoc.x, maxLoc.y, maxLocGold.x, maxLocGold.y);
+                ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+                return;
+            }
+        }
+        catch (const Exception& e)
+        {
+            ts->printf(CvTS::CONSOLE, e.what());
+            if (!check_and_treat_gpu_exception(e, ts)) throw;
+            return;
+        }
+    }
+} match_templet_find_bordered_pattern_test;