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171 lines
5.6 KiB
C++
171 lines
5.6 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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#include <fstream>
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using namespace std;
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using namespace cv;
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using namespace cvtest;
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//#define DUMP
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namespace
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{
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// first four bytes, should be the same in little endian
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const float FLO_TAG_FLOAT = 202021.25f; // check for this when READING the file
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const char FLO_TAG_STRING[] = "PIEH"; // use this when WRITING the file
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// binary file format for flow data specified here:
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// http://vision.middlebury.edu/flow/data/
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void writeOpticalFlowToFile(const Mat_<Point2f>& flow, const string& fileName)
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{
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ofstream file(fileName.c_str(), ios_base::binary);
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file << FLO_TAG_STRING;
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file.write((const char*) &flow.cols, sizeof(int));
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file.write((const char*) &flow.rows, sizeof(int));
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for (int i = 0; i < flow.rows; ++i)
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{
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for (int j = 0; j < flow.cols; ++j)
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{
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const Point2f u = flow(i, j);
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file.write((const char*) &u.x, sizeof(float));
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file.write((const char*) &u.y, sizeof(float));
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}
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}
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}
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// binary file format for flow data specified here:
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// http://vision.middlebury.edu/flow/data/
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void readOpticalFlowFromFile(Mat_<Point2f>& flow, const string& fileName)
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{
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ifstream file(fileName.c_str(), ios_base::binary);
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float tag;
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file.read((char*) &tag, sizeof(float));
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CV_Assert( tag == FLO_TAG_FLOAT );
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Size size;
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file.read((char*) &size.width, sizeof(int));
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file.read((char*) &size.height, sizeof(int));
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flow.create(size);
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for (int i = 0; i < flow.rows; ++i)
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{
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for (int j = 0; j < flow.cols; ++j)
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{
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Point2f u;
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file.read((char*) &u.x, sizeof(float));
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file.read((char*) &u.y, sizeof(float));
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flow(i, j) = u;
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}
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}
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}
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bool isFlowCorrect(Point2f u)
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{
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return !cvIsNaN(u.x) && !cvIsNaN(u.y) && (fabs(u.x) < 1e9) && (fabs(u.y) < 1e9);
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}
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double calcRMSE(const Mat_<Point2f>& flow1, const Mat_<Point2f>& flow2)
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{
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double sum = 0.0;
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int counter = 0;
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for (int i = 0; i < flow1.rows; ++i)
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{
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for (int j = 0; j < flow1.cols; ++j)
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{
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const Point2f u1 = flow1(i, j);
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const Point2f u2 = flow2(i, j);
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if (isFlowCorrect(u1) && isFlowCorrect(u2))
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{
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const Point2f diff = u1 - u2;
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sum += diff.ddot(diff);
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++counter;
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}
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}
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}
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return sqrt(sum / (1e-9 + counter));
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}
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}
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TEST(Video_calcOpticalFlowDual_TVL1, Regression)
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{
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const double MAX_RMSE = 0.03;
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const string frame1_path = TS::ptr()->get_data_path() + "optflow/RubberWhale1.png";
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const string frame2_path = TS::ptr()->get_data_path() + "optflow/RubberWhale2.png";
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const string gold_flow_path = TS::ptr()->get_data_path() + "optflow/tvl1_flow.flo";
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Mat frame1 = imread(frame1_path, IMREAD_GRAYSCALE);
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Mat frame2 = imread(frame2_path, IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1.empty());
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ASSERT_FALSE(frame2.empty());
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Mat_<Point2f> flow;
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Ptr<DenseOpticalFlow> tvl1 = createOptFlow_DualTVL1();
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tvl1->calc(frame1, frame2, flow);
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#ifdef DUMP
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writeOpticalFlowToFile(flow, gold_flow_path);
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#else
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Mat_<Point2f> gold;
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readOpticalFlowFromFile(gold, gold_flow_path);
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ASSERT_EQ(gold.rows, flow.rows);
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ASSERT_EQ(gold.cols, flow.cols);
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const double err = calcRMSE(gold, flow);
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EXPECT_LE(err, MAX_RMSE);
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#endif
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}
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