added support of CV_32F & CV_TM_SQDIFF into gpu::matchTemplate
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@@ -50,6 +50,7 @@ using namespace cv::gpu;
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namespace cv { namespace gpu { namespace imgproc {
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texture<unsigned char, 2> imageTex_8U;
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texture<unsigned char, 2> templTex_8U;
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@@ -98,6 +99,54 @@ void matchTemplate_8U_SQDIFF(const DevMem2D image, const DevMem2D templ, DevMem2
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}
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texture<float, 2> imageTex_32F;
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texture<float, 2> templTex_32F;
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__global__ void matchTemplateKernel_32F_SQDIFF(int w, int h, DevMem2Df result)
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{
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int x = blockDim.x * blockIdx.x + threadIdx.x;
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int y = blockDim.y * blockIdx.y + threadIdx.y;
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if (x < result.cols && y < result.rows)
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{
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float sum = 0.f;
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float delta;
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for (int i = 0; i < h; ++i)
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{
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for (int j = 0; j < w; ++j)
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{
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delta = tex2D(imageTex_32F, x + j, y + i) -
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tex2D(templTex_32F, j, i);
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sum += delta * delta;
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}
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}
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result.ptr(y)[x] = sum;
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}
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}
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void matchTemplate_32F_SQDIFF(const DevMem2D image, const DevMem2D templ, DevMem2Df result)
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{
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dim3 threads(32, 8);
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dim3 grid(divUp(image.cols - templ.cols + 1, threads.x),
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divUp(image.rows - templ.rows + 1, threads.y));
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cudaChannelFormatDesc desc = cudaCreateChannelDesc<float>();
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cudaBindTexture2D(0, imageTex_32F, image.data, desc, image.cols, image.rows, image.step);
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cudaBindTexture2D(0, templTex_32F, templ.data, desc, templ.cols, templ.rows, templ.step);
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imageTex_8U.filterMode = cudaFilterModePoint;
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templTex_8U.filterMode = cudaFilterModePoint;
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matchTemplateKernel_32F_SQDIFF<<<grid, threads>>>(templ.cols, templ.rows, result);
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cudaSafeCall(cudaThreadSynchronize());
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cudaSafeCall(cudaUnbindTexture(imageTex_32F));
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cudaSafeCall(cudaUnbindTexture(templTex_32F));
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}
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__global__ void multiplyAndNormalizeSpectsKernel(int n, float scale, const cufftComplex* a,
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const cufftComplex* b, cufftComplex* c)
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{
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@@ -61,6 +61,7 @@ namespace cv { namespace gpu { namespace imgproc
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void multiplyAndNormalizeSpects(int n, float scale, const cufftComplex* a,
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const cufftComplex* b, cufftComplex* c);
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void matchTemplate_8U_SQDIFF(const DevMem2D image, const DevMem2D templ, DevMem2Df result);
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void matchTemplate_32F_SQDIFF(const DevMem2D image, const DevMem2D templ, DevMem2Df result);
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}}}
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@@ -92,6 +93,14 @@ namespace
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imgproc::matchTemplate_8U_SQDIFF(image, templ, result);
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}
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template <>
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void matchTemplate<CV_32F, CV_TM_SQDIFF>(const GpuMat& image, const GpuMat& templ, GpuMat& result)
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{
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result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
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imgproc::matchTemplate_32F_SQDIFF(image, templ, result);
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}
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#ifdef BLOCK_VERSION
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template <>
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@@ -243,7 +252,8 @@ void cv::gpu::matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& re
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typedef void (*Caller)(const GpuMat&, const GpuMat&, GpuMat&);
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static const Caller callers8U[] = { ::matchTemplate<CV_8U, CV_TM_SQDIFF>, 0, 0, 0, 0, 0 };
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static const Caller callers32F[] = { 0, 0, ::matchTemplate<CV_32F, CV_TM_CCORR>, 0, 0, 0 };
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static const Caller callers32F[] = { ::matchTemplate<CV_32F, CV_TM_SQDIFF>, 0,
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::matchTemplate<CV_32F, CV_TM_CCORR>, 0, 0, 0 };
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const Caller* callers;
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switch (image.type())
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@@ -87,6 +87,16 @@ struct CV_GpuMatchTemplateTest: CvTest
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F(cout << "gpu_block: " << clock() - t << endl;)
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if (!check(dst_gold, Mat(dst), 5 * h * w * 1e-5f)) return;
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gen(image, n, m, CV_32F);
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gen(templ, h, w, CV_32F);
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F(t = clock();)
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matchTemplate(image, templ, dst_gold, CV_TM_SQDIFF);
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F(cout << "cpu:" << clock() - t << endl;)
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F(t = clock();)
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gpu::matchTemplate(gpu::GpuMat(image), gpu::GpuMat(templ), dst, CV_TM_SQDIFF);
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F(cout << "gpu_block: " << clock() - t << endl;)
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if (!check(dst_gold, Mat(dst), 0.25f * h * w * 1e-5f)) return;
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gen(image, n, m, CV_32F);
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gen(templ, h, w, CV_32F);
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F(t = clock();)
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@@ -136,48 +146,48 @@ struct CV_GpuMatchTemplateTest: CvTest
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return true;
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}
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void match_template_naive_SQDIFF(const Mat& a, const Mat& b, Mat& c)
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{
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c.create(a.rows - b.rows + 1, a.cols - b.cols + 1, CV_32F);
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for (int i = 0; i < c.rows; ++i)
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{
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for (int j = 0; j < c.cols; ++j)
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{
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float delta;
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float sum = 0.f;
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for (int y = 0; y < b.rows; ++y)
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{
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const unsigned char* arow = a.ptr(i + y);
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const unsigned char* brow = b.ptr(y);
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for (int x = 0; x < b.cols; ++x)
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{
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delta = (float)(arow[j + x] - brow[x]);
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sum += delta * delta;
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}
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}
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c.at<float>(i, j) = sum;
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}
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}
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}
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//void match_template_naive_SQDIFF(const Mat& a, const Mat& b, Mat& c)
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//{
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// c.create(a.rows - b.rows + 1, a.cols - b.cols + 1, CV_32F);
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// for (int i = 0; i < c.rows; ++i)
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// {
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// for (int j = 0; j < c.cols; ++j)
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// {
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// float delta;
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// float sum = 0.f;
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// for (int y = 0; y < b.rows; ++y)
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// {
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// const unsigned char* arow = a.ptr(i + y);
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// const unsigned char* brow = b.ptr(y);
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// for (int x = 0; x < b.cols; ++x)
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// {
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// delta = (float)(arow[j + x] - brow[x]);
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// sum += delta * delta;
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// }
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// }
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// c.at<float>(i, j) = sum;
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// }
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// }
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//}
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void match_template_naive_CCORR(const Mat& a, const Mat& b, Mat& c)
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{
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c.create(a.rows - b.rows + 1, a.cols - b.cols + 1, CV_32F);
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for (int i = 0; i < c.rows; ++i)
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{
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for (int j = 0; j < c.cols; ++j)
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{
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float sum = 0.f;
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for (int y = 0; y < b.rows; ++y)
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{
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const float* arow = a.ptr<float>(i + y);
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const float* brow = b.ptr<float>(y);
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for (int x = 0; x < b.cols; ++x)
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sum += arow[j + x] * brow[x];
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}
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c.at<float>(i, j) = sum;
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}
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}
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}
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//void match_template_naive_CCORR(const Mat& a, const Mat& b, Mat& c)
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//{
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// c.create(a.rows - b.rows + 1, a.cols - b.cols + 1, CV_32F);
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// for (int i = 0; i < c.rows; ++i)
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// {
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// for (int j = 0; j < c.cols; ++j)
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// {
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// float sum = 0.f;
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// for (int y = 0; y < b.rows; ++y)
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// {
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// const float* arow = a.ptr<float>(i + y);
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// const float* brow = b.ptr<float>(y);
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// for (int x = 0; x < b.cols; ++x)
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// sum += arow[j + x] * brow[x];
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// }
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// c.at<float>(i, j) = sum;
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// }
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// }
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//}
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} match_template_test;
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