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299 lines
11 KiB
C++
299 lines
11 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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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., 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 the copyright holders 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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namespace opencv_test { namespace {
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#define CORE_COUNTNONZERO_ERROR_COUNT 1
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#define MESSAGE_ERROR_COUNT "Count non zero elements returned by OpenCV function is incorrect."
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#define sign(a) a > 0 ? 1 : a == 0 ? 0 : -1
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#define MAX_WIDTH 100
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#define MAX_HEIGHT 100
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class CV_CountNonZeroTest: public cvtest::BaseTest
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{
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public:
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CV_CountNonZeroTest();
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~CV_CountNonZeroTest();
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protected:
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void run (int);
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private:
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float eps_32;
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double eps_64;
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Mat src;
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int current_type;
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void generate_src_data(cv::Size size, int type);
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void generate_src_data(cv::Size size, int type, int count_non_zero);
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void generate_src_stat_data(cv::Size size, int type, int distribution);
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int get_count_non_zero();
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void print_information(int right, int result);
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};
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CV_CountNonZeroTest::CV_CountNonZeroTest(): eps_32(std::numeric_limits<float>::min()), eps_64(std::numeric_limits<double>::min()), src(Mat()), current_type(-1) {}
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CV_CountNonZeroTest::~CV_CountNonZeroTest() {}
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void CV_CountNonZeroTest::generate_src_data(cv::Size size, int type)
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{
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src.create(size, CV_MAKETYPE(type, 1));
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for (int j = 0; j < size.width; ++j)
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for (int i = 0; i < size.height; ++i)
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switch (type)
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{
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case CV_8U: { src.at<uchar>(i, j) = cv::randu<uchar>(); break; }
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case CV_8S: { src.at<char>(i, j) = cv::randu<uchar>() - 128; break; }
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case CV_16U: { src.at<ushort>(i, j) = cv::randu<ushort>(); break; }
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case CV_16S: { src.at<short>(i, j) = cv::randu<short>(); break; }
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case CV_32S: { src.at<int>(i, j) = cv::randu<int>(); break; }
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case CV_32F: { src.at<float>(i, j) = cv::randu<float>(); break; }
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case CV_64F: { src.at<double>(i, j) = cv::randu<double>(); break; }
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default: break;
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}
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}
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void CV_CountNonZeroTest::generate_src_data(cv::Size size, int type, int count_non_zero)
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{
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src = Mat::zeros(size, CV_MAKETYPE(type, 1));
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int n = 0; RNG& rng = ts->get_rng();
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while (n < count_non_zero)
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{
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int i = rng.next()%size.height, j = rng.next()%size.width;
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switch (type)
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{
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case CV_8U: { if (!src.at<uchar>(i, j)) {src.at<uchar>(i, j) = cv::randu<uchar>(); n += (src.at<uchar>(i, j) > 0);} break; }
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case CV_8S: { if (!src.at<char>(i, j)) {src.at<char>(i, j) = cv::randu<uchar>() - 128; n += abs(sign(src.at<char>(i, j)));} break; }
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case CV_16U: { if (!src.at<ushort>(i, j)) {src.at<ushort>(i, j) = cv::randu<ushort>(); n += (src.at<ushort>(i, j) > 0);} break; }
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case CV_16S: { if (!src.at<short>(i, j)) {src.at<short>(i, j) = cv::randu<short>(); n += abs(sign(src.at<short>(i, j)));} break; }
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case CV_32S: { if (!src.at<int>(i, j)) {src.at<int>(i, j) = cv::randu<int>(); n += abs(sign(src.at<int>(i, j)));} break; }
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case CV_32F: { if (fabs(src.at<float>(i, j)) <= eps_32) {src.at<float>(i, j) = cv::randu<float>(); n += (fabs(src.at<float>(i, j)) > eps_32);} break; }
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case CV_64F: { if (fabs(src.at<double>(i, j)) <= eps_64) {src.at<double>(i, j) = cv::randu<double>(); n += (fabs(src.at<double>(i, j)) > eps_64);} break; }
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default: break;
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}
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}
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}
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void CV_CountNonZeroTest::generate_src_stat_data(cv::Size size, int type, int distribution)
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{
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src.create(size, CV_MAKETYPE(type, 1));
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double mean = 0.0, sigma = 1.0;
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double left = -1.0, right = 1.0;
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RNG& rng = ts->get_rng();
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if (distribution == RNG::NORMAL)
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rng.fill(src, RNG::NORMAL, Scalar::all(mean), Scalar::all(sigma));
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else if (distribution == RNG::UNIFORM)
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rng.fill(src, RNG::UNIFORM, Scalar::all(left), Scalar::all(right));
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}
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int CV_CountNonZeroTest::get_count_non_zero()
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{
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int result = 0;
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for (int i = 0; i < src.rows; ++i)
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for (int j = 0; j < src.cols; ++j)
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{
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if (current_type == CV_8U) result += (src.at<uchar>(i, j) > 0);
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else if (current_type == CV_8S) result += abs(sign(src.at<char>(i, j)));
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else if (current_type == CV_16U) result += (src.at<ushort>(i, j) > 0);
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else if (current_type == CV_16S) result += abs(sign(src.at<short>(i, j)));
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else if (current_type == CV_32S) result += abs(sign(src.at<int>(i, j)));
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else if (current_type == CV_32F) result += (fabs(src.at<float>(i, j)) > eps_32);
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else result += (fabs(src.at<double>(i, j)) > eps_64);
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}
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return result;
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}
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void CV_CountNonZeroTest::print_information(int right, int result)
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{
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cout << endl; cout << "Checking for the work of countNonZero function..." << endl; cout << endl;
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cout << "Type of Mat: ";
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switch (current_type)
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{
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case 0: {cout << "CV_8U"; break;}
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case 1: {cout << "CV_8S"; break;}
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case 2: {cout << "CV_16U"; break;}
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case 3: {cout << "CV_16S"; break;}
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case 4: {cout << "CV_32S"; break;}
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case 5: {cout << "CV_32F"; break;}
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case 6: {cout << "CV_64F"; break;}
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default: break;
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}
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cout << endl;
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cout << "Number of rows: " << src.rows << " Number of cols: " << src.cols << endl;
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cout << "True count non zero elements: " << right << " Result: " << result << endl;
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cout << endl;
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}
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void CV_CountNonZeroTest::run(int)
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{
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const size_t N = 1500;
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for (int k = 1; k <= 3; ++k)
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for (size_t i = 0; i < N; ++i)
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{
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RNG& rng = ts->get_rng();
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int w = rng.next()%MAX_WIDTH + 1, h = rng.next()%MAX_HEIGHT + 1;
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current_type = rng.next()%7;
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switch (k)
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{
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case 1: {
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generate_src_data(Size(w, h), current_type);
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int right = get_count_non_zero(), result = countNonZero(src);
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if (result != right)
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{
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cout << "Number of experiment: " << i << endl;
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cout << "Method of data generation: RANDOM" << endl;
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print_information(right, result);
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CV_Error(CORE_COUNTNONZERO_ERROR_COUNT, MESSAGE_ERROR_COUNT);
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return;
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}
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break;
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}
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case 2: {
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int count_non_zero = rng.next()%(w*h);
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generate_src_data(Size(w, h), current_type, count_non_zero);
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int result = countNonZero(src);
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if (result != count_non_zero)
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{
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cout << "Number of experiment: " << i << endl;
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cout << "Method of data generation: HALF-RANDOM" << endl;
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print_information(count_non_zero, result);
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CV_Error(CORE_COUNTNONZERO_ERROR_COUNT, MESSAGE_ERROR_COUNT);
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return;
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}
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break;
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}
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case 3: {
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int distribution = cv::randu<uchar>()%2;
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generate_src_stat_data(Size(w, h), current_type, distribution);
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int right = get_count_non_zero(), result = countNonZero(src);
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if (right != result)
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{
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cout << "Number of experiment: " << i << endl;
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cout << "Method of data generation: STATISTIC" << endl;
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print_information(right, result);
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CV_Error(CORE_COUNTNONZERO_ERROR_COUNT, MESSAGE_ERROR_COUNT);
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return;
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}
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break;
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}
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default: break;
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}
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}
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}
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TEST (Core_CountNonZero, accuracy) { CV_CountNonZeroTest test; test.safe_run(); }
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typedef testing::TestWithParam<tuple<int, int> > CountNonZeroND;
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TEST_P (CountNonZeroND, ndim)
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{
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const int dims = get<0>(GetParam());
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const int type = get<1>(GetParam());
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const int ONE_SIZE = 5;
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vector<int> sizes(dims);
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fill(sizes.begin(), sizes.end(), ONE_SIZE);
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Mat data(sizes, CV_MAKETYPE(type, 1));
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data = 0;
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EXPECT_EQ(0, cv::countNonZero(data));
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data = Scalar::all(1);
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int expected = static_cast<int>(pow(static_cast<float>(ONE_SIZE), dims));
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EXPECT_EQ(expected, cv::countNonZero(data));
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}
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INSTANTIATE_TEST_CASE_P(Core, CountNonZeroND,
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testing::Combine(
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testing::Range(2, 9),
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testing::Values(CV_8U, CV_8S, CV_32F)
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)
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);
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typedef testing::TestWithParam<tuple<int, cv::Size> > CountNonZeroBig;
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TEST_P(CountNonZeroBig, /**/)
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{
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const int type = get<0>(GetParam());
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const Size sz = get<1>(GetParam());
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EXPECT_EQ(0, cv::countNonZero(cv::Mat::zeros(sz, type)));
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EXPECT_EQ(sz.area(), cv::countNonZero(cv::Mat::ones(sz, type)));
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}
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INSTANTIATE_TEST_CASE_P(Core, CountNonZeroBig,
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testing::Combine(
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testing::Values(CV_8UC1, CV_32FC1),
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testing::Values(Size(1, 524190), Size(524190, 1), Size(3840, 2160))
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)
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);
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}} // namespace
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