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refactored matchTemplate.cu

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pull/13383/head
Alexey Spizhevoy 14 years ago
parent ce47a37e6e
commit 1887b7d2e4
1 changed files with 119 additions and 35 deletions
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  1. 154
      modules/gpu/src/cuda/match_template.cu

154
modules/gpu/src/cuda/match_template.cu
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@ -43,20 +43,104 @@
#include <cufft.h>
#include "internal_shared.hpp"
#include <iostream>
using namespace std;
using namespace cv::gpu;
namespace cv { namespace gpu { namespace imgproc {
texture<unsigned char, 2> imageTex_8U_CCORR;
texture<unsigned char, 2> templTex_8U_CCORR;
__global__ void matchTemplateNaiveKernel_8U_CCORR(int w, int h,
DevMem2Df result)
{
int x = blockDim.x * blockIdx.x + threadIdx.x;
int y = blockDim.y * blockIdx.y + threadIdx.y;
if (x < result.cols && y < result.rows)
{
float sum = 0.f;
for (int i = 0; i < h; ++i)
for (int j = 0; j < w; ++j)
sum += (float)tex2D(imageTex_8U_CCORR, x + j, y + i) *
(float)tex2D(templTex_8U_CCORR, j, i);
result.ptr(y)[x] = sum;
}
}
texture<unsigned char, 2> imageTex_8U;
texture<unsigned char, 2> templTex_8U;
void matchTemplateNaive_8U_CCORR(const DevMem2D image, const DevMem2D templ,
DevMem2Df result)
{
dim3 threads(32, 8);
dim3 grid(divUp(image.cols - templ.cols + 1, threads.x),
divUp(image.rows - templ.rows + 1, threads.y));
cudaChannelFormatDesc desc = cudaCreateChannelDesc<unsigned char>();
cudaBindTexture2D(0, imageTex_8U_CCORR, image.data, desc, image.cols, image.rows, image.step);
cudaBindTexture2D(0, templTex_8U_CCORR, templ.data, desc, templ.cols, templ.rows, templ.step);
imageTex_8U_CCORR.filterMode = cudaFilterModePoint;
templTex_8U_CCORR.filterMode = cudaFilterModePoint;
matchTemplateNaiveKernel_8U_CCORR<<<grid, threads>>>(templ.cols, templ.rows, result);
cudaSafeCall(cudaThreadSynchronize());
cudaSafeCall(cudaUnbindTexture(imageTex_8U_CCORR));
cudaSafeCall(cudaUnbindTexture(templTex_8U_CCORR));
}
texture<float, 2> imageTex_32F_CCORR;
texture<float, 2> templTex_32F_CCORR;
__global__ void matchTemplateNaiveKernel_32F_CCORR(int w, int h,
DevMem2Df result)
{
int x = blockDim.x * blockIdx.x + threadIdx.x;
int y = blockDim.y * blockIdx.y + threadIdx.y;
if (x < result.cols && y < result.rows)
{
float sum = 0.f;
for (int i = 0; i < h; ++i)
for (int j = 0; j < w; ++j)
sum += tex2D(imageTex_32F_CCORR, x + j, y + i) *
tex2D(templTex_32F_CCORR, j, i);
result.ptr(y)[x] = sum;
}
}
void matchTemplateNaive_32F_CCORR(const DevMem2D image, const DevMem2D templ,
DevMem2Df result)
{
dim3 threads(32, 8);
dim3 grid(divUp(image.cols - templ.cols + 1, threads.x),
divUp(image.rows - templ.rows + 1, threads.y));
cudaChannelFormatDesc desc = cudaCreateChannelDesc<float>();
cudaBindTexture2D(0, imageTex_32F_CCORR, image.data, desc, image.cols, image.rows, image.step);
cudaBindTexture2D(0, templTex_32F_CCORR, templ.data, desc, templ.cols, templ.rows, templ.step);
imageTex_32F_CCORR.filterMode = cudaFilterModePoint;
templTex_32F_CCORR.filterMode = cudaFilterModePoint;
matchTemplateNaiveKernel_32F_CCORR<<<grid, threads>>>(templ.cols, templ.rows, result);
cudaSafeCall(cudaThreadSynchronize());
cudaSafeCall(cudaUnbindTexture(imageTex_32F_CCORR));
cudaSafeCall(cudaUnbindTexture(templTex_32F_CCORR));
}
texture<unsigned char, 2> imageTex_8U_SQDIFF;
texture<unsigned char, 2> templTex_8U_SQDIFF;
__global__ void matchTemplateNaiveKernel_8U_SQDIFF(int w, int h,
DevMem2Df result)
DevMem2Df result)
{
int x = blockDim.x * blockIdx.x + threadIdx.x;
int y = blockDim.y * blockIdx.y + threadIdx.y;
@ -70,8 +154,8 @@ __global__ void matchTemplateNaiveKernel_8U_SQDIFF(int w, int h,
{
for (int j = 0; j < w; ++j)
{
delta = (float)tex2D(imageTex_8U, x + j, y + i) -
(float)tex2D(templTex_8U, j, i);
delta = (float)tex2D(imageTex_8U_SQDIFF, x + j, y + i) -
(float)tex2D(templTex_8U_SQDIFF, j, i);
sum += delta * delta;
}
}
@ -82,27 +166,27 @@ __global__ void matchTemplateNaiveKernel_8U_SQDIFF(int w, int h,
void matchTemplateNaive_8U_SQDIFF(const DevMem2D image, const DevMem2D templ,
DevMem2Df result)
DevMem2Df result)
{
dim3 threads(32, 8);
dim3 grid(divUp(image.cols - templ.cols + 1, threads.x),
divUp(image.rows - templ.rows + 1, threads.y));
divUp(image.rows - templ.rows + 1, threads.y));
cudaChannelFormatDesc desc = cudaCreateChannelDesc<unsigned char>();
cudaBindTexture2D(0, imageTex_8U, image.data, desc, image.cols, image.rows, image.step);
cudaBindTexture2D(0, templTex_8U, templ.data, desc, templ.cols, templ.rows, templ.step);
imageTex_8U.filterMode = cudaFilterModePoint;
templTex_8U.filterMode = cudaFilterModePoint;
cudaBindTexture2D(0, imageTex_8U_SQDIFF, image.data, desc, image.cols, image.rows, image.step);
cudaBindTexture2D(0, templTex_8U_SQDIFF, templ.data, desc, templ.cols, templ.rows, templ.step);
imageTex_8U_SQDIFF.filterMode = cudaFilterModePoint;
templTex_8U_SQDIFF.filterMode = cudaFilterModePoint;
matchTemplateNaiveKernel_8U_SQDIFF<<<grid, threads>>>(templ.cols, templ.rows, result);
cudaSafeCall(cudaThreadSynchronize());
cudaSafeCall(cudaUnbindTexture(imageTex_8U));
cudaSafeCall(cudaUnbindTexture(templTex_8U));
cudaSafeCall(cudaUnbindTexture(imageTex_8U_SQDIFF));
cudaSafeCall(cudaUnbindTexture(templTex_8U_SQDIFF));
}
texture<float, 2> imageTex_32F;
texture<float, 2> templTex_32F;
texture<float, 2> imageTex_32F_SQDIFF;
texture<float, 2> templTex_32F_SQDIFF;
__global__ void matchTemplateNaiveKernel_32F_SQDIFF(int w, int h,
@ -120,8 +204,8 @@ __global__ void matchTemplateNaiveKernel_32F_SQDIFF(int w, int h,
{
for (int j = 0; j < w; ++j)
{
delta = tex2D(imageTex_32F, x + j, y + i) -
tex2D(templTex_32F, j, i);
delta = tex2D(imageTex_32F_SQDIFF, x + j, y + i) -
tex2D(templTex_32F_SQDIFF, j, i);
sum += delta * delta;
}
}
@ -132,22 +216,22 @@ __global__ void matchTemplateNaiveKernel_32F_SQDIFF(int w, int h,
void matchTemplateNaive_32F_SQDIFF(const DevMem2D image, const DevMem2D templ,
DevMem2Df result)
DevMem2Df result)
{
dim3 threads(32, 8);
dim3 grid(divUp(image.cols - templ.cols + 1, threads.x),
divUp(image.rows - templ.rows + 1, threads.y));
divUp(image.rows - templ.rows + 1, threads.y));
cudaChannelFormatDesc desc = cudaCreateChannelDesc<float>();
cudaBindTexture2D(0, imageTex_32F, image.data, desc, image.cols, image.rows, image.step);
cudaBindTexture2D(0, templTex_32F, templ.data, desc, templ.cols, templ.rows, templ.step);
imageTex_8U.filterMode = cudaFilterModePoint;
templTex_8U.filterMode = cudaFilterModePoint;
cudaBindTexture2D(0, imageTex_32F_SQDIFF, image.data, desc, image.cols, image.rows, image.step);
cudaBindTexture2D(0, templTex_32F_SQDIFF, templ.data, desc, templ.cols, templ.rows, templ.step);
imageTex_8U_SQDIFF.filterMode = cudaFilterModePoint;
templTex_8U_SQDIFF.filterMode = cudaFilterModePoint;
matchTemplateNaiveKernel_32F_SQDIFF<<<grid, threads>>>(templ.cols, templ.rows, result);
cudaSafeCall(cudaThreadSynchronize());
cudaSafeCall(cudaUnbindTexture(imageTex_32F));
cudaSafeCall(cudaUnbindTexture(templTex_32F));
cudaSafeCall(cudaUnbindTexture(imageTex_32F_SQDIFF));
cudaSafeCall(cudaUnbindTexture(templTex_32F_SQDIFF));
}
@ -183,11 +267,11 @@ __global__ void matchTemplatePreparedKernel_8U_SQDIFF(
if (x < result.cols && y < result.rows)
{
float image_sq = (float)(
float image_sqsum_ = (float)(
(image_sqsum.ptr(y + h)[x + w] - image_sqsum.ptr(y)[x + w]) -
(image_sqsum.ptr(y + h)[x] - image_sqsum.ptr(y)[x]));
float ccorr = result.ptr(y)[x];
result.ptr(y)[x] = image_sq - 2.f * ccorr + templ_sqsum;
result.ptr(y)[x] = image_sqsum_ - 2.f * ccorr + templ_sqsum;
}
}
@ -213,12 +297,12 @@ __global__ void matchTemplatePreparedKernel_8U_SQDIFF_NORMED(
if (x < result.cols && y < result.rows)
{
float image_sq = (float)(
float image_sqsum_ = (float)(
(image_sqsum.ptr(y + h)[x + w] - image_sqsum.ptr(y)[x + w]) -
(image_sqsum.ptr(y + h)[x] - image_sqsum.ptr(y)[x]));
float ccorr = result.ptr(y)[x];
result.ptr(y)[x] = (image_sq - 2.f * ccorr + templ_sqsum) *
rsqrtf(image_sq * templ_sqsum);
result.ptr(y)[x] = (image_sqsum_ - 2.f * ccorr + templ_sqsum) *
rsqrtf(image_sqsum_ * templ_sqsum);
}
}
@ -318,10 +402,10 @@ __global__ void normalizeKernel_8U(
if (x < result.cols && y < result.rows)
{
float image_sq = (float)(
float image_sqsum_ = (float)(
(image_sqsum.ptr(y + h)[x + w] - image_sqsum.ptr(y)[x + w]) -
(image_sqsum.ptr(y + h)[x] - image_sqsum.ptr(y)[x]));
result.ptr(y)[x] *= rsqrtf(image_sq * templ_sqsum);
result.ptr(y)[x] *= rsqrtf(image_sqsum_ * templ_sqsum);
}
}

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