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fixed bug in matchTemplate when template size is (1,1), refactored

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This commit is contained in:
Alexey Spizhevoy 2010-12-14 09:53:17 +00:00
parent 1887b7d2e4
commit e7cf541f5f
2 changed files with 71 additions and 72 deletions
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142
modules/gpu/src/cuda/match_template.cu
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@ -47,50 +47,6 @@ 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;
}
}
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;
@ -135,6 +91,56 @@ void matchTemplateNaive_32F_CCORR(const DevMem2D image, const DevMem2D templ,
}
texture<float, 2> imageTex_32F_SQDIFF;
texture<float, 2> templTex_32F_SQDIFF;
__global__ void matchTemplateNaiveKernel_32F_SQDIFF(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;
float delta;
for (int i = 0; i < h; ++i)
{
for (int j = 0; j < w; ++j)
{
delta = tex2D(imageTex_32F_SQDIFF, x + j, y + i) -
tex2D(templTex_32F_SQDIFF, j, i);
sum += delta * delta;
}
}
result.ptr(y)[x] = sum;
}
}
void matchTemplateNaive_32F_SQDIFF(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_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_32F_SQDIFF.filterMode = cudaFilterModePoint;
templTex_32F_SQDIFF.filterMode = cudaFilterModePoint;
matchTemplateNaiveKernel_32F_SQDIFF<<<grid, threads>>>(templ.cols, templ.rows, result);
cudaSafeCall(cudaThreadSynchronize());
cudaSafeCall(cudaUnbindTexture(imageTex_32F_SQDIFF));
cudaSafeCall(cudaUnbindTexture(templTex_32F_SQDIFF));
}
texture<unsigned char, 2> imageTex_8U_SQDIFF;
texture<unsigned char, 2> templTex_8U_SQDIFF;
@ -185,12 +191,12 @@ void matchTemplateNaive_8U_SQDIFF(const DevMem2D image, const DevMem2D templ,
}
texture<float, 2> imageTex_32F_SQDIFF;
texture<float, 2> templTex_32F_SQDIFF;
texture<unsigned char, 2> imageTex_8U_CCORR;
texture<unsigned char, 2> templTex_8U_CCORR;
__global__ void matchTemplateNaiveKernel_32F_SQDIFF(int w, int h,
DevMem2Df result)
__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;
@ -198,40 +204,34 @@ __global__ void matchTemplateNaiveKernel_32F_SQDIFF(int w, int h,
if (x < result.cols && y < result.rows)
{
float sum = 0.f;
float delta;
for (int i = 0; i < h; ++i)
{
for (int j = 0; j < w; ++j)
{
delta = tex2D(imageTex_32F_SQDIFF, x + j, y + i) -
tex2D(templTex_32F_SQDIFF, j, i);
sum += delta * delta;
}
}
sum += (float)tex2D(imageTex_8U_CCORR, x + j, y + i) *
(float)tex2D(templTex_8U_CCORR, j, i);
result.ptr(y)[x] = sum;
}
}
void matchTemplateNaive_32F_SQDIFF(const DevMem2D image, const DevMem2D templ,
DevMem2Df result)
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<float>();
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;
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_32F_SQDIFF<<<grid, threads>>>(templ.cols, templ.rows, result);
matchTemplateNaiveKernel_8U_CCORR<<<grid, threads>>>(templ.cols, templ.rows, result);
cudaSafeCall(cudaThreadSynchronize());
cudaSafeCall(cudaUnbindTexture(imageTex_32F_SQDIFF));
cudaSafeCall(cudaUnbindTexture(templTex_32F_SQDIFF));
cudaSafeCall(cudaUnbindTexture(imageTex_8U_CCORR));
cudaSafeCall(cudaUnbindTexture(templTex_8U_CCORR));
}
@ -301,8 +301,8 @@ __global__ void matchTemplatePreparedKernel_8U_SQDIFF_NORMED(
(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_sqsum_ - 2.f * ccorr + templ_sqsum) *
rsqrtf(image_sqsum_ * templ_sqsum);
result.ptr(y)[x] = min(1.f, (image_sqsum_ - 2.f * ccorr + templ_sqsum) *
rsqrtf(image_sqsum_ * templ_sqsum));
}
}
@ -368,8 +368,8 @@ __global__ void matchTemplatePreparedKernel_8U_CCOEFF_NORMED(
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] = (ccorr - image_sum_ * templ_sum_scale) *
rsqrtf(templ_sqsum_scale * (image_sqsum_ - weight * image_sum_ * image_sum_));
result.ptr(y)[x] = min(1.f, (ccorr - image_sum_ * templ_sum_scale) *
rsqrtf(templ_sqsum_scale * (image_sqsum_ - weight * image_sum_ * image_sum_)));
}
}
@ -405,7 +405,7 @@ __global__ void normalizeKernel_8U(
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_sqsum_ * templ_sqsum);
result.ptr(y)[x] = min(1.f, result.ptr(y)[x] * rsqrtf(image_sqsum_ * templ_sqsum));
}
}

1
tests/gpu/src/gputest_main.cpp
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@ -51,7 +51,6 @@ const char* blacklist[] =
};
int main( int argc, char** argv )
{
return test_system.run( argc, argv, blacklist );
}