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@ -47,12 +47,12 @@ using namespace cv::gpu; |
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namespace cv { namespace gpu { namespace imgproc { |
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texture<unsigned char, 2> imageTex_8U_CCORR; |
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texture<unsigned char, 2> templTex_8U_CCORR; |
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texture<float, 2> imageTex_32F_CCORR; |
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texture<float, 2> templTex_32F_CCORR; |
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__global__ void matchTemplateNaiveKernel_8U_CCORR(int w, int h, |
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DevMem2Df result) |
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__global__ void matchTemplateNaiveKernel_32F_CCORR(int w, int h, |
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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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@ -63,40 +63,40 @@ __global__ void matchTemplateNaiveKernel_8U_CCORR(int w, int h, |
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for (int i = 0; i < h; ++i) |
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for (int j = 0; j < w; ++j) |
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sum += (float)tex2D(imageTex_8U_CCORR, x + j, y + i) * |
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(float)tex2D(templTex_8U_CCORR, j, i); |
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sum += tex2D(imageTex_32F_CCORR, x + j, y + i) * |
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tex2D(templTex_32F_CCORR, j, i); |
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result.ptr(y)[x] = sum; |
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} |
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} |
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void matchTemplateNaive_8U_CCORR(const DevMem2D image, const DevMem2D templ, |
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DevMem2Df result) |
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void matchTemplateNaive_32F_CCORR(const DevMem2D image, const DevMem2D templ, |
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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<unsigned char>(); |
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cudaBindTexture2D(0, imageTex_8U_CCORR, image.data, desc, image.cols, image.rows, image.step); |
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cudaBindTexture2D(0, templTex_8U_CCORR, templ.data, desc, templ.cols, templ.rows, templ.step); |
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imageTex_8U_CCORR.filterMode = cudaFilterModePoint; |
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templTex_8U_CCORR.filterMode = cudaFilterModePoint; |
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cudaChannelFormatDesc desc = cudaCreateChannelDesc<float>(); |
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cudaBindTexture2D(0, imageTex_32F_CCORR, image.data, desc, image.cols, image.rows, image.step); |
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cudaBindTexture2D(0, templTex_32F_CCORR, templ.data, desc, templ.cols, templ.rows, templ.step); |
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imageTex_32F_CCORR.filterMode = cudaFilterModePoint; |
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templTex_32F_CCORR.filterMode = cudaFilterModePoint; |
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matchTemplateNaiveKernel_8U_CCORR<<<grid, threads>>>(templ.cols, templ.rows, result); |
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matchTemplateNaiveKernel_32F_CCORR<<<grid, threads>>>(templ.cols, templ.rows, result); |
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cudaSafeCall(cudaThreadSynchronize()); |
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cudaSafeCall(cudaUnbindTexture(imageTex_8U_CCORR)); |
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cudaSafeCall(cudaUnbindTexture(templTex_8U_CCORR)); |
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cudaSafeCall(cudaUnbindTexture(imageTex_32F_CCORR)); |
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cudaSafeCall(cudaUnbindTexture(templTex_32F_CCORR)); |
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} |
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texture<float, 2> imageTex_32F_CCORR; |
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texture<float, 2> templTex_32F_CCORR; |
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texture<float, 2> imageTex_32F_SQDIFF; |
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texture<float, 2> templTex_32F_SQDIFF; |
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__global__ void matchTemplateNaiveKernel_32F_CCORR(int w, int h, |
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DevMem2Df result) |
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__global__ void matchTemplateNaiveKernel_32F_SQDIFF(int w, int h, |
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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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@ -104,34 +104,40 @@ __global__ void matchTemplateNaiveKernel_32F_CCORR(int w, int h, |
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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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sum += tex2D(imageTex_32F_CCORR, x + j, y + i) * |
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tex2D(templTex_32F_CCORR, j, i); |
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{ |
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delta = tex2D(imageTex_32F_SQDIFF, x + j, y + i) - |
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tex2D(templTex_32F_SQDIFF, 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 matchTemplateNaive_32F_CCORR(const DevMem2D image, const DevMem2D templ, |
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DevMem2Df result) |
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void matchTemplateNaive_32F_SQDIFF(const DevMem2D image, const DevMem2D templ, |
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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_CCORR, image.data, desc, image.cols, image.rows, image.step); |
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cudaBindTexture2D(0, templTex_32F_CCORR, templ.data, desc, templ.cols, templ.rows, templ.step); |
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imageTex_32F_CCORR.filterMode = cudaFilterModePoint; |
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templTex_32F_CCORR.filterMode = cudaFilterModePoint; |
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cudaBindTexture2D(0, imageTex_32F_SQDIFF, image.data, desc, image.cols, image.rows, image.step); |
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cudaBindTexture2D(0, templTex_32F_SQDIFF, templ.data, desc, templ.cols, templ.rows, templ.step); |
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imageTex_32F_SQDIFF.filterMode = cudaFilterModePoint; |
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templTex_32F_SQDIFF.filterMode = cudaFilterModePoint; |
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matchTemplateNaiveKernel_32F_CCORR<<<grid, threads>>>(templ.cols, templ.rows, result); |
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matchTemplateNaiveKernel_32F_SQDIFF<<<grid, threads>>>(templ.cols, templ.rows, result); |
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cudaSafeCall(cudaThreadSynchronize()); |
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cudaSafeCall(cudaUnbindTexture(imageTex_32F_CCORR)); |
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cudaSafeCall(cudaUnbindTexture(templTex_32F_CCORR)); |
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cudaSafeCall(cudaUnbindTexture(imageTex_32F_SQDIFF)); |
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cudaSafeCall(cudaUnbindTexture(templTex_32F_SQDIFF)); |
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} |
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@ -185,12 +191,12 @@ void matchTemplateNaive_8U_SQDIFF(const DevMem2D image, const DevMem2D templ, |
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} |
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texture<float, 2> imageTex_32F_SQDIFF; |
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texture<float, 2> templTex_32F_SQDIFF; |
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texture<unsigned char, 2> imageTex_8U_CCORR; |
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texture<unsigned char, 2> templTex_8U_CCORR; |
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__global__ void matchTemplateNaiveKernel_32F_SQDIFF(int w, int h, |
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DevMem2Df result) |
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__global__ void matchTemplateNaiveKernel_8U_CCORR(int w, int h, |
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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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@ -198,40 +204,34 @@ __global__ void matchTemplateNaiveKernel_32F_SQDIFF(int w, int h, |
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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_SQDIFF, x + j, y + i) - |
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tex2D(templTex_32F_SQDIFF, j, i); |
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sum += delta * delta; |
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} |
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} |
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sum += (float)tex2D(imageTex_8U_CCORR, x + j, y + i) * |
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(float)tex2D(templTex_8U_CCORR, j, i); |
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result.ptr(y)[x] = sum; |
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} |
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} |
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void matchTemplateNaive_32F_SQDIFF(const DevMem2D image, const DevMem2D templ, |
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DevMem2Df result) |
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void matchTemplateNaive_8U_CCORR(const DevMem2D image, const DevMem2D templ, |
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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_SQDIFF, image.data, desc, image.cols, image.rows, image.step); |
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cudaBindTexture2D(0, templTex_32F_SQDIFF, templ.data, desc, templ.cols, templ.rows, templ.step); |
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imageTex_8U_SQDIFF.filterMode = cudaFilterModePoint; |
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templTex_8U_SQDIFF.filterMode = cudaFilterModePoint; |
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cudaChannelFormatDesc desc = cudaCreateChannelDesc<unsigned char>(); |
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cudaBindTexture2D(0, imageTex_8U_CCORR, image.data, desc, image.cols, image.rows, image.step); |
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cudaBindTexture2D(0, templTex_8U_CCORR, templ.data, desc, templ.cols, templ.rows, templ.step); |
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imageTex_8U_CCORR.filterMode = cudaFilterModePoint; |
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templTex_8U_CCORR.filterMode = cudaFilterModePoint; |
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matchTemplateNaiveKernel_32F_SQDIFF<<<grid, threads>>>(templ.cols, templ.rows, result); |
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matchTemplateNaiveKernel_8U_CCORR<<<grid, threads>>>(templ.cols, templ.rows, result); |
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cudaSafeCall(cudaThreadSynchronize()); |
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cudaSafeCall(cudaUnbindTexture(imageTex_32F_SQDIFF)); |
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cudaSafeCall(cudaUnbindTexture(templTex_32F_SQDIFF)); |
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cudaSafeCall(cudaUnbindTexture(imageTex_8U_CCORR)); |
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cudaSafeCall(cudaUnbindTexture(templTex_8U_CCORR)); |
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} |
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@ -301,8 +301,8 @@ __global__ void matchTemplatePreparedKernel_8U_SQDIFF_NORMED( |
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(image_sqsum.ptr(y + h)[x + w] - image_sqsum.ptr(y)[x + w]) - |
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(image_sqsum.ptr(y + h)[x] - image_sqsum.ptr(y)[x])); |
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float ccorr = result.ptr(y)[x]; |
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result.ptr(y)[x] = (image_sqsum_ - 2.f * ccorr + templ_sqsum) * |
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rsqrtf(image_sqsum_ * templ_sqsum); |
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result.ptr(y)[x] = min(1.f, (image_sqsum_ - 2.f * ccorr + templ_sqsum) * |
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rsqrtf(image_sqsum_ * templ_sqsum)); |
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} |
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} |
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@ -368,8 +368,8 @@ __global__ void matchTemplatePreparedKernel_8U_CCOEFF_NORMED( |
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float image_sqsum_ = (float)( |
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(image_sqsum.ptr(y + h)[x + w] - image_sqsum.ptr(y)[x + w]) - |
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(image_sqsum.ptr(y + h)[x] - image_sqsum.ptr(y)[x])); |
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result.ptr(y)[x] = (ccorr - image_sum_ * templ_sum_scale) * |
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rsqrtf(templ_sqsum_scale * (image_sqsum_ - weight * image_sum_ * image_sum_)); |
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result.ptr(y)[x] = min(1.f, (ccorr - image_sum_ * templ_sum_scale) * |
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rsqrtf(templ_sqsum_scale * (image_sqsum_ - weight * image_sum_ * image_sum_))); |
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} |
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} |
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@ -405,7 +405,7 @@ __global__ void normalizeKernel_8U( |
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float image_sqsum_ = (float)( |
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(image_sqsum.ptr(y + h)[x + w] - image_sqsum.ptr(y)[x + w]) - |
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(image_sqsum.ptr(y + h)[x] - image_sqsum.ptr(y)[x])); |
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result.ptr(y)[x] *= rsqrtf(image_sqsum_ * templ_sqsum); |
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result.ptr(y)[x] = min(1.f, result.ptr(y)[x] * rsqrtf(image_sqsum_ * templ_sqsum)); |
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} |
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} |
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