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928 lines
32 KiB
928 lines
32 KiB
/*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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using namespace cv; |
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using namespace std; |
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class CV_DefaultNewCameraMatrixTest : public cvtest::ArrayTest |
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{ |
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public: |
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CV_DefaultNewCameraMatrixTest(); |
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protected: |
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int prepare_test_case (int test_case_idx); |
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void prepare_to_validation( int test_case_idx ); |
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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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void run_func(); |
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private: |
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cv::Size img_size; |
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cv::Mat camera_mat; |
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cv::Mat new_camera_mat; |
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int matrix_type; |
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bool center_principal_point; |
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static const int MAX_X = 2048; |
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static const int MAX_Y = 2048; |
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static const int MAX_VAL = 10000; |
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}; |
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CV_DefaultNewCameraMatrixTest::CV_DefaultNewCameraMatrixTest() |
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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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} |
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void CV_DefaultNewCameraMatrixTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types ) |
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{ |
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cvtest::ArrayTest::get_test_array_types_and_sizes(test_case_idx,sizes,types); |
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RNG& rng = ts->get_rng(); |
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matrix_type = types[INPUT][0] = types[OUTPUT][0]= types[REF_OUTPUT][0] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; |
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sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(3,3); |
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} |
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int CV_DefaultNewCameraMatrixTest::prepare_test_case(int test_case_idx) |
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{ |
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int code = cvtest::ArrayTest::prepare_test_case( test_case_idx ); |
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if (code <= 0) |
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return code; |
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RNG& rng = ts->get_rng(); |
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img_size.width = cvtest::randInt(rng) % MAX_X + 1; |
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img_size.height = cvtest::randInt(rng) % MAX_Y + 1; |
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center_principal_point = ((cvtest::randInt(rng) % 2)!=0); |
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// Generating camera_mat matrix |
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double sz = MAX(img_size.width, img_size.height); |
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double aspect_ratio = cvtest::randReal(rng)*0.6 + 0.7; |
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double a[9] = {0,0,0,0,0,0,0,0,1}; |
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Mat _a(3,3,CV_64F,a); |
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a[2] = (img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5; |
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a[5] = (img_size.height - 1)*0.5 + cvtest::randReal(rng)*10 - 5; |
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a[0] = sz/(0.9 - cvtest::randReal(rng)*0.6); |
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a[4] = aspect_ratio*a[0]; |
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Mat& _a0 = test_mat[INPUT][0]; |
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cvtest::convert(_a, _a0, _a0.type()); |
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camera_mat = _a0; |
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return code; |
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} |
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void CV_DefaultNewCameraMatrixTest::run_func() |
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{ |
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new_camera_mat = cv::getDefaultNewCameraMatrix(camera_mat,img_size,center_principal_point); |
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} |
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void CV_DefaultNewCameraMatrixTest::prepare_to_validation( int /*test_case_idx*/ ) |
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{ |
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const Mat& src = test_mat[INPUT][0]; |
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Mat& dst = test_mat[REF_OUTPUT][0]; |
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Mat& test_output = test_mat[OUTPUT][0]; |
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Mat& output = new_camera_mat; |
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cvtest::convert( output, test_output, test_output.type() ); |
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if (!center_principal_point) |
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{ |
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cvtest::copy(src, dst); |
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} |
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else |
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{ |
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double a[9] = {0,0,0,0,0,0,0,0,1}; |
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Mat _a(3,3,CV_64F,a); |
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if (matrix_type == CV_64F) |
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{ |
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a[0] = src.at<double>(0,0); |
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a[4] = src.at<double>(1,1); |
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} |
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else |
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{ |
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a[0] = src.at<float>(0,0); |
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a[4] = src.at<float>(1,1); |
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} |
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a[2] = (img_size.width - 1)*0.5; |
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a[5] = (img_size.height - 1)*0.5; |
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cvtest::convert( _a, dst, dst.type() ); |
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} |
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} |
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//--------- |
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class CV_UndistortPointsTest : public cvtest::ArrayTest |
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{ |
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public: |
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CV_UndistortPointsTest(); |
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protected: |
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int prepare_test_case (int test_case_idx); |
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void prepare_to_validation( int test_case_idx ); |
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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 distortPoints(const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatrix, |
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const CvMat* _distCoeffs, const CvMat* matR, const CvMat* matP); |
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private: |
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bool useCPlus; |
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bool useDstMat; |
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static const int N_POINTS = 10; |
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static const int MAX_X = 2048; |
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static const int MAX_Y = 2048; |
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bool zero_new_cam; |
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bool zero_distortion; |
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bool zero_R; |
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cv::Size img_size; |
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cv::Mat dst_points_mat; |
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cv::Mat camera_mat; |
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cv::Mat R; |
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cv::Mat P; |
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cv::Mat distortion_coeffs; |
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cv::Mat src_points; |
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std::vector<cv::Point2f> dst_points; |
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}; |
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CV_UndistortPointsTest::CV_UndistortPointsTest() |
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{ |
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test_array[INPUT].push_back(NULL); // points matrix |
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test_array[INPUT].push_back(NULL); // camera matrix |
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test_array[INPUT].push_back(NULL); // distortion coeffs |
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test_array[INPUT].push_back(NULL); // R matrix |
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test_array[INPUT].push_back(NULL); // P matrix |
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test_array[OUTPUT].push_back(NULL); // distorted dst points |
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test_array[TEMP].push_back(NULL); // dst points |
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test_array[REF_OUTPUT].push_back(NULL); |
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} |
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void CV_UndistortPointsTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types ) |
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{ |
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cvtest::ArrayTest::get_test_array_types_and_sizes(test_case_idx,sizes,types); |
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RNG& rng = ts->get_rng(); |
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useCPlus = ((cvtest::randInt(rng) % 2)!=0); |
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//useCPlus = 0; |
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if (useCPlus) |
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{ |
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types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0]= CV_32FC2; |
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} |
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else |
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{ |
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types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0]= cvtest::randInt(rng)%2 ? CV_64FC2 : CV_32FC2; |
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} |
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types[INPUT][1] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; |
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types[INPUT][2] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; |
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types[INPUT][3] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; |
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types[INPUT][4] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; |
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sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = sizes[TEMP][0]= cvtest::randInt(rng)%2 ? cvSize(1,N_POINTS) : cvSize(N_POINTS,1); |
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sizes[INPUT][1] = sizes[INPUT][3] = cvSize(3,3); |
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sizes[INPUT][4] = cvtest::randInt(rng)%2 ? cvSize(3,3) : cvSize(4,3); |
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if (cvtest::randInt(rng)%2) |
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{ |
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if (cvtest::randInt(rng)%2) |
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{ |
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sizes[INPUT][2] = cvSize(1,4); |
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} |
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else |
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{ |
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sizes[INPUT][2] = cvSize(1,5); |
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} |
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} |
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else |
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{ |
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if (cvtest::randInt(rng)%2) |
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{ |
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sizes[INPUT][2] = cvSize(4,1); |
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} |
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else |
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{ |
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sizes[INPUT][2] = cvSize(5,1); |
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} |
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} |
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} |
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int CV_UndistortPointsTest::prepare_test_case(int test_case_idx) |
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{ |
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RNG& rng = ts->get_rng(); |
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int code = cvtest::ArrayTest::prepare_test_case( test_case_idx ); |
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if (code <= 0) |
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return code; |
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useDstMat = (cvtest::randInt(rng) % 2) == 0; |
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img_size.width = cvtest::randInt(rng) % MAX_X + 1; |
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img_size.height = cvtest::randInt(rng) % MAX_Y + 1; |
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int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows; |
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double cam[9] = {0,0,0,0,0,0,0,0,1}; |
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vector<double> dist(dist_size); |
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vector<double> proj(test_mat[INPUT][4].cols * test_mat[INPUT][4].rows); |
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vector<Point2d> points(N_POINTS); |
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Mat _camera(3,3,CV_64F,cam); |
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Mat _distort(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,&dist[0]); |
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Mat _proj(test_mat[INPUT][4].size(), CV_64F, &proj[0]); |
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Mat _points(test_mat[INPUT][0].size(), CV_64FC2, &points[0]); |
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_proj = Scalar::all(0); |
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//Generating points |
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for( int i = 0; i < N_POINTS; i++ ) |
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{ |
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points[i].x = cvtest::randReal(rng)*img_size.width; |
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points[i].y = cvtest::randReal(rng)*img_size.height; |
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} |
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//Generating camera matrix |
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double sz = MAX(img_size.width,img_size.height); |
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double aspect_ratio = cvtest::randReal(rng)*0.6 + 0.7; |
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cam[2] = (img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5; |
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cam[5] = (img_size.height - 1)*0.5 + cvtest::randReal(rng)*10 - 5; |
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cam[0] = sz/(0.9 - cvtest::randReal(rng)*0.6); |
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cam[4] = aspect_ratio*cam[0]; |
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//Generating distortion coeffs |
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dist[0] = cvtest::randReal(rng)*0.06 - 0.03; |
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dist[1] = cvtest::randReal(rng)*0.06 - 0.03; |
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if( dist[0]*dist[1] > 0 ) |
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dist[1] = -dist[1]; |
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if( cvtest::randInt(rng)%4 != 0 ) |
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{ |
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dist[2] = cvtest::randReal(rng)*0.004 - 0.002; |
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dist[3] = cvtest::randReal(rng)*0.004 - 0.002; |
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if (dist_size > 4) |
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dist[4] = cvtest::randReal(rng)*0.004 - 0.002; |
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} |
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else |
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{ |
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dist[2] = dist[3] = 0; |
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if (dist_size > 4) |
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dist[4] = 0; |
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} |
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//Generating P matrix (projection) |
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if( test_mat[INPUT][4].cols != 4 ) |
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{ |
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proj[8] = 1; |
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if (cvtest::randInt(rng)%2 == 0) // use identity new camera matrix |
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{ |
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proj[0] = 1; |
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proj[4] = 1; |
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} |
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else |
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{ |
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proj[0] = cam[0] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[0]; //10% |
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proj[4] = cam[4] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[4]; //10% |
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proj[2] = cam[2] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.width; //15% |
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proj[5] = cam[5] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.height; //15% |
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} |
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} |
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else |
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{ |
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proj[10] = 1; |
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proj[0] = cam[0] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[0]; //10% |
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proj[5] = cam[4] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[4]; //10% |
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proj[2] = cam[2] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.width; //15% |
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proj[6] = cam[5] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.height; //15% |
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proj[3] = (img_size.height + img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5; |
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proj[7] = (img_size.height + img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5; |
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proj[11] = (img_size.height + img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5; |
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} |
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//Generating R matrix |
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Mat _rot(3,3,CV_64F); |
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Mat rotation(1,3,CV_64F); |
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rotation.at<double>(0) = CV_PI*(cvtest::randReal(rng) - (double)0.5); // phi |
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rotation.at<double>(1) = CV_PI*(cvtest::randReal(rng) - (double)0.5); // ksi |
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rotation.at<double>(2) = CV_PI*(cvtest::randReal(rng) - (double)0.5); //khi |
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cvtest::Rodrigues(rotation, _rot); |
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//copying data |
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//src_points = &_points; |
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_points.convertTo(test_mat[INPUT][0], test_mat[INPUT][0].type()); |
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_camera.convertTo(test_mat[INPUT][1], test_mat[INPUT][1].type()); |
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_distort.convertTo(test_mat[INPUT][2], test_mat[INPUT][2].type()); |
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_rot.convertTo(test_mat[INPUT][3], test_mat[INPUT][3].type()); |
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_proj.convertTo(test_mat[INPUT][4], test_mat[INPUT][4].type()); |
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zero_distortion = (cvtest::randInt(rng)%2) == 0 ? false : true; |
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zero_new_cam = (cvtest::randInt(rng)%2) == 0 ? false : true; |
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zero_R = (cvtest::randInt(rng)%2) == 0 ? false : true; |
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if (useCPlus) |
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{ |
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_points.convertTo(src_points, CV_32F); |
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camera_mat = test_mat[INPUT][1]; |
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distortion_coeffs = test_mat[INPUT][2]; |
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R = test_mat[INPUT][3]; |
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P = test_mat[INPUT][4]; |
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} |
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return code; |
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} |
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void CV_UndistortPointsTest::prepare_to_validation(int /*test_case_idx*/) |
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{ |
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int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows; |
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double cam[9] = {0,0,0,0,0,0,0,0,1}; |
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double rot[9] = {1,0,0,0,1,0,0,0,1}; |
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double* dist = new double[dist_size ]; |
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double* proj = new double[test_mat[INPUT][4].cols * test_mat[INPUT][4].rows]; |
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double* points = new double[N_POINTS*2]; |
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double* r_points = new double[N_POINTS*2]; |
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//Run reference calculations |
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CvMat ref_points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,r_points); |
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CvMat _camera = cvMat(3,3,CV_64F,cam); |
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CvMat _rot = cvMat(3,3,CV_64F,rot); |
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CvMat _distort = cvMat(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,dist); |
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CvMat _proj = cvMat(test_mat[INPUT][4].rows,test_mat[INPUT][4].cols,CV_64F,proj); |
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CvMat _points= cvMat(test_mat[TEMP][0].rows,test_mat[TEMP][0].cols,CV_64FC2,points); |
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Mat __camera = cvarrToMat(&_camera); |
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Mat __distort = cvarrToMat(&_distort); |
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Mat __rot = cvarrToMat(&_rot); |
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Mat __proj = cvarrToMat(&_proj); |
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Mat __points = cvarrToMat(&_points); |
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Mat _ref_points = cvarrToMat(&ref_points); |
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cvtest::convert(test_mat[INPUT][1], __camera, __camera.type()); |
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cvtest::convert(test_mat[INPUT][2], __distort, __distort.type()); |
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cvtest::convert(test_mat[INPUT][3], __rot, __rot.type()); |
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cvtest::convert(test_mat[INPUT][4], __proj, __proj.type()); |
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if (useCPlus) |
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{ |
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if (useDstMat) |
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{ |
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CvMat temp = dst_points_mat; |
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for (int i=0;i<N_POINTS*2;i++) |
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{ |
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points[i] = temp.data.fl[i]; |
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} |
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} |
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else |
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{ |
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for (int i=0;i<N_POINTS;i++) |
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{ |
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points[2*i] = dst_points[i].x; |
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points[2*i+1] = dst_points[i].y; |
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} |
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} |
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} |
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else |
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{ |
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cvtest::convert(test_mat[TEMP][0],__points, __points.type()); |
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} |
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CvMat* input2 = zero_distortion ? 0 : &_distort; |
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CvMat* input3 = zero_R ? 0 : &_rot; |
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CvMat* input4 = zero_new_cam ? 0 : &_proj; |
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distortPoints(&_points,&ref_points,&_camera,input2,input3,input4); |
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Mat& dst = test_mat[REF_OUTPUT][0]; |
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cvtest::convert(_ref_points, dst, dst.type()); |
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cvtest::copy(test_mat[INPUT][0], test_mat[OUTPUT][0]); |
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delete[] dist; |
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delete[] proj; |
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delete[] points; |
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delete[] r_points; |
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} |
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void CV_UndistortPointsTest::run_func() |
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{ |
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if (useCPlus) |
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{ |
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cv::Mat input2,input3,input4; |
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input2 = zero_distortion ? cv::Mat() : cv::Mat(test_mat[INPUT][2]); |
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input3 = zero_R ? cv::Mat() : cv::Mat(test_mat[INPUT][3]); |
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input4 = zero_new_cam ? cv::Mat() : cv::Mat(test_mat[INPUT][4]); |
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if (useDstMat) |
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{ |
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//cv::undistortPoints(src_points,dst_points_mat,camera_mat,distortion_coeffs,R,P); |
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cv::undistortPoints(src_points,dst_points_mat,camera_mat,input2,input3,input4); |
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} |
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else |
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{ |
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//cv::undistortPoints(src_points,dst_points,camera_mat,distortion_coeffs,R,P); |
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cv::undistortPoints(src_points,dst_points,camera_mat,input2,input3,input4); |
|
} |
|
} |
|
else |
|
{ |
|
CvMat _input0 = test_mat[INPUT][0], _input1 = test_mat[INPUT][1], _input2, _input3, _input4; |
|
CvMat _output = test_mat[TEMP][0]; |
|
if(!zero_distortion) |
|
_input2 = test_mat[INPUT][2]; |
|
if(!zero_R) |
|
_input3 = test_mat[INPUT][3]; |
|
if(!zero_new_cam) |
|
_input4 = test_mat[INPUT][4]; |
|
cvUndistortPoints(&_input0, &_output, &_input1, |
|
zero_distortion ? 0 : &_input2, |
|
zero_R ? 0 : &_input3, |
|
zero_new_cam ? 0 : &_input4); |
|
} |
|
} |
|
|
|
void CV_UndistortPointsTest::distortPoints(const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatrix, |
|
const CvMat* _distCoeffs, |
|
const CvMat* matR, const CvMat* matP) |
|
{ |
|
double a[9]; |
|
|
|
CvMat* __P; |
|
if ((!matP)||(matP->cols == 3)) |
|
__P = cvCreateMat(3,3,CV_64F); |
|
else |
|
__P = cvCreateMat(3,4,CV_64F); |
|
if (matP) |
|
{ |
|
cvtest::convert(cvarrToMat(matP), cvarrToMat(__P), -1); |
|
} |
|
else |
|
{ |
|
cvZero(__P); |
|
__P->data.db[0] = 1; |
|
__P->data.db[4] = 1; |
|
__P->data.db[8] = 1; |
|
} |
|
CvMat* __R = cvCreateMat(3,3,CV_64F); |
|
if (matR) |
|
{ |
|
cvCopy(matR,__R); |
|
} |
|
else |
|
{ |
|
cvZero(__R); |
|
__R->data.db[0] = 1; |
|
__R->data.db[4] = 1; |
|
__R->data.db[8] = 1; |
|
} |
|
for (int i=0;i<N_POINTS;i++) |
|
{ |
|
int movement = __P->cols > 3 ? 1 : 0; |
|
double x = (_src->data.db[2*i]-__P->data.db[2])/__P->data.db[0]; |
|
double y = (_src->data.db[2*i+1]-__P->data.db[5+movement])/__P->data.db[4+movement]; |
|
CvMat inverse = cvMat(3,3,CV_64F,a); |
|
cvInvert(__R,&inverse); |
|
double w1 = x*inverse.data.db[6]+y*inverse.data.db[7]+inverse.data.db[8]; |
|
double _x = (x*inverse.data.db[0]+y*inverse.data.db[1]+inverse.data.db[2])/w1; |
|
double _y = (x*inverse.data.db[3]+y*inverse.data.db[4]+inverse.data.db[5])/w1; |
|
|
|
//Distortions |
|
|
|
double __x = _x; |
|
double __y = _y; |
|
if (_distCoeffs) |
|
{ |
|
double r2 = _x*_x+_y*_y; |
|
|
|
__x = _x*(1+_distCoeffs->data.db[0]*r2+_distCoeffs->data.db[1]*r2*r2)+ |
|
2*_distCoeffs->data.db[2]*_x*_y+_distCoeffs->data.db[3]*(r2+2*_x*_x); |
|
__y = _y*(1+_distCoeffs->data.db[0]*r2+_distCoeffs->data.db[1]*r2*r2)+ |
|
2*_distCoeffs->data.db[3]*_x*_y+_distCoeffs->data.db[2]*(r2+2*_y*_y); |
|
if ((_distCoeffs->cols > 4) || (_distCoeffs->rows > 4)) |
|
{ |
|
__x+=_x*_distCoeffs->data.db[4]*r2*r2*r2; |
|
__y+=_y*_distCoeffs->data.db[4]*r2*r2*r2; |
|
} |
|
} |
|
|
|
|
|
_dst->data.db[2*i] = __x*_cameraMatrix->data.db[0]+_cameraMatrix->data.db[2]; |
|
_dst->data.db[2*i+1] = __y*_cameraMatrix->data.db[4]+_cameraMatrix->data.db[5]; |
|
|
|
} |
|
|
|
cvReleaseMat(&__R); |
|
cvReleaseMat(&__P); |
|
|
|
} |
|
|
|
|
|
double CV_UndistortPointsTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ ) |
|
{ |
|
return 5e-2; |
|
} |
|
|
|
//------------------------------------------------------ |
|
|
|
class CV_InitUndistortRectifyMapTest : public cvtest::ArrayTest |
|
{ |
|
public: |
|
CV_InitUndistortRectifyMapTest(); |
|
protected: |
|
int prepare_test_case (int test_case_idx); |
|
void prepare_to_validation( int test_case_idx ); |
|
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(); |
|
|
|
private: |
|
bool useCPlus; |
|
static const int N_POINTS = 100; |
|
static const int MAX_X = 2048; |
|
static const int MAX_Y = 2048; |
|
bool zero_new_cam; |
|
bool zero_distortion; |
|
bool zero_R; |
|
|
|
|
|
cv::Size img_size; |
|
|
|
cv::Mat camera_mat; |
|
cv::Mat R; |
|
cv::Mat new_camera_mat; |
|
cv::Mat distortion_coeffs; |
|
cv::Mat mapx; |
|
cv::Mat mapy; |
|
CvMat* _mapx; |
|
CvMat* _mapy; |
|
int mat_type; |
|
}; |
|
|
|
CV_InitUndistortRectifyMapTest::CV_InitUndistortRectifyMapTest() |
|
{ |
|
test_array[INPUT].push_back(NULL); // test points matrix |
|
test_array[INPUT].push_back(NULL); // camera matrix |
|
test_array[INPUT].push_back(NULL); // distortion coeffs |
|
test_array[INPUT].push_back(NULL); // R matrix |
|
test_array[INPUT].push_back(NULL); // new camera matrix |
|
test_array[OUTPUT].push_back(NULL); // distorted dst points |
|
test_array[REF_OUTPUT].push_back(NULL); |
|
} |
|
|
|
void CV_InitUndistortRectifyMapTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types ) |
|
{ |
|
cvtest::ArrayTest::get_test_array_types_and_sizes(test_case_idx,sizes,types); |
|
RNG& rng = ts->get_rng(); |
|
useCPlus = ((cvtest::randInt(rng) % 2)!=0); |
|
//useCPlus = 0; |
|
types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC2; |
|
|
|
types[INPUT][1] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; |
|
types[INPUT][2] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; |
|
types[INPUT][3] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; |
|
types[INPUT][4] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F; |
|
|
|
sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(N_POINTS,1); |
|
sizes[INPUT][1] = sizes[INPUT][3] = cvSize(3,3); |
|
sizes[INPUT][4] = cvSize(3,3); |
|
|
|
if (cvtest::randInt(rng)%2) |
|
{ |
|
if (cvtest::randInt(rng)%2) |
|
{ |
|
sizes[INPUT][2] = cvSize(1,4); |
|
} |
|
else |
|
{ |
|
sizes[INPUT][2] = cvSize(1,5); |
|
} |
|
} |
|
else |
|
{ |
|
if (cvtest::randInt(rng)%2) |
|
{ |
|
sizes[INPUT][2] = cvSize(4,1); |
|
} |
|
else |
|
{ |
|
sizes[INPUT][2] = cvSize(5,1); |
|
} |
|
} |
|
} |
|
|
|
|
|
int CV_InitUndistortRectifyMapTest::prepare_test_case(int test_case_idx) |
|
{ |
|
RNG& rng = ts->get_rng(); |
|
int code = cvtest::ArrayTest::prepare_test_case( test_case_idx ); |
|
|
|
if (code <= 0) |
|
return code; |
|
|
|
img_size.width = cvtest::randInt(rng) % MAX_X + 1; |
|
img_size.height = cvtest::randInt(rng) % MAX_Y + 1; |
|
|
|
if (useCPlus) |
|
{ |
|
mat_type = (cvtest::randInt(rng) % 2) == 0 ? CV_32FC1 : CV_16SC2; |
|
if ((cvtest::randInt(rng) % 4) == 0) |
|
mat_type = -1; |
|
if ((cvtest::randInt(rng) % 4) == 0) |
|
mat_type = CV_32FC2; |
|
_mapx = 0; |
|
_mapy = 0; |
|
} |
|
else |
|
{ |
|
int typex = (cvtest::randInt(rng) % 2) == 0 ? CV_32FC1 : CV_16SC2; |
|
//typex = CV_32FC1; ///!!!!!!!!!!!!!!!! |
|
int typey = (typex == CV_32FC1) ? CV_32FC1 : CV_16UC1; |
|
|
|
_mapx = cvCreateMat(img_size.height,img_size.width,typex); |
|
_mapy = cvCreateMat(img_size.height,img_size.width,typey); |
|
|
|
|
|
} |
|
|
|
int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows; |
|
double cam[9] = {0,0,0,0,0,0,0,0,1}; |
|
vector<double> dist(dist_size); |
|
vector<double> new_cam(test_mat[INPUT][4].cols * test_mat[INPUT][4].rows); |
|
vector<Point2d> points(N_POINTS); |
|
|
|
Mat _camera(3,3,CV_64F,cam); |
|
Mat _distort(test_mat[INPUT][2].size(),CV_64F,&dist[0]); |
|
Mat _new_cam(test_mat[INPUT][4].size(),CV_64F,&new_cam[0]); |
|
Mat _points(test_mat[INPUT][0].size(),CV_64FC2, &points[0]); |
|
|
|
//Generating points |
|
for (int i=0;i<N_POINTS;i++) |
|
{ |
|
points[i].x = cvtest::randReal(rng)*img_size.width; |
|
points[i].y = cvtest::randReal(rng)*img_size.height; |
|
} |
|
|
|
//Generating camera matrix |
|
double sz = MAX(img_size.width,img_size.height); |
|
double aspect_ratio = cvtest::randReal(rng)*0.6 + 0.7; |
|
cam[2] = (img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5; |
|
cam[5] = (img_size.height - 1)*0.5 + cvtest::randReal(rng)*10 - 5; |
|
cam[0] = sz/(0.9 - cvtest::randReal(rng)*0.6); |
|
cam[4] = aspect_ratio*cam[0]; |
|
|
|
//Generating distortion coeffs |
|
dist[0] = cvtest::randReal(rng)*0.06 - 0.03; |
|
dist[1] = cvtest::randReal(rng)*0.06 - 0.03; |
|
if( dist[0]*dist[1] > 0 ) |
|
dist[1] = -dist[1]; |
|
if( cvtest::randInt(rng)%4 != 0 ) |
|
{ |
|
dist[2] = cvtest::randReal(rng)*0.004 - 0.002; |
|
dist[3] = cvtest::randReal(rng)*0.004 - 0.002; |
|
if (dist_size > 4) |
|
dist[4] = cvtest::randReal(rng)*0.004 - 0.002; |
|
} |
|
else |
|
{ |
|
dist[2] = dist[3] = 0; |
|
if (dist_size > 4) |
|
dist[4] = 0; |
|
} |
|
|
|
//Generating new camera matrix |
|
_new_cam = Scalar::all(0); |
|
new_cam[8] = 1; |
|
|
|
//new_cam[0] = cam[0]; |
|
//new_cam[4] = cam[4]; |
|
//new_cam[2] = cam[2]; |
|
//new_cam[5] = cam[5]; |
|
|
|
new_cam[0] = cam[0] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[0]; //10% |
|
new_cam[4] = cam[4] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[4]; //10% |
|
new_cam[2] = cam[2] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.width; //15% |
|
new_cam[5] = cam[5] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.height; //15% |
|
|
|
|
|
//Generating R matrix |
|
Mat _rot(3,3,CV_64F); |
|
Mat rotation(1,3,CV_64F); |
|
rotation.at<double>(0) = CV_PI/8*(cvtest::randReal(rng) - (double)0.5); // phi |
|
rotation.at<double>(1) = CV_PI/8*(cvtest::randReal(rng) - (double)0.5); // ksi |
|
rotation.at<double>(2) = CV_PI/3*(cvtest::randReal(rng) - (double)0.5); //khi |
|
cvtest::Rodrigues(rotation, _rot); |
|
|
|
//cvSetIdentity(_rot); |
|
//copying data |
|
cvtest::convert( _points, test_mat[INPUT][0], test_mat[INPUT][0].type()); |
|
cvtest::convert( _camera, test_mat[INPUT][1], test_mat[INPUT][1].type()); |
|
cvtest::convert( _distort, test_mat[INPUT][2], test_mat[INPUT][2].type()); |
|
cvtest::convert( _rot, test_mat[INPUT][3], test_mat[INPUT][3].type()); |
|
cvtest::convert( _new_cam, test_mat[INPUT][4], test_mat[INPUT][4].type()); |
|
|
|
zero_distortion = (cvtest::randInt(rng)%2) == 0 ? false : true; |
|
zero_new_cam = (cvtest::randInt(rng)%2) == 0 ? false : true; |
|
zero_R = (cvtest::randInt(rng)%2) == 0 ? false : true; |
|
|
|
if (useCPlus) |
|
{ |
|
camera_mat = test_mat[INPUT][1]; |
|
distortion_coeffs = test_mat[INPUT][2]; |
|
R = test_mat[INPUT][3]; |
|
new_camera_mat = test_mat[INPUT][4]; |
|
} |
|
|
|
return code; |
|
} |
|
|
|
void CV_InitUndistortRectifyMapTest::prepare_to_validation(int/* test_case_idx*/) |
|
{ |
|
#if 0 |
|
int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows; |
|
double cam[9] = {0,0,0,0,0,0,0,0,1}; |
|
double rot[9] = {1,0,0,0,1,0,0,0,1}; |
|
vector<double> dist(dist_size); |
|
vector<double> new_cam(test_mat[INPUT][4].cols * test_mat[INPUT][4].rows); |
|
vector<Point2d> points(N_POINTS); |
|
vector<Point2d> r_points(N_POINTS); |
|
//Run reference calculations |
|
Mat ref_points(test_mat[INPUT][0].size(),CV_64FC2,&r_points[0]); |
|
Mat _camera(3,3,CV_64F,cam); |
|
Mat _rot(3,3,CV_64F,rot); |
|
Mat _distort(test_mat[INPUT][2].size(),CV_64F,&dist[0]); |
|
Mat _new_cam(test_mat[INPUT][4].size(),CV_64F,&new_cam[0]); |
|
Mat _points(test_mat[INPUT][0].size(),CV_64FC2,&points[0]); |
|
|
|
cvtest::convert(test_mat[INPUT][1],_camera,_camera.type()); |
|
cvtest::convert(test_mat[INPUT][2],_distort,_distort.type()); |
|
cvtest::convert(test_mat[INPUT][3],_rot,_rot.type()); |
|
cvtest::convert(test_mat[INPUT][4],_new_cam,_new_cam.type()); |
|
|
|
//Applying precalculated undistort rectify map |
|
if (!useCPlus) |
|
{ |
|
mapx = cv::Mat(_mapx); |
|
mapy = cv::Mat(_mapy); |
|
} |
|
cv::Mat map1,map2; |
|
cv::convertMaps(mapx,mapy,map1,map2,CV_32FC1); |
|
CvMat _map1 = map1; |
|
CvMat _map2 = map2; |
|
const Point2d* sptr = (const Point2d*)test_mat[INPUT][0].data; |
|
for( int i = 0;i < N_POINTS; i++ ) |
|
{ |
|
int u = saturate_cast<int>(sptr[i].x); |
|
int v = saturate_cast<int>(sptr[i].y); |
|
points[i].x = _map1.data.fl[v*_map1.cols + u]; |
|
points[i].y = _map2.data.fl[v*_map2.cols + u]; |
|
} |
|
|
|
//--- |
|
|
|
cv::undistortPoints(_points, ref_points, _camera, |
|
zero_distortion ? Mat() : _distort, |
|
zero_R ? Mat::eye(3,3,CV_64F) : _rot, |
|
zero_new_cam ? _camera : _new_cam); |
|
//cvTsDistortPoints(&_points,&ref_points,&_camera,&_distort,&_rot,&_new_cam); |
|
cvtest::convert(ref_points, test_mat[REF_OUTPUT][0], test_mat[REF_OUTPUT][0].type()); |
|
cvtest::copy(test_mat[INPUT][0],test_mat[OUTPUT][0]); |
|
|
|
cvReleaseMat(&_mapx); |
|
cvReleaseMat(&_mapy); |
|
#else |
|
int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows; |
|
double cam[9] = {0,0,0,0,0,0,0,0,1}; |
|
double rot[9] = {1,0,0,0,1,0,0,0,1}; |
|
double* dist = new double[dist_size ]; |
|
double* new_cam = new double[test_mat[INPUT][4].cols * test_mat[INPUT][4].rows]; |
|
double* points = new double[N_POINTS*2]; |
|
double* r_points = new double[N_POINTS*2]; |
|
//Run reference calculations |
|
CvMat ref_points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,r_points); |
|
CvMat _camera = cvMat(3,3,CV_64F,cam); |
|
CvMat _rot = cvMat(3,3,CV_64F,rot); |
|
CvMat _distort = cvMat(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,dist); |
|
CvMat _new_cam = cvMat(test_mat[INPUT][4].rows,test_mat[INPUT][4].cols,CV_64F,new_cam); |
|
CvMat _points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,points); |
|
|
|
CvMat _input1 = test_mat[INPUT][1]; |
|
CvMat _input2 = test_mat[INPUT][2]; |
|
CvMat _input3 = test_mat[INPUT][3]; |
|
CvMat _input4 = test_mat[INPUT][4]; |
|
|
|
cvtest::convert(cvarrToMat(&_input1), cvarrToMat(&_camera), -1); |
|
cvtest::convert(cvarrToMat(&_input2), cvarrToMat(&_distort), -1); |
|
cvtest::convert(cvarrToMat(&_input3), cvarrToMat(&_rot), -1); |
|
cvtest::convert(cvarrToMat(&_input4), cvarrToMat(&_new_cam), -1); |
|
|
|
//Applying precalculated undistort rectify map |
|
if (!useCPlus) |
|
{ |
|
mapx = cv::cvarrToMat(_mapx); |
|
mapy = cv::cvarrToMat(_mapy); |
|
} |
|
cv::Mat map1,map2; |
|
cv::convertMaps(mapx,mapy,map1,map2,CV_32FC1); |
|
CvMat _map1 = map1; |
|
CvMat _map2 = map2; |
|
for (int i=0;i<N_POINTS;i++) |
|
{ |
|
double u = test_mat[INPUT][0].ptr<double>()[2*i]; |
|
double v = test_mat[INPUT][0].ptr<double>()[2*i+1]; |
|
_points.data.db[2*i] = (double)_map1.data.fl[(int)v*_map1.cols+(int)u]; |
|
_points.data.db[2*i+1] = (double)_map2.data.fl[(int)v*_map2.cols+(int)u]; |
|
} |
|
|
|
//--- |
|
|
|
cvUndistortPoints(&_points,&ref_points,&_camera, |
|
zero_distortion ? 0 : &_distort, zero_R ? 0 : &_rot, zero_new_cam ? &_camera : &_new_cam); |
|
//cvTsDistortPoints(&_points,&ref_points,&_camera,&_distort,&_rot,&_new_cam); |
|
CvMat dst = test_mat[REF_OUTPUT][0]; |
|
cvtest::convert(cvarrToMat(&ref_points), cvarrToMat(&dst), -1); |
|
|
|
cvtest::copy(test_mat[INPUT][0],test_mat[OUTPUT][0]); |
|
|
|
delete[] dist; |
|
delete[] new_cam; |
|
delete[] points; |
|
delete[] r_points; |
|
cvReleaseMat(&_mapx); |
|
cvReleaseMat(&_mapy); |
|
#endif |
|
} |
|
|
|
void CV_InitUndistortRectifyMapTest::run_func() |
|
{ |
|
if (useCPlus) |
|
{ |
|
cv::Mat input2,input3,input4; |
|
input2 = zero_distortion ? cv::Mat() : test_mat[INPUT][2]; |
|
input3 = zero_R ? cv::Mat() : test_mat[INPUT][3]; |
|
input4 = zero_new_cam ? cv::Mat() : test_mat[INPUT][4]; |
|
cv::initUndistortRectifyMap(camera_mat,input2,input3,input4,img_size,mat_type,mapx,mapy); |
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} |
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else |
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{ |
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CvMat input1 = test_mat[INPUT][1], input2, input3, input4; |
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if( !zero_distortion ) |
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input2 = test_mat[INPUT][2]; |
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if( !zero_R ) |
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input3 = test_mat[INPUT][3]; |
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if( !zero_new_cam ) |
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input4 = test_mat[INPUT][4]; |
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cvInitUndistortRectifyMap(&input1, |
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zero_distortion ? 0 : &input2, |
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zero_R ? 0 : &input3, |
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zero_new_cam ? 0 : &input4, |
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_mapx,_mapy); |
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} |
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} |
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|
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double CV_InitUndistortRectifyMapTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ ) |
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{ |
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return 8; |
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} |
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|
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////////////////////////////////////////////////////////////////////////////////////////////////////// |
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|
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TEST(Calib3d_DefaultNewCameraMatrix, accuracy) { CV_DefaultNewCameraMatrixTest test; test.safe_run(); } |
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TEST(Calib3d_UndistortPoints, accuracy) { CV_UndistortPointsTest test; test.safe_run(); } |
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TEST(Calib3d_InitUndistortRectifyMap, accuracy) { CV_InitUndistortRectifyMapTest test; test.safe_run(); }
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