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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.
//
//
// 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 <fstream>
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
const char FLO_TAG_STRING[] = "PIEH"; // use this when WRITING the file
// binary file format for flow data specified here:
// http://vision.middlebury.edu/flow/data/
void writeOpticalFlowToFile(const Mat_<Point2f>& flow, const string& fileName)
{
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_<Point2f>& 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;
}
}
}
bool isFlowCorrect(Point2f u)
{
return !cvIsNaN(u.x) && !cvIsNaN(u.y) && (fabs(u.x) < 1e9) && (fabs(u.y) < 1e9);
}
void check(const Mat_<Point2f>& gold, const Mat_<Point2f>& 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_<Point2f> flow;
Ptr<DenseOpticalFlow> tvl1 = createOptFlow_DualTVL1();
tvl1->calc(frame1, frame2, flow);
#ifdef DUMP
writeOpticalFlowToFile(flow, gold_flow_path);
#else
Mat_<Point2f> gold;
readOpticalFlowFromFile(gold, gold_flow_path);
ASSERT_EQ(gold.rows, flow.rows);
ASSERT_EQ(gold.cols, flow.cols);
check(gold, flow);
#endif
}