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