fixed unused warnings

modules/gpu/perf/perf_core.cpp

@@ -1607,6 +1607,7 @@ GPU_PERF_TEST(Norm, cv::gpu::DeviceInfo, cv::Size, MatDepth, NormType)
     {
         dst = cv::gpu::norm(src, normType, buf);
     }
+    (void)dst;
 }
 
 INSTANTIATE_TEST_CASE_P(Core, Norm, testing::Combine(
@@ -1642,6 +1643,7 @@ GPU_PERF_TEST(NormDiff, cv::gpu::DeviceInfo, cv::Size, NormType)
     {
         dst = cv::gpu::norm(src1, src2, normType);
     }
+    (void)dst;
 }
 
 INSTANTIATE_TEST_CASE_P(Core, NormDiff, testing::Combine(
@@ -1829,6 +1831,7 @@ GPU_PERF_TEST(CountNonZero, cv::gpu::DeviceInfo, cv::Size, MatDepth)
     {
         dst = cv::gpu::countNonZero(src, buf);
     }
+    (void)dst;
 }
 
 INSTANTIATE_TEST_CASE_P(Core, CountNonZero, testing::Combine(

modules/gpu/perf_cpu/perf_core.cpp

@@ -1229,6 +1229,7 @@ GPU_PERF_TEST(Norm, cv::gpu::DeviceInfo, cv::Size, MatDepth, NormType)
     {
         dst = cv::norm(src, normType);
     }
+    (void)dst;
 }
 
 INSTANTIATE_TEST_CASE_P(Core, Norm, testing::Combine(
@@ -1259,6 +1260,7 @@ GPU_PERF_TEST(NormDiff, cv::gpu::DeviceInfo, cv::Size, NormType)
     {
         dst = cv::norm(src1, src2, normType);
     }
+    (void)dst;
 }
 
 INSTANTIATE_TEST_CASE_P(Core, NormDiff, testing::Combine(
@@ -1338,6 +1340,7 @@ GPU_PERF_TEST(CountNonZero, cv::gpu::DeviceInfo, cv::Size, MatDepth)
     {
         dst = cv::countNonZero(src);
     }
+    (void)dst;
 }
 
 INSTANTIATE_TEST_CASE_P(Core, CountNonZero, testing::Combine(

modules/gpu/src/calib3d.cpp

@@ -56,14 +56,14 @@ void cv::gpu::solvePnPRansac(const Mat&, const Mat&, const Mat&, const Mat&, Mat
 
 #else
 
-namespace cv { namespace gpu { namespace device 
+namespace cv { namespace gpu { namespace device
 {
-    namespace transform_points 
+    namespace transform_points
     {
         void call(const DevMem2D_<float3> src, const float* rot, const float* transl, DevMem2D_<float3> dst, cudaStream_t stream);
     }
 
-    namespace project_points 
+    namespace project_points
     {
         void call(const DevMem2D_<float3> src, const float* rot, const float* transl, const float* proj, DevMem2D_<float2> dst, cudaStream_t stream);
     }
@@ -154,11 +154,11 @@ namespace
     class TransformHypothesesGenerator
     {
     public:
-        TransformHypothesesGenerator(const Mat& object_, const Mat& image_, const Mat& dist_coef_, 
-                                     const Mat& camera_mat_, int num_points_, int subset_size_, 
+        TransformHypothesesGenerator(const Mat& object_, const Mat& image_, const Mat& dist_coef_,
+                                     const Mat& camera_mat_, int num_points_, int subset_size_,
                                      Mat rot_matrices_, Mat transl_vectors_)
-                : object(&object_), image(&image_), dist_coef(&dist_coef_), camera_mat(&camera_mat_), 
-                  num_points(num_points_), subset_size(subset_size_), rot_matrices(rot_matrices_), 
+                : object(&object_), image(&image_), dist_coef(&dist_coef_), camera_mat(&camera_mat_),
+                  num_points(num_points_), subset_size(subset_size_), rot_matrices(rot_matrices_),
                   transl_vectors(transl_vectors_) {}
 
         void operator()(const BlockedRange& range) const
@@ -211,9 +211,10 @@ namespace
 
 void cv::gpu::solvePnPRansac(const Mat& object, const Mat& image, const Mat& camera_mat,
                              const Mat& dist_coef, Mat& rvec, Mat& tvec, bool use_extrinsic_guess,
-                             int num_iters, float max_dist, int min_inlier_count, 
+                             int num_iters, float max_dist, int min_inlier_count,
                              vector<int>* inliers)
 {
+    (void)min_inlier_count;
     CV_Assert(object.rows == 1 && object.cols > 0 && object.type() == CV_32FC3);
     CV_Assert(image.rows == 1 && image.cols > 0 && image.type() == CV_32FC2);
     CV_Assert(object.cols == image.cols);
@@ -236,7 +237,7 @@ void cv::gpu::solvePnPRansac(const Mat& object, const Mat& image, const Mat& cam
     Mat transl_vectors(1, num_iters * 3, CV_32F);
 
     // Generate set of hypotheses using small subsets of the input data
-    TransformHypothesesGenerator body(object, image_normalized, empty_dist_coef, eye_camera_mat, 
+    TransformHypothesesGenerator body(object, image_normalized, empty_dist_coef, eye_camera_mat,
                                       num_points, subset_size, rot_matrices, transl_vectors);
     parallel_for(BlockedRange(0, num_iters), body);
 
@@ -246,7 +247,7 @@ void cv::gpu::solvePnPRansac(const Mat& object, const Mat& image, const Mat& cam
     GpuMat d_hypothesis_scores(1, num_iters, CV_32S);
     solve_pnp_ransac::computeHypothesisScores(
             num_iters, num_points, rot_matrices.ptr<float>(), transl_vectors.ptr<float3>(),
-            d_object.ptr<float3>(), d_image_normalized.ptr<float2>(), max_dist * max_dist, 
+            d_object.ptr<float3>(), d_image_normalized.ptr<float2>(), max_dist * max_dist,
             d_hypothesis_scores.ptr<int>());
 
     // Find the best hypothesis index

modules/gpu/src/cascadeclassifier.cpp

@@ -143,7 +143,7 @@ public:
     }
 
     unsigned int process(const GpuMat& image, GpuMat& objectsBuf, float scaleFactor, int minNeighbors,
-                      bool findLargestObject, bool visualizeInPlace, cv::Size minSize, cv::Size maxObjectSize)
+                      bool findLargestObject, bool visualizeInPlace, cv::Size minSize, cv::Size /*maxObjectSize*/)
     {
         CV_Assert( scaleFactor > 1 && image.depth() == CV_8U);
 
@@ -380,12 +380,12 @@ public:
     LbpCascade(){}
     virtual ~LbpCascade(){}
 
-    virtual unsigned int process(const GpuMat& image, GpuMat& objects, float scaleFactor, int groupThreshold, bool findLargestObject,
-        bool visualizeInPlace, cv::Size minObjectSize, cv::Size maxObjectSize)
+    virtual unsigned int process(const GpuMat& image, GpuMat& objects, float scaleFactor, int groupThreshold, bool /*findLargestObject*/,
+        bool /*visualizeInPlace*/, cv::Size minObjectSize, cv::Size maxObjectSize)
     {
         CV_Assert(scaleFactor > 1 && image.depth() == CV_8U);
 
-        const int defaultObjSearchNum = 100;
+        // const int defaultObjSearchNum = 100;
         const float grouping_eps = 0.2f;
 
         if( !objects.empty() && objects.depth() == CV_32S)

modules/gpu/src/match_template.cpp

@@ -52,9 +52,9 @@ void cv::gpu::matchTemplate(const GpuMat&, const GpuMat&, GpuMat&, int, Stream&)
 
 #else
 
-namespace cv { namespace gpu { namespace device 
+namespace cv { namespace gpu { namespace device
 {
-    namespace match_template 
+    namespace match_template
     {
         void matchTemplateNaive_CCORR_8U(const DevMem2Db image, const DevMem2Db templ, DevMem2Df result, int cn, cudaStream_t stream);
         void matchTemplateNaive_CCORR_32F(const DevMem2Db image, const DevMem2Db templ, DevMem2Df result, int cn, cudaStream_t stream);
@@ -71,47 +71,47 @@ namespace cv { namespace gpu { namespace device
         void matchTemplatePrepared_CCOFF_8U(int w, int h, const DevMem2D_<unsigned int> image_sum, unsigned int templ_sum, DevMem2Df result, cudaStream_t stream);
         void matchTemplatePrepared_CCOFF_8UC2(
             int w, int h,
-            const DevMem2D_<unsigned int> image_sum_r, 
-            const DevMem2D_<unsigned int> image_sum_g, 
+            const DevMem2D_<unsigned int> image_sum_r,
+            const DevMem2D_<unsigned int> image_sum_g,
             unsigned int templ_sum_r,
-            unsigned int templ_sum_g, 
+            unsigned int templ_sum_g,
             DevMem2Df result, cudaStream_t stream);
         void matchTemplatePrepared_CCOFF_8UC3(
-                int w, int h, 
-                const DevMem2D_<unsigned int> image_sum_r, 
+                int w, int h,
+                const DevMem2D_<unsigned int> image_sum_r,
                 const DevMem2D_<unsigned int> image_sum_g,
                 const DevMem2D_<unsigned int> image_sum_b,
-                unsigned int templ_sum_r, 
-                unsigned int templ_sum_g, 
-                unsigned int templ_sum_b, 
+                unsigned int templ_sum_r,
+                unsigned int templ_sum_g,
+                unsigned int templ_sum_b,
                 DevMem2Df result, cudaStream_t stream);
         void matchTemplatePrepared_CCOFF_8UC4(
-                int w, int h, 
-                const DevMem2D_<unsigned int> image_sum_r, 
+                int w, int h,
+                const DevMem2D_<unsigned int> image_sum_r,
                 const DevMem2D_<unsigned int> image_sum_g,
                 const DevMem2D_<unsigned int> image_sum_b,
                 const DevMem2D_<unsigned int> image_sum_a,
-                unsigned int templ_sum_r, 
-                unsigned int templ_sum_g, 
-                unsigned int templ_sum_b, 
-                unsigned int templ_sum_a, 
+                unsigned int templ_sum_r,
+                unsigned int templ_sum_g,
+                unsigned int templ_sum_b,
+                unsigned int templ_sum_a,
                 DevMem2Df result, cudaStream_t stream);
 
 
         void matchTemplatePrepared_CCOFF_NORMED_8U(
-                int w, int h, const DevMem2D_<unsigned int> image_sum, 
+                int w, int h, const DevMem2D_<unsigned int> image_sum,
                 const DevMem2D_<unsigned long long> image_sqsum,
                 unsigned int templ_sum, unsigned long long templ_sqsum,
                 DevMem2Df result, cudaStream_t stream);
         void matchTemplatePrepared_CCOFF_NORMED_8UC2(
-                int w, int h, 
+                int w, int h,
                 const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
                 const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
                 unsigned int templ_sum_r, unsigned long long templ_sqsum_r,
                 unsigned int templ_sum_g, unsigned long long templ_sqsum_g,
                 DevMem2Df result, cudaStream_t stream);
         void matchTemplatePrepared_CCOFF_NORMED_8UC3(
-                int w, int h, 
+                int w, int h,
                 const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
                 const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
                 const DevMem2D_<unsigned int> image_sum_b, const DevMem2D_<unsigned long long> image_sqsum_b,
@@ -120,7 +120,7 @@ namespace cv { namespace gpu { namespace device
                 unsigned int templ_sum_b, unsigned long long templ_sqsum_b,
                 DevMem2Df result, cudaStream_t stream);
         void matchTemplatePrepared_CCOFF_NORMED_8UC4(
-                int w, int h, 
+                int w, int h,
                 const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
                 const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
                 const DevMem2D_<unsigned int> image_sum_b, const DevMem2D_<unsigned long long> image_sqsum_b,
@@ -131,7 +131,7 @@ namespace cv { namespace gpu { namespace device
                 unsigned int templ_sum_a, unsigned long long templ_sqsum_a,
                 DevMem2Df result, cudaStream_t stream);
 
-        void normalize_8U(int w, int h, const DevMem2D_<unsigned long long> image_sqsum, 
+        void normalize_8U(int w, int h, const DevMem2D_<unsigned long long> image_sqsum,
                           unsigned long long templ_sqsum, DevMem2Df result, int cn, cudaStream_t stream);
 
         void extractFirstChannel_32F(const DevMem2Db image, DevMem2Df result, int cn, cudaStream_t stream);
@@ -140,17 +140,17 @@ namespace cv { namespace gpu { namespace device
 
 using namespace ::cv::gpu::device::match_template;
 
-namespace 
+namespace
 {
 
-    // Evaluates optimal template's area threshold. If 
-    // template's area is less  than the threshold, we use naive match 
+    // Evaluates optimal template's area threshold. If
+    // template's area is less  than the threshold, we use naive match
     // template version, otherwise FFT-based (if available)
     int getTemplateThreshold(int method, int depth)
     {
         switch (method)
         {
-        case CV_TM_CCORR: 
+        case CV_TM_CCORR:
             if (depth == CV_32F) return 250;
             if (depth == CV_8U) return 300;
             break;
@@ -162,10 +162,10 @@ namespace
         return 0;
     }
 
-    
+
     void matchTemplate_CCORR_32F(
             const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
-    {        
+    {
         result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
         if (templ.size().area() < getTemplateThreshold(CV_TM_CCORR, CV_32F))
         {
@@ -223,10 +223,11 @@ namespace
         normalize_8U(templ.cols, templ.rows, buf.image_sqsums[0], templ_sqsum, result, image.channels(), StreamAccessor::getStream(stream));
     }
 
-    
+
     void matchTemplate_SQDIFF_32F(
             const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
     {
+        (void)buf;
         result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
         matchTemplateNaive_SQDIFF_32F(image, templ, result, image.channels(), StreamAccessor::getStream(stream));
     }
@@ -362,7 +363,7 @@ namespace
             {
             case 2:
                 matchTemplatePrepared_CCOFF_NORMED_8UC2(
-                        templ.cols, templ.rows, 
+                        templ.cols, templ.rows,
                         buf.image_sums[0], buf.image_sqsums[0],
                         buf.image_sums[1], buf.image_sqsums[1],
                         (unsigned int)templ_sum[0], (unsigned long long)templ_sqsum[0],
@@ -371,7 +372,7 @@ namespace
                 break;
             case 3:
                 matchTemplatePrepared_CCOFF_NORMED_8UC3(
-                        templ.cols, templ.rows, 
+                        templ.cols, templ.rows,
                         buf.image_sums[0], buf.image_sqsums[0],
                         buf.image_sums[1], buf.image_sqsums[1],
                         buf.image_sums[2], buf.image_sqsums[2],
@@ -382,7 +383,7 @@ namespace
                 break;
             case 4:
                 matchTemplatePrepared_CCOFF_NORMED_8UC4(
-                        templ.cols, templ.rows, 
+                        templ.cols, templ.rows,
                         buf.image_sums[0], buf.image_sqsums[0],
                         buf.image_sums[1], buf.image_sqsums[1],
                         buf.image_sums[2], buf.image_sqsums[2],
@@ -391,7 +392,7 @@ namespace
                         (unsigned int)templ_sum[1], (unsigned long long)templ_sqsum[1],
                         (unsigned int)templ_sum[2], (unsigned long long)templ_sqsum[2],
                         (unsigned int)templ_sum[3], (unsigned long long)templ_sqsum[3],
-                        result, StreamAccessor::getStream(stream));                
+                        result, StreamAccessor::getStream(stream));
                 break;
             default:
                 CV_Error(CV_StsBadArg, "matchTemplate: unsupported number of channels");

modules/gpu/src/split_merge.cpp

@@ -119,7 +119,6 @@ namespace
 
         int depth = src.depth();
         int num_channels = src.channels();
-        Size size = src.size();
 
         if (depth == CV_64F)
         {

modules/gpu/test/test_objdetect.cpp

@@ -302,13 +302,13 @@ PARAM_TEST_CASE(LBP_Read_classifier, cv::gpu::DeviceInfo, int)
 
 TEST_P(LBP_Read_classifier, Accuracy)
 {
-    cv::gpu::CascadeClassifier_GPU classifier;
+    cv::gpu::CascadeClassifier_GPU classifier;
     std::string classifierXmlPath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/lbpcascade_frontalface.xml";
     ASSERT_TRUE(classifier.load(classifierXmlPath));
 }
 
-INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_Read_classifier,
-                        testing::Combine(ALL_DEVICES, testing::Values<int>(0)));
+INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_Read_classifier,
+                        testing::Combine(ALL_DEVICES, testing::Values<int>(0)));
 
 
 PARAM_TEST_CASE(LBP_classify, cv::gpu::DeviceInfo, int)
@@ -344,31 +344,32 @@ TEST_P(LBP_classify, Accuracy)
     for (; it != rects.end(); ++it)
         cv::rectangle(markedImage, *it, CV_RGB(0, 0, 255));
 
-    cv::gpu::CascadeClassifier_GPU gpuClassifier;
+    cv::gpu::CascadeClassifier_GPU gpuClassifier;
     ASSERT_TRUE(gpuClassifier.load(classifierXmlPath));
 
     cv::gpu::GpuMat gpu_rects;
     cv::gpu::GpuMat tested(grey);
     int count = gpuClassifier.detectMultiScale(tested, gpu_rects);
 
+#if defined (LOG_CASCADE_STATISTIC)
     cv::Mat downloaded(gpu_rects);
-    const cv::Rect* faces = downloaded.ptr<cv::Rect>();
+    const cv::Rect* faces = downloaded.ptr<cv::Rect>();
     for (int i = 0; i < count; i++)
     {
         cv::Rect r = faces[i];
 
-#if defined (LOG_CASCADE_STATISTIC)
-        std::cout << r.x << " " << r.y  << " " << r.width << " " << r.height << std::endl;
+        std::cout << r.x << " " << r.y  << " " << r.width << " " << r.height << std::endl;
         cv::rectangle(markedImage, r , CV_RGB(255, 0, 0));
-#endif
     }
+#endif
 
 #if defined (LOG_CASCADE_STATISTIC)
-    cv::imshow("Res", markedImage); cv::waitKey();
+    cv::imshow("Res", markedImage); cv::waitKey();
 #endif
+    (void)count;
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_classify,
-                        testing::Combine(ALL_DEVICES, testing::Values<int>(0)));
+                        testing::Combine(ALL_DEVICES, testing::Values<int>(0)));
 
 } // namespace