/*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. // // // Intel License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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" #include using namespace std; using namespace cv; using namespace cvtest; //#define DUMP namespace { // first four bytes, should be the same in little endian const float FLO_TAG_FLOAT = 202021.25f; // check for this when READING the file #ifdef DUMP // binary file format for flow data specified here: // http://vision.middlebury.edu/flow/data/ void writeOpticalFlowToFile(const Mat_& flow, const string& fileName) { const char FLO_TAG_STRING[] = "PIEH"; // use this when WRITING the file ofstream file(fileName.c_str(), ios_base::binary); file << FLO_TAG_STRING; file.write((const char*) &flow.cols, sizeof(int)); file.write((const char*) &flow.rows, sizeof(int)); for (int i = 0; i < flow.rows; ++i) { for (int j = 0; j < flow.cols; ++j) { const Point2f u = flow(i, j); file.write((const char*) &u.x, sizeof(float)); file.write((const char*) &u.y, sizeof(float)); } } } #endif // binary file format for flow data specified here: // http://vision.middlebury.edu/flow/data/ void readOpticalFlowFromFile(Mat_& flow, const string& fileName) { ifstream file(fileName.c_str(), ios_base::binary); float tag; file.read((char*) &tag, sizeof(float)); CV_Assert( tag == FLO_TAG_FLOAT ); Size size; file.read((char*) &size.width, sizeof(int)); file.read((char*) &size.height, sizeof(int)); flow.create(size); for (int i = 0; i < flow.rows; ++i) { for (int j = 0; j < flow.cols; ++j) { Point2f u; file.read((char*) &u.x, sizeof(float)); file.read((char*) &u.y, sizeof(float)); flow(i, j) = u; } } file.close(); } bool isFlowCorrect(Point2f u) { return !cvIsNaN(u.x) && !cvIsNaN(u.y) && (fabs(u.x) < 1e9) && (fabs(u.y) < 1e9); } void check(const Mat_& gold, const Mat_& flow, double threshold = 0.1, double expectedAccuracy = 0.95) { threshold = threshold*threshold; size_t gold_counter = 0; size_t valid_counter = 0; for (int i = 0; i < gold.rows; ++i) { for (int j = 0; j < gold.cols; ++j) { const Point2f u1 = gold(i, j); const Point2f u2 = flow(i, j); if (isFlowCorrect(u1)) { gold_counter++; if (isFlowCorrect(u2)) { const Point2f diff = u1 - u2; double err = diff.ddot(diff); if (err <= threshold) valid_counter++; } } } } EXPECT_GE(valid_counter, expectedAccuracy * gold_counter); } } TEST(Video_calcOpticalFlowDual_TVL1, Regression) { const string frame1_path = TS::ptr()->get_data_path() + "optflow/RubberWhale1.png"; const string frame2_path = TS::ptr()->get_data_path() + "optflow/RubberWhale2.png"; const string gold_flow_path = TS::ptr()->get_data_path() + "optflow/tvl1_flow.flo"; Mat frame1 = imread(frame1_path, IMREAD_GRAYSCALE); Mat frame2 = imread(frame2_path, IMREAD_GRAYSCALE); ASSERT_FALSE(frame1.empty()); ASSERT_FALSE(frame2.empty()); Mat_ flow; Ptr tvl1 = cv::DualTVL1OpticalFlow::create(); tvl1->calc(frame1, frame2, flow); #ifdef DUMP writeOpticalFlowToFile(flow, gold_flow_path); #else Mat_ gold; readOpticalFlowFromFile(gold, gold_flow_path); ASSERT_EQ(gold.rows, flow.rows); ASSERT_EQ(gold.cols, flow.cols); check(gold, flow); #endif }