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added buffered version of norm, updated performance sample and docs

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This commit is contained in:
Alexey Spizhevoy 2011-02-01 10:46:19 +00:00
parent 3795142604
commit 16e74ab306
4 changed files with 32 additions and 11 deletions
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11
doc/gpu_matrix_reductions.tex
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@ -17,12 +17,19 @@ See also: \cvCppCross{meanStdDev}.
\cvCppFunc{gpu::norm}
Returns norm of matrix (or of two matrices difference).
\cvdefCpp{double norm(const GpuMat\& src1, int normType=NORM\_L2);}
\cvdefCpp{double norm(const GpuMat\& src, int normType=NORM\_L2);}
\begin{description}
\cvarg{src1}{Source matrix. Any matrices except 64F are supported.}
\cvarg{src}{Source matrix. Any matrices except 64F are supported.}
\cvarg{normType}{Norm type. \texttt{NORM\_L1}, \texttt{NORM\_L2} and \texttt{NORM\_INF} are supported for now.}
\end{description}
\cvdefCpp{double norm(const GpuMat\& src, int normType, GpuMat\& buf);}
\begin{description}
\cvarg{src}{Source matrix. Any matrices except 64F are supported.}
\cvarg{normType}{Norm type. \texttt{NORM\_L1}, \texttt{NORM\_L2} and \texttt{NORM\_INF} are supported for now.}
\cvarg{buf}{Optional buffer to avoid extra memory allocations. It's resized automatically.}
\end{description}
\cvdefCpp{double norm(const GpuMat\& src1, const GpuMat\& src2,\par
int normType=NORM\_L2);}
\begin{description}

7
modules/gpu/include/opencv2/gpu/gpu.hpp
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@ -750,9 +750,14 @@ namespace cv
//! computes norm of array
//! supports NORM_INF, NORM_L1, NORM_L2
//! supports only CV_8UC1 type
//! supports all matrices except 64F
CV_EXPORTS double norm(const GpuMat& src1, int normType=NORM_L2);
//! computes norm of array
//! supports NORM_INF, NORM_L1, NORM_L2
//! supports all matrices except 64F
CV_EXPORTS double norm(const GpuMat& src1, int normType, GpuMat& buf);
//! computes norm of the difference between two arrays
//! supports NORM_INF, NORM_L1, NORM_L2
//! supports only CV_8UC1 type

13
modules/gpu/src/matrix_reductions.cpp
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@ -49,6 +49,7 @@ using namespace cv::gpu;
void cv::gpu::meanStdDev(const GpuMat&, Scalar&, Scalar&) { throw_nogpu(); }
double cv::gpu::norm(const GpuMat&, int) { throw_nogpu(); return 0.0; }
double cv::gpu::norm(const GpuMat&, int, GpuMat&) { throw_nogpu(); return 0.0; }
double cv::gpu::norm(const GpuMat&, const GpuMat&, int) { throw_nogpu(); return 0.0; }
Scalar cv::gpu::sum(const GpuMat&) { throw_nogpu(); return Scalar(); }
Scalar cv::gpu::sum(const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); }
@ -87,19 +88,25 @@ void cv::gpu::meanStdDev(const GpuMat& src, Scalar& mean, Scalar& stddev)
// norm
double cv::gpu::norm(const GpuMat& src, int normType)
{
GpuMat buf;
return norm(src, normType, buf);
}
double cv::gpu::norm(const GpuMat& src, int normType, GpuMat& buf)
{
GpuMat src_single_channel = src.reshape(1);
if (normType == NORM_L1)
return absSum(src_single_channel)[0];
return absSum(src_single_channel, buf)[0];
if (normType == NORM_L2)
return sqrt(sqrSum(src_single_channel)[0]);
return sqrt(sqrSum(src_single_channel, buf)[0]);
if (normType == NORM_INF)
{
double min_val, max_val;
minMax(src_single_channel, &min_val, &max_val);
minMax(src_single_channel, &min_val, &max_val, GpuMat(), buf);
return std::max(std::abs(min_val), std::abs(max_val));
}

12
samples/gpu/performance/tests.cpp
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@ -198,22 +198,24 @@ TEST(integral)
TEST(norm)
{
Mat src;
gpu::GpuMat d_src;
gpu::GpuMat d_src, d_buf;
for (int size = 1000; size <= 8000; size *= 2)
{
SUBTEST << "size " << size << ", 8U";
SUBTEST << "size " << size << ", 32F";
gen(src, size, size, CV_8U, 0, 256);
gen(src, size, size, CV_32F, 0, 1);
CPU_ON;
norm(src);
for (int i = 0; i < 10; ++i)
norm(src, NORM_L2);
CPU_OFF;
d_src = src;
GPU_ON;
gpu::norm(d_src);
for (int i = 0; i < 10; ++i)
gpu::norm(d_src, NORM_L2, d_buf);
GPU_OFF;
}
}