spatialGradient: Add test class and Sobel proxy method

This commit is contained in:
Seon-Wook Park 2015-06-18 17:42:32 +02:00
parent 12e6efc6e4
commit 9f1c641199
3 changed files with 126 additions and 0 deletions

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@ -1369,6 +1369,15 @@ CV_EXPORTS_W void Sobel( InputArray src, OutputArray dst, int ddepth,
double scale = 1, double delta = 0,
int borderType = BORDER_DEFAULT );
/** @brief TODO
TODO
*/
CV_EXPORTS_W void spatialGradient( InputArray src, OutputArray dx,
OutputArray dy, int ksize );
/** @brief Calculates the first x- or y- image derivative using Scharr operator.
The function computes the first x- or y- spatial image derivative using the Scharr operator. The

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@ -0,0 +1,56 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
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// If you do not agree to this license, do not download, install,
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//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//M*/
#include "precomp.hpp"
namespace cv
{
void spatialGradient( InputArray src, OutputArray dx, OutputArray dy, int ksize )
{
// TODO: Vectorize using hal intrinsics
Sobel( src, dx, CV_16S, 1, 0, 3 );
Sobel( src, dy, CV_16S, 0, 1, 3 );
}
}

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@ -552,6 +552,66 @@ void CV_SobelTest::prepare_to_validation( int /*test_case_idx*/ )
}
/////////////// spatialGradient ///////////////
class CV_SpatialGradientTest : public CV_DerivBaseTest
{
public:
CV_SpatialGradientTest();
protected:
void prepare_to_validation( int test_case_idx );
void run_func();
void get_test_array_types_and_sizes( int test_case_idx,
vector<vector<Size> >& sizes, vector<vector<int> >& types );
int ksize;
};
CV_SpatialGradientTest::CV_SpatialGradientTest() {
test_array[OUTPUT].push_back(NULL);
test_array[REF_OUTPUT].push_back(NULL);
inplace = false;
}
void CV_SpatialGradientTest::get_test_array_types_and_sizes( int test_case_idx,
vector<vector<Size> >& sizes,
vector<vector<int> >& types )
{
CV_DerivBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
sizes[OUTPUT][1] = sizes[REF_OUTPUT][1] = sizes[OUTPUT][0];
// Only CV_16S1 for now
types[INPUT][0] = types[OUTPUT][0] = types[OUTPUT][1] = types[REF_OUTPUT][0]
= types[REF_OUTPUT][1] = CV_MAKETYPE(CV_16S, 1);
ksize = 3;
}
void CV_SpatialGradientTest::run_func()
{
spatialGradient( cvarrToMat(test_array[INPUT][0]),
cvarrToMat(test_array[OUTPUT][0]),
cvarrToMat(test_array[OUTPUT][1]),
ksize
);
}
void CV_SpatialGradientTest::prepare_to_validation( int /*test_case_idx*/ )
{
int dx, dy;
dx = 1; dy = 0;
Sobel( test_mat[INPUT][0], test_mat[REF_OUTPUT][0], CV_16SC1, dx, dy, ksize );
dx = 0; dy = 1;
Sobel( test_mat[INPUT][0], test_mat[REF_OUTPUT][1], CV_16SC1, dx, dy, ksize );
}
/////////////// laplace ///////////////
class CV_LaplaceTest : public CV_DerivBaseTest
@ -1773,6 +1833,7 @@ TEST(Imgproc_Dilate, accuracy) { CV_DilateTest test; test.safe_run(); }
TEST(Imgproc_MorphologyEx, accuracy) { CV_MorphExTest test; test.safe_run(); }
TEST(Imgproc_Filter2D, accuracy) { CV_FilterTest test; test.safe_run(); }
TEST(Imgproc_Sobel, accuracy) { CV_SobelTest test; test.safe_run(); }
TEST(Imgproc_SpatialGradient, accuracy) { CV_SpatialGradientTest test; test.safe_run(); }
TEST(Imgproc_Laplace, accuracy) { CV_LaplaceTest test; test.safe_run(); }
TEST(Imgproc_Blur, accuracy) { CV_BlurTest test; test.safe_run(); }
TEST(Imgproc_GaussianBlur, accuracy) { CV_GaussianBlurTest test; test.safe_run(); }