mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
476 lines
16 KiB
476 lines
16 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
|
// |
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
|
// |
|
// By downloading, copying, installing or using the software you agree to this license. |
|
// If you do not agree to this license, do not download, install, |
|
// copy or use the software. |
|
// |
|
// |
|
// Intel License Agreement |
|
// For Open Source Computer Vision Library |
|
// |
|
// Copyright (C) 2000, Intel Corporation, all rights reserved. |
|
// Third party copyrights are property of their respective owners. |
|
// |
|
// Redistribution and use in source and binary forms, with or without modification, |
|
// are permitted provided that the following conditions are met: |
|
// |
|
// * Redistribution's of source code must retain the above copyright notice, |
|
// this list of conditions and the following disclaimer. |
|
// |
|
// * Redistribution's in binary form must reproduce the above copyright notice, |
|
// this list of conditions and the following disclaimer in the documentation |
|
// and/or other materials provided with the distribution. |
|
// |
|
// * The name of Intel Corporation may not be used to endorse or promote products |
|
// derived from this software without specific prior written permission. |
|
// |
|
// This software is provided by the copyright holders and contributors "as is" and |
|
// any express or implied warranties, including, but not limited to, the implied |
|
// warranties of merchantability and fitness for a particular purpose are disclaimed. |
|
// In no event shall the Intel Corporation or contributors be liable for any direct, |
|
// indirect, incidental, special, exemplary, or consequential damages |
|
// (including, but not limited to, procurement of substitute goods or services; |
|
// loss of use, data, or profits; or business interruption) however caused |
|
// and on any theory of liability, whether in contract, strict liability, |
|
// or tort (including negligence or otherwise) arising in any way out of |
|
// the use of this software, even if advised of the possibility of such damage. |
|
// |
|
//M*/ |
|
|
|
#include "test_precomp.hpp" |
|
|
|
namespace opencv_test { namespace { |
|
|
|
class CV_ThreshTest : public cvtest::ArrayTest |
|
{ |
|
public: |
|
CV_ThreshTest(); |
|
|
|
protected: |
|
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types ); |
|
double get_success_error_level( int test_case_idx, int i, int j ); |
|
void run_func(); |
|
void prepare_to_validation( int ); |
|
|
|
int thresh_type; |
|
double thresh_val; |
|
double max_val; |
|
}; |
|
|
|
|
|
CV_ThreshTest::CV_ThreshTest() |
|
{ |
|
test_array[INPUT].push_back(NULL); |
|
test_array[OUTPUT].push_back(NULL); |
|
test_array[REF_OUTPUT].push_back(NULL); |
|
optional_mask = false; |
|
element_wise_relative_error = true; |
|
} |
|
|
|
|
|
void CV_ThreshTest::get_test_array_types_and_sizes( int test_case_idx, |
|
vector<vector<Size> >& sizes, vector<vector<int> >& types ) |
|
{ |
|
RNG& rng = ts->get_rng(); |
|
int depth = cvtest::randInt(rng) % 5, cn = cvtest::randInt(rng) % 4 + 1; |
|
cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types ); |
|
depth = depth == 0 ? CV_8U : depth == 1 ? CV_16S : depth == 2 ? CV_16U : depth == 3 ? CV_32F : CV_64F; |
|
|
|
types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(depth,cn); |
|
thresh_type = cvtest::randInt(rng) % 5; |
|
|
|
if( depth == CV_8U ) |
|
{ |
|
thresh_val = (cvtest::randReal(rng)*350. - 50.); |
|
max_val = (cvtest::randReal(rng)*350. - 50.); |
|
if( cvtest::randInt(rng)%4 == 0 ) |
|
max_val = 255.f; |
|
} |
|
else if( depth == CV_16S ) |
|
{ |
|
double min_val = SHRT_MIN-100.f; |
|
max_val = SHRT_MAX+100.f; |
|
thresh_val = (cvtest::randReal(rng)*(max_val - min_val) + min_val); |
|
max_val = (cvtest::randReal(rng)*(max_val - min_val) + min_val); |
|
if( cvtest::randInt(rng)%4 == 0 ) |
|
max_val = (double)SHRT_MAX; |
|
} |
|
else if( depth == CV_16U ) |
|
{ |
|
double min_val = -100.f; |
|
max_val = USHRT_MAX+100.f; |
|
thresh_val = (cvtest::randReal(rng)*(max_val - min_val) + min_val); |
|
max_val = (cvtest::randReal(rng)*(max_val - min_val) + min_val); |
|
if( cvtest::randInt(rng)%4 == 0 ) |
|
max_val = (double)USHRT_MAX; |
|
} |
|
else |
|
{ |
|
thresh_val = (cvtest::randReal(rng)*1000. - 500.); |
|
max_val = (cvtest::randReal(rng)*1000. - 500.); |
|
} |
|
} |
|
|
|
|
|
double CV_ThreshTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ ) |
|
{ |
|
return FLT_EPSILON*10; |
|
} |
|
|
|
|
|
void CV_ThreshTest::run_func() |
|
{ |
|
cvThreshold( test_array[INPUT][0], test_array[OUTPUT][0], |
|
thresh_val, max_val, thresh_type ); |
|
} |
|
|
|
|
|
static void test_threshold( const Mat& _src, Mat& _dst, |
|
double thresh, double maxval, int thresh_type ) |
|
{ |
|
int i, j; |
|
int depth = _src.depth(), cn = _src.channels(); |
|
int width_n = _src.cols*cn, height = _src.rows; |
|
int ithresh = cvFloor(thresh); |
|
int imaxval, ithresh2; |
|
|
|
if( depth == CV_8U ) |
|
{ |
|
ithresh2 = saturate_cast<uchar>(ithresh); |
|
imaxval = saturate_cast<uchar>(maxval); |
|
} |
|
else if( depth == CV_16S ) |
|
{ |
|
ithresh2 = saturate_cast<short>(ithresh); |
|
imaxval = saturate_cast<short>(maxval); |
|
} |
|
else if( depth == CV_16U ) |
|
{ |
|
ithresh2 = saturate_cast<ushort>(ithresh); |
|
imaxval = saturate_cast<ushort>(maxval); |
|
} |
|
else |
|
{ |
|
ithresh2 = cvRound(ithresh); |
|
imaxval = cvRound(maxval); |
|
} |
|
|
|
CV_Assert( depth == CV_8U || depth == CV_16S || depth == CV_16U || depth == CV_32F || depth == CV_64F ); |
|
|
|
switch( thresh_type ) |
|
{ |
|
case CV_THRESH_BINARY: |
|
for( i = 0; i < height; i++ ) |
|
{ |
|
if( depth == CV_8U ) |
|
{ |
|
const uchar* src = _src.ptr<uchar>(i); |
|
uchar* dst = _dst.ptr<uchar>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
dst[j] = (uchar)(src[j] > ithresh ? imaxval : 0); |
|
} |
|
else if( depth == CV_16S ) |
|
{ |
|
const short* src = _src.ptr<short>(i); |
|
short* dst = _dst.ptr<short>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
dst[j] = (short)(src[j] > ithresh ? imaxval : 0); |
|
} |
|
else if( depth == CV_16U ) |
|
{ |
|
const ushort* src = _src.ptr<ushort>(i); |
|
ushort* dst = _dst.ptr<ushort>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
dst[j] = (ushort)(src[j] > ithresh ? imaxval : 0); |
|
} |
|
else if( depth == CV_32F ) |
|
{ |
|
const float* src = _src.ptr<float>(i); |
|
float* dst = _dst.ptr<float>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
dst[j] = (float)(src[j] > thresh ? maxval : 0.f); |
|
} |
|
else |
|
{ |
|
const double* src = _src.ptr<double>(i); |
|
double* dst = _dst.ptr<double>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
dst[j] = src[j] > thresh ? maxval : 0.0; |
|
} |
|
} |
|
break; |
|
case CV_THRESH_BINARY_INV: |
|
for( i = 0; i < height; i++ ) |
|
{ |
|
if( depth == CV_8U ) |
|
{ |
|
const uchar* src = _src.ptr<uchar>(i); |
|
uchar* dst = _dst.ptr<uchar>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
dst[j] = (uchar)(src[j] > ithresh ? 0 : imaxval); |
|
} |
|
else if( depth == CV_16S ) |
|
{ |
|
const short* src = _src.ptr<short>(i); |
|
short* dst = _dst.ptr<short>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
dst[j] = (short)(src[j] > ithresh ? 0 : imaxval); |
|
} |
|
else if( depth == CV_16U ) |
|
{ |
|
const ushort* src = _src.ptr<ushort>(i); |
|
ushort* dst = _dst.ptr<ushort>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
dst[j] = (ushort)(src[j] > ithresh ? 0 : imaxval); |
|
} |
|
else if( depth == CV_32F ) |
|
{ |
|
const float* src = _src.ptr<float>(i); |
|
float* dst = _dst.ptr<float>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
dst[j] = (float)(src[j] > thresh ? 0.f : maxval); |
|
} |
|
else |
|
{ |
|
const double* src = _src.ptr<double>(i); |
|
double* dst = _dst.ptr<double>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
dst[j] = src[j] > thresh ? 0.0 : maxval; |
|
} |
|
} |
|
break; |
|
case CV_THRESH_TRUNC: |
|
for( i = 0; i < height; i++ ) |
|
{ |
|
if( depth == CV_8U ) |
|
{ |
|
const uchar* src = _src.ptr<uchar>(i); |
|
uchar* dst = _dst.ptr<uchar>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
int s = src[j]; |
|
dst[j] = (uchar)(s > ithresh ? ithresh2 : s); |
|
} |
|
} |
|
else if( depth == CV_16S ) |
|
{ |
|
const short* src = _src.ptr<short>(i); |
|
short* dst = _dst.ptr<short>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
int s = src[j]; |
|
dst[j] = (short)(s > ithresh ? ithresh2 : s); |
|
} |
|
} |
|
else if( depth == CV_16U ) |
|
{ |
|
const ushort* src = _src.ptr<ushort>(i); |
|
ushort* dst = _dst.ptr<ushort>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
int s = src[j]; |
|
dst[j] = (ushort)(s > ithresh ? ithresh2 : s); |
|
} |
|
} |
|
else if( depth == CV_32F ) |
|
{ |
|
const float* src = _src.ptr<float>(i); |
|
float* dst = _dst.ptr<float>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
float s = src[j]; |
|
dst[j] = (float)(s > thresh ? thresh : s); |
|
} |
|
} |
|
else |
|
{ |
|
const double* src = _src.ptr<double>(i); |
|
double* dst = _dst.ptr<double>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
double s = src[j]; |
|
dst[j] = s > thresh ? thresh : s; |
|
} |
|
} |
|
} |
|
break; |
|
case CV_THRESH_TOZERO: |
|
for( i = 0; i < height; i++ ) |
|
{ |
|
if( depth == CV_8U ) |
|
{ |
|
const uchar* src = _src.ptr<uchar>(i); |
|
uchar* dst = _dst.ptr<uchar>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
int s = src[j]; |
|
dst[j] = (uchar)(s > ithresh ? s : 0); |
|
} |
|
} |
|
else if( depth == CV_16S ) |
|
{ |
|
const short* src = _src.ptr<short>(i); |
|
short* dst = _dst.ptr<short>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
int s = src[j]; |
|
dst[j] = (short)(s > ithresh ? s : 0); |
|
} |
|
} |
|
else if( depth == CV_16U ) |
|
{ |
|
const ushort* src = _src.ptr<ushort>(i); |
|
ushort* dst = _dst.ptr<ushort>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
int s = src[j]; |
|
dst[j] = (ushort)(s > ithresh ? s : 0); |
|
} |
|
} |
|
else if( depth == CV_32F ) |
|
{ |
|
const float* src = _src.ptr<float>(i); |
|
float* dst = _dst.ptr<float>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
float s = src[j]; |
|
dst[j] = s > thresh ? s : 0.f; |
|
} |
|
} |
|
else |
|
{ |
|
const double* src = _src.ptr<double>(i); |
|
double* dst = _dst.ptr<double>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
double s = src[j]; |
|
dst[j] = s > thresh ? s : 0.0; |
|
} |
|
} |
|
} |
|
break; |
|
case CV_THRESH_TOZERO_INV: |
|
for( i = 0; i < height; i++ ) |
|
{ |
|
if( depth == CV_8U ) |
|
{ |
|
const uchar* src = _src.ptr<uchar>(i); |
|
uchar* dst = _dst.ptr<uchar>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
int s = src[j]; |
|
dst[j] = (uchar)(s > ithresh ? 0 : s); |
|
} |
|
} |
|
else if( depth == CV_16S ) |
|
{ |
|
const short* src = _src.ptr<short>(i); |
|
short* dst = _dst.ptr<short>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
int s = src[j]; |
|
dst[j] = (short)(s > ithresh ? 0 : s); |
|
} |
|
} |
|
else if( depth == CV_16U ) |
|
{ |
|
const ushort* src = _src.ptr<ushort>(i); |
|
ushort* dst = _dst.ptr<ushort>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
int s = src[j]; |
|
dst[j] = (ushort)(s > ithresh ? 0 : s); |
|
} |
|
} |
|
else if (depth == CV_32F) |
|
{ |
|
const float* src = _src.ptr<float>(i); |
|
float* dst = _dst.ptr<float>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
float s = src[j]; |
|
dst[j] = s > thresh ? 0.f : s; |
|
} |
|
} |
|
else |
|
{ |
|
const double* src = _src.ptr<double>(i); |
|
double* dst = _dst.ptr<double>(i); |
|
for( j = 0; j < width_n; j++ ) |
|
{ |
|
double s = src[j]; |
|
dst[j] = s > thresh ? 0.0 : s; |
|
} |
|
} |
|
} |
|
break; |
|
default: |
|
CV_Assert(0); |
|
} |
|
} |
|
|
|
|
|
void CV_ThreshTest::prepare_to_validation( int /*test_case_idx*/ ) |
|
{ |
|
test_threshold( test_mat[INPUT][0], test_mat[REF_OUTPUT][0], |
|
thresh_val, max_val, thresh_type ); |
|
} |
|
|
|
TEST(Imgproc_Threshold, accuracy) { CV_ThreshTest test; test.safe_run(); } |
|
|
|
BIGDATA_TEST(Imgproc_Threshold, huge) |
|
{ |
|
Mat m(65000, 40000, CV_8U); |
|
ASSERT_FALSE(m.isContinuous()); |
|
|
|
uint64 i, n = (uint64)m.rows*m.cols; |
|
for( i = 0; i < n; i++ ) |
|
m.data[i] = (uchar)(i & 255); |
|
|
|
cv::threshold(m, m, 127, 255, cv::THRESH_BINARY); |
|
int nz = cv::countNonZero(m); // FIXIT 'int' is not enough here (overflow is possible with other inputs) |
|
ASSERT_EQ((uint64)nz, n / 2); |
|
} |
|
|
|
TEST(Imgproc_Threshold, regression_THRESH_TOZERO_IPP_16085) |
|
{ |
|
Size sz(16, 16); |
|
Mat input(sz, CV_32F, Scalar::all(2)); |
|
Mat result; |
|
cv::threshold(input, result, 2.0, 0.0, THRESH_TOZERO); |
|
EXPECT_EQ(0, cv::norm(result, NORM_INF)); |
|
} |
|
|
|
TEST(Imgproc_Threshold, regression_THRESH_TOZERO_IPP_21258) |
|
{ |
|
Size sz(16, 16); |
|
float val = nextafterf(16.0f, 0.0f); // 0x417fffff, all bits in mantissa are 1 |
|
Mat input(sz, CV_32F, Scalar::all(val)); |
|
Mat result; |
|
cv::threshold(input, result, val, 0.0, THRESH_TOZERO); |
|
EXPECT_EQ(0, cv::norm(result, NORM_INF)); |
|
} |
|
|
|
TEST(Imgproc_Threshold, regression_THRESH_TOZERO_IPP_21258_Min) |
|
{ |
|
Size sz(16, 16); |
|
float min_val = -std::numeric_limits<float>::max(); |
|
Mat input(sz, CV_32F, Scalar::all(min_val)); |
|
Mat result; |
|
cv::threshold(input, result, min_val, 0.0, THRESH_TOZERO); |
|
EXPECT_EQ(0, cv::norm(result, NORM_INF)); |
|
} |
|
|
|
TEST(Imgproc_Threshold, regression_THRESH_TOZERO_IPP_21258_Max) |
|
{ |
|
Size sz(16, 16); |
|
float max_val = std::numeric_limits<float>::max(); |
|
Mat input(sz, CV_32F, Scalar::all(max_val)); |
|
Mat result; |
|
cv::threshold(input, result, max_val, 0.0, THRESH_TOZERO); |
|
EXPECT_EQ(0, cv::norm(result, NORM_INF)); |
|
} |
|
|
|
}} // namespace
|
|
|