simplified gpu::columnSum test, it doesn't fail on Quadro anymore (when seed is 000001af5a11badd) after BFM test, but something definitely wrong with NPP_Staging's transpose
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@ -1156,25 +1156,25 @@ void cv::gpu::dft(const GpuMat& src, GpuMat& dst, Size dft_size, int flags)
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if (src_data.data != src.data)
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src.copyTo(src_data);
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Size dft_size_ = dft_size;
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Size dft_size_opt = dft_size;
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if (is_1d_input && !is_row_dft)
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{
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// If the source matrix is single column handle it as single row
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dft_size_.width = std::max(dft_size.width, dft_size.height);
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dft_size_.height = std::min(dft_size.width, dft_size.height);
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dft_size_opt.width = std::max(dft_size.width, dft_size.height);
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dft_size_opt.height = std::min(dft_size.width, dft_size.height);
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}
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cufftType dft_type = CUFFT_R2C;
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if (is_complex_input)
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dft_type = is_complex_output ? CUFFT_C2C : CUFFT_C2R;
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CV_Assert(dft_size_.width > 1);
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CV_Assert(dft_size_opt.width > 1);
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cufftHandle plan;
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if (is_1d_input || is_row_dft)
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cufftPlan1d(&plan, dft_size_.width, dft_type, dft_size_.height);
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cufftPlan1d(&plan, dft_size_opt.width, dft_type, dft_size_opt.height);
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else
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cufftPlan2d(&plan, dft_size_.height, dft_size_.width, dft_type);
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cufftPlan2d(&plan, dft_size_opt.height, dft_size_opt.width, dft_type);
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if (is_complex_input)
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{
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@ -1194,7 +1194,8 @@ void cv::gpu::dft(const GpuMat& src, GpuMat& dst, Size dft_size, int flags)
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}
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else
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{
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if (dft_size == dft_size_)
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// We could swap dft_size for efficiency. Here we must reflect it
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if (dft_size == dft_size_opt)
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createContinuous(Size(dft_size.width / 2 + 1, dft_size.height), CV_32FC2, dst);
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else
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createContinuous(Size(dft_size.width, dft_size.height / 2 + 1), CV_32FC2, dst);
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@ -1206,7 +1207,7 @@ void cv::gpu::dft(const GpuMat& src, GpuMat& dst, Size dft_size, int flags)
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cufftSafeCall(cufftDestroy(plan));
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if (is_scaled_dft)
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multiply(dst, Scalar::all(1. / (dft_size.area())), dst);
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multiply(dst, Scalar::all(1. / dft_size.area()), dst);
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}
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//////////////////////////////////////////////////////////////////////////////
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@ -1260,18 +1261,19 @@ void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result,
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block_size.width = std::min(dft_size.width - templ.cols + 1, result.cols);
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block_size.height = std::min(dft_size.height - templ.rows + 1, result.rows);
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GpuMat result_data = createContinuous(dft_size, CV_32F);
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int spect_len = dft_size.height * (dft_size.width / 2 + 1);
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GpuMat image_spect(1, spect_len, CV_32FC2);
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GpuMat templ_spect(1, spect_len, CV_32FC2);
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GpuMat result_spect(1, spect_len, CV_32FC2);
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GpuMat image_spect = createContinuous(1, spect_len, CV_32FC2);
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GpuMat templ_spect = createContinuous(1, spect_len, CV_32FC2);
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GpuMat result_spect = createContinuous(1, spect_len, CV_32FC2);
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cufftHandle planR2C, planC2R;
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cufftSafeCall(cufftPlan2d(&planC2R, dft_size.height, dft_size.width, CUFFT_C2R));
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cufftSafeCall(cufftPlan2d(&planR2C, dft_size.height, dft_size.width, CUFFT_R2C));
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GpuMat image_block = createContinuous(dft_size, CV_32F);
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GpuMat templ_block = createContinuous(dft_size, CV_32F);
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GpuMat result_data = createContinuous(dft_size, CV_32F);
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GpuMat templ_roi(templ.size(), CV_32F, templ.data, templ.step);
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copyMakeBorder(templ_roi, templ_block, 0, templ_block.rows - templ_roi.rows, 0,
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templ_block.cols - templ_roi.cols, 0);
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@ -1279,8 +1281,6 @@ void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result,
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cufftSafeCall(cufftExecR2C(planR2C, templ_block.ptr<cufftReal>(),
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templ_spect.ptr<cufftComplex>()));
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GpuMat image_block = createContinuous(dft_size, CV_32F);
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// Process all blocks of the result matrix
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for (int y = 0; y < result.rows; y += block_size.height)
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{
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@ -47,7 +47,6 @@ const char* blacklist[] =
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{
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"GPU-AsyncGpuMatOperator", // crash
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"GPU-NppImageCanny", // NPP_TEXTURE_BIND_ERROR
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"GPU-BruteForceMatcher", // often crashes when seed=000001af5a11badd
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0
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};
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@ -768,34 +768,37 @@ struct CV_GpuColumnSumTest: CvTest
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{
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try
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{
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int n = 375;
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int m = 1072;
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Mat src(n, m, CV_32F);
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int cols = 375;
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int rows = 1072;
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Mat src(rows, cols, CV_32F);
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RNG rng(1);
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rng.fill(src, RNG::UNIFORM, Scalar(0), Scalar(1));
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Mat dst_gold, dst2_gold;
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integral(src, dst_gold, dst2_gold);
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GpuMat dsrc(src);
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GpuMat buf;
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GpuMat dst;
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columnSum(dsrc, buf);
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transpose(buf, dst);
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columnSum(dst, buf);
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transpose(buf, dst);
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GpuMat d_dst;
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columnSum(GpuMat(src), d_dst);
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Mat dst_ = dst;
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for (int i = 0; i < dst_.rows; ++i)
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Mat dst = d_dst;
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for (int j = 0; j < src.cols; ++j)
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{
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const double* dst_gold_data = (const double*)dst_gold.ptr(i + 1);
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for (int j = 0; j < dst_.cols; ++j)
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float a = src.at<float>(0, j);
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float b = dst.at<float>(0, j);
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if (fabs(a - b) > 0.5f)
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{
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float a = (float)dst_gold_data[j + 1];
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float b = dst_.at<float>(i, j);
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ts->printf(CvTS::CONSOLE, "big diff at %d %d: %f %f\n", 0, j, a, b);
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ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
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return;
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}
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}
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for (int i = 1; i < src.rows; ++i)
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{
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for (int j = 0; j < src.cols; ++j)
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{
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float a = src.at<float>(i, j) += src.at<float>(i - 1, j);
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float b = dst.at<float>(i, j);
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if (fabs(a - b) > 0.5f)
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{
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ts->printf(CvTS::CONSOLE, "%d %d %f %f\n", i, j, a, b);
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ts->printf(CvTS::CONSOLE, "big diff at %d %d: %f %f\n", i, j, a, b);
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ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
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return;
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}
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@ -804,6 +807,7 @@ struct CV_GpuColumnSumTest: CvTest
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}
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catch (const Exception& e)
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{
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ts->printf(CvTS::CONSOLE, e.what());
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if (!check_and_treat_gpu_exception(e, ts)) throw;
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return;
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}
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