Open Source Computer Vision Library https://opencv.org/
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#include "test_precomp.hpp"
using namespace cv;
using namespace std;
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;
float thresh_val;
float 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) % 3, 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 : CV_32F;
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 = (float)(cvtest::randReal(rng)*350. - 50.);
max_val = (float)(cvtest::randReal(rng)*350. - 50.);
if( cvtest::randInt(rng)%4 == 0 )
max_val = 255.f;
}
else if( depth == CV_16S )
{
float min_val = SHRT_MIN-100.f;
max_val = SHRT_MAX+100.f;
thresh_val = (float)(cvtest::randReal(rng)*(max_val - min_val) + min_val);
max_val = (float)(cvtest::randReal(rng)*(max_val - min_val) + min_val);
if( cvtest::randInt(rng)%4 == 0 )
max_val = (float)SHRT_MAX;
}
else
{
thresh_val = (float)(cvtest::randReal(rng)*1000. - 500.);
max_val = (float)(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,
float thresh, float 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
{
ithresh2 = cvRound(ithresh);
imaxval = cvRound(maxval);
}
assert( depth == CV_8U || depth == CV_16S || depth == CV_32F );
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
{
const float* src = _src.ptr<float>(i);
float* dst = _dst.ptr<float>(i);
for( j = 0; j < width_n; j++ )
dst[j] = src[j] > thresh ? maxval : 0.f;
}
}
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
{
const float* src = _src.ptr<float>(i);
float* dst = _dst.ptr<float>(i);
for( j = 0; j < width_n; j++ )
dst[j] = src[j] > thresh ? 0.f : 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
{
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 ? 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
{
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;
}
}
}
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
{
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;
}
}
}
break;
default:
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(); }