2010-12-06 17:44:51 +08:00
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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2010-12-08 21:03:53 +08:00
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#include <cufft.h>
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2010-12-07 00:37:32 +08:00
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#include "internal_shared.hpp"
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2010-12-06 17:44:51 +08:00
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2010-12-08 21:03:53 +08:00
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#include <iostream>
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using namespace std;
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2010-12-06 22:19:41 +08:00
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using namespace cv::gpu;
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2010-12-06 17:44:51 +08:00
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2010-12-06 22:19:41 +08:00
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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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2010-12-08 21:03:53 +08:00
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__global__ void matchTemplateKernel_8U_SQDIFF(int w, int h, DevMem2Df result)
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2010-12-06 22:19:41 +08:00
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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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2010-12-06 17:44:51 +08:00
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{
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2010-12-06 22:19:41 +08:00
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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 = (float)tex2D(imageTex_8U, x + j, y + i) -
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(float)tex2D(templTex_8U, 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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2010-12-08 21:03:53 +08:00
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void matchTemplate_8U_SQDIFF(const DevMem2D image, const DevMem2D templ, DevMem2Df result)
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2010-12-06 22:19:41 +08:00
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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, image.data, desc, image.cols, image.rows, image.step);
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cudaBindTexture2D(0, templTex_8U, 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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2010-12-08 21:03:53 +08:00
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matchTemplateKernel_8U_SQDIFF<<<grid, threads>>>(templ.cols, templ.rows, result);
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2010-12-06 22:19:41 +08:00
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cudaSafeCall(cudaThreadSynchronize());
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cudaSafeCall(cudaUnbindTexture(imageTex_8U));
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cudaSafeCall(cudaUnbindTexture(templTex_8U));
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}
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2010-12-06 17:44:51 +08:00
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2010-12-08 21:03:53 +08:00
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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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int x = blockIdx.x * blockDim.x + threadIdx.x;
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if (x < n)
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{
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cufftComplex v = cuCmulf(a[x], cuConjf(b[x]));
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c[x] = make_cuFloatComplex(cuCrealf(v) * scale, cuCimagf(v) * scale);
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}
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}
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void multiplyAndNormalizeSpects(int n, float scale, const cufftComplex* a, const cufftComplex* b,
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cufftComplex* c)
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{
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dim3 threads(256);
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dim3 grid(divUp(n, threads.x));
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multiplyAndNormalizeSpectsKernel<<<grid, threads>>>(n, scale, a, b, c);
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}
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2010-12-06 22:19:41 +08:00
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}}}
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