321 lines
10 KiB
C++
321 lines
10 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of Intel Corporation may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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using namespace cv;
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using namespace std;
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class CV_ThreshTest : public cvtest::ArrayTest
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{
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public:
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CV_ThreshTest();
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protected:
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void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
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double get_success_error_level( int test_case_idx, int i, int j );
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void run_func();
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void prepare_to_validation( int );
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int thresh_type;
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float thresh_val;
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float max_val;
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};
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CV_ThreshTest::CV_ThreshTest()
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{
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test_array[INPUT].push_back(NULL);
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test_array[OUTPUT].push_back(NULL);
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test_array[REF_OUTPUT].push_back(NULL);
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optional_mask = false;
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element_wise_relative_error = true;
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}
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void CV_ThreshTest::get_test_array_types_and_sizes( int test_case_idx,
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vector<vector<Size> >& sizes, vector<vector<int> >& types )
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{
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RNG& rng = ts->get_rng();
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int depth = cvtest::randInt(rng) % 3, cn = cvtest::randInt(rng) % 4 + 1;
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cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
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depth = depth == 0 ? CV_8U : depth == 1 ? CV_16S : CV_32F;
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types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(depth,cn);
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thresh_type = cvtest::randInt(rng) % 5;
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if( depth == CV_8U )
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{
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thresh_val = (float)(cvtest::randReal(rng)*350. - 50.);
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max_val = (float)(cvtest::randReal(rng)*350. - 50.);
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if( cvtest::randInt(rng)%4 == 0 )
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max_val = 255.f;
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}
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else if( depth == CV_16S )
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{
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float min_val = SHRT_MIN-100.f;
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max_val = SHRT_MAX+100.f;
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thresh_val = (float)(cvtest::randReal(rng)*(max_val - min_val) + min_val);
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max_val = (float)(cvtest::randReal(rng)*(max_val - min_val) + min_val);
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if( cvtest::randInt(rng)%4 == 0 )
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max_val = (float)SHRT_MAX;
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}
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else
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{
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thresh_val = (float)(cvtest::randReal(rng)*1000. - 500.);
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max_val = (float)(cvtest::randReal(rng)*1000. - 500.);
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}
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}
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double CV_ThreshTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
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{
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return FLT_EPSILON*10;
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}
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void CV_ThreshTest::run_func()
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{
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cvThreshold( test_array[INPUT][0], test_array[OUTPUT][0],
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thresh_val, max_val, thresh_type );
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}
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static void test_threshold( const Mat& _src, Mat& _dst,
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float thresh, float maxval, int thresh_type )
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{
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int i, j;
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int depth = _src.depth(), cn = _src.channels();
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int width_n = _src.cols*cn, height = _src.rows;
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int ithresh = cvFloor(thresh);
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int imaxval, ithresh2;
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if( depth == CV_8U )
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{
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ithresh2 = saturate_cast<uchar>(ithresh);
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imaxval = saturate_cast<uchar>(maxval);
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}
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else if( depth == CV_16S )
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{
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ithresh2 = saturate_cast<short>(ithresh);
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imaxval = saturate_cast<short>(maxval);
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}
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else
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{
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ithresh2 = cvRound(ithresh);
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imaxval = cvRound(maxval);
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}
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assert( depth == CV_8U || depth == CV_16S || depth == CV_32F );
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switch( thresh_type )
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{
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case CV_THRESH_BINARY:
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for( i = 0; i < height; i++ )
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{
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if( depth == CV_8U )
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{
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const uchar* src = _src.ptr<uchar>(i);
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uchar* dst = _dst.ptr<uchar>(i);
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for( j = 0; j < width_n; j++ )
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dst[j] = (uchar)(src[j] > ithresh ? imaxval : 0);
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}
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else if( depth == CV_16S )
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{
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const short* src = _src.ptr<short>(i);
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short* dst = _dst.ptr<short>(i);
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for( j = 0; j < width_n; j++ )
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dst[j] = (short)(src[j] > ithresh ? imaxval : 0);
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}
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else
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{
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const float* src = _src.ptr<float>(i);
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float* dst = _dst.ptr<float>(i);
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for( j = 0; j < width_n; j++ )
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dst[j] = src[j] > thresh ? maxval : 0.f;
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}
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}
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break;
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case CV_THRESH_BINARY_INV:
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for( i = 0; i < height; i++ )
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{
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if( depth == CV_8U )
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{
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const uchar* src = _src.ptr<uchar>(i);
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uchar* dst = _dst.ptr<uchar>(i);
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for( j = 0; j < width_n; j++ )
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dst[j] = (uchar)(src[j] > ithresh ? 0 : imaxval);
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}
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else if( depth == CV_16S )
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{
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const short* src = _src.ptr<short>(i);
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short* dst = _dst.ptr<short>(i);
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for( j = 0; j < width_n; j++ )
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dst[j] = (short)(src[j] > ithresh ? 0 : imaxval);
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}
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else
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{
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const float* src = _src.ptr<float>(i);
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float* dst = _dst.ptr<float>(i);
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for( j = 0; j < width_n; j++ )
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dst[j] = src[j] > thresh ? 0.f : maxval;
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}
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}
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break;
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case CV_THRESH_TRUNC:
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for( i = 0; i < height; i++ )
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{
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if( depth == CV_8U )
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{
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const uchar* src = _src.ptr<uchar>(i);
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uchar* dst = _dst.ptr<uchar>(i);
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for( j = 0; j < width_n; j++ )
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{
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int s = src[j];
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dst[j] = (uchar)(s > ithresh ? ithresh2 : s);
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}
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}
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else if( depth == CV_16S )
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{
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const short* src = _src.ptr<short>(i);
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short* dst = _dst.ptr<short>(i);
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for( j = 0; j < width_n; j++ )
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{
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int s = src[j];
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dst[j] = (short)(s > ithresh ? ithresh2 : s);
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}
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}
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else
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{
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const float* src = _src.ptr<float>(i);
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float* dst = _dst.ptr<float>(i);
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for( j = 0; j < width_n; j++ )
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{
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float s = src[j];
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dst[j] = s > thresh ? thresh : s;
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}
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}
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}
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break;
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case CV_THRESH_TOZERO:
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for( i = 0; i < height; i++ )
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{
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if( depth == CV_8U )
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{
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const uchar* src = _src.ptr<uchar>(i);
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uchar* dst = _dst.ptr<uchar>(i);
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for( j = 0; j < width_n; j++ )
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{
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int s = src[j];
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dst[j] = (uchar)(s > ithresh ? s : 0);
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}
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}
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else if( depth == CV_16S )
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{
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const short* src = _src.ptr<short>(i);
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short* dst = _dst.ptr<short>(i);
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for( j = 0; j < width_n; j++ )
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{
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int s = src[j];
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dst[j] = (short)(s > ithresh ? s : 0);
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}
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}
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else
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{
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const float* src = _src.ptr<float>(i);
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float* dst = _dst.ptr<float>(i);
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for( j = 0; j < width_n; j++ )
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{
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float s = src[j];
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dst[j] = s > thresh ? s : 0.f;
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}
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}
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}
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break;
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case CV_THRESH_TOZERO_INV:
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for( i = 0; i < height; i++ )
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{
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if( depth == CV_8U )
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{
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const uchar* src = _src.ptr<uchar>(i);
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uchar* dst = _dst.ptr<uchar>(i);
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for( j = 0; j < width_n; j++ )
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{
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int s = src[j];
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dst[j] = (uchar)(s > ithresh ? 0 : s);
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}
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}
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else if( depth == CV_16S )
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{
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const short* src = _src.ptr<short>(i);
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short* dst = _dst.ptr<short>(i);
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for( j = 0; j < width_n; j++ )
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{
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int s = src[j];
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dst[j] = (short)(s > ithresh ? 0 : s);
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}
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}
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else
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{
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const float* src = _src.ptr<float>(i);
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float* dst = _dst.ptr<float>(i);
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for( j = 0; j < width_n; j++ )
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{
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float s = src[j];
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dst[j] = s > thresh ? 0.f : s;
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}
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}
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}
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break;
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default:
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assert(0);
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}
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}
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void CV_ThreshTest::prepare_to_validation( int /*test_case_idx*/ )
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{
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test_threshold( test_mat[INPUT][0], test_mat[REF_OUTPUT][0],
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thresh_val, max_val, thresh_type );
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}
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TEST(Imgproc_Threshold, accuracy) { CV_ThreshTest test; test.safe_run(); }
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