test_OF_accuracy.cpp
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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.
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// 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
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//M*/
#include "test_precomp.hpp"
namespace opencv_test { namespace {
static string getDataDir() { return TS::ptr()->get_data_path(); }
static string getRubberWhaleFrame1() { return getDataDir() + "optflow/RubberWhale1.png"; }
static string getRubberWhaleFrame2() { return getDataDir() + "optflow/RubberWhale2.png"; }
static string getRubberWhaleGroundTruth() { return getDataDir() + "optflow/RubberWhale.flo"; }
static bool isFlowCorrect(float u) { return !cvIsNaN(u) && (fabs(u) < 1e9); }
static float calcRMSE(Mat flow1, Mat flow2)
{
float sum = 0;
int counter = 0;
const int rows = flow1.rows;
const int cols = flow1.cols;
for (int y = 0; y < rows; ++y)
{
for (int x = 0; x < cols; ++x)
{
Vec2f flow1_at_point = flow1.at<Vec2f>(y, x);
Vec2f flow2_at_point = flow2.at<Vec2f>(y, x);
float u1 = flow1_at_point[0];
float v1 = flow1_at_point[1];
float u2 = flow2_at_point[0];
float v2 = flow2_at_point[1];
if (isFlowCorrect(u1) && isFlowCorrect(u2) && isFlowCorrect(v1) && isFlowCorrect(v2))
{
sum += (u1 - u2) * (u1 - u2) + (v1 - v2) * (v1 - v2);
counter++;
}
}
}
return (float)sqrt(sum / (1e-9 + counter));
}
bool readRubberWhale(Mat &dst_frame_1, Mat &dst_frame_2, Mat &dst_GT)
{
const string frame1_path = getRubberWhaleFrame1();
const string frame2_path = getRubberWhaleFrame2();
const string gt_flow_path = getRubberWhaleGroundTruth();
dst_frame_1 = imread(frame1_path);
dst_frame_2 = imread(frame2_path);
dst_GT = readOpticalFlow(gt_flow_path);
if (dst_frame_1.empty() || dst_frame_2.empty() || dst_GT.empty())
return false;
else
return true;
}
TEST(DenseOpticalFlow_DIS, ReferenceAccuracy)
{
Mat frame1, frame2, GT;
ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
int presets[] = {DISOpticalFlow::PRESET_ULTRAFAST, DISOpticalFlow::PRESET_FAST, DISOpticalFlow::PRESET_MEDIUM};
float target_RMSE[] = {0.86f, 0.74f, 0.49f};
cvtColor(frame1, frame1, COLOR_BGR2GRAY);
cvtColor(frame2, frame2, COLOR_BGR2GRAY);
Ptr<DenseOpticalFlow> algo;
// iterate over presets:
for (int i = 0; i < 3; i++)
{
Mat flow;
algo = DISOpticalFlow::create(presets[i]);
algo->calc(frame1, frame2, flow);
ASSERT_EQ(GT.rows, flow.rows);
ASSERT_EQ(GT.cols, flow.cols);
EXPECT_LE(calcRMSE(GT, flow), target_RMSE[i]);
}
}
TEST(DenseOpticalFlow_DIS, InvalidImgSize_CoarsestLevelLessThanZero)
{
cv::Ptr<cv::DISOpticalFlow> of = cv::DISOpticalFlow::create();
const int mat_size = 10;
cv::Mat x(mat_size, mat_size, CV_8UC1, 42);
cv::Mat y(mat_size, mat_size, CV_8UC1, 42);
cv::Mat flow;
ASSERT_THROW(of->calc(x, y, flow), cv::Exception);
}
// make sure that autoSelectPatchSizeAndScales() works properly.
TEST(DenseOpticalFlow_DIS, InvalidImgSize_CoarsestLevelLessThanFinestLevel)
{
cv::Ptr<cv::DISOpticalFlow> of = cv::DISOpticalFlow::create();
const int mat_size = 80;
cv::Mat x(mat_size, mat_size, CV_8UC1, 42);
cv::Mat y(mat_size, mat_size, CV_8UC1, 42);
cv::Mat flow;
of->calc(x, y, flow);
ASSERT_EQ(flow.rows, mat_size);
ASSERT_EQ(flow.cols, mat_size);
}
TEST(DenseOpticalFlow_VariationalRefinement, ReferenceAccuracy)
{
Mat frame1, frame2, GT;
ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
float target_RMSE = 0.86f;
cvtColor(frame1, frame1, COLOR_BGR2GRAY);
cvtColor(frame2, frame2, COLOR_BGR2GRAY);
Ptr<VariationalRefinement> var_ref;
var_ref = VariationalRefinement::create();
var_ref->setAlpha(20.0f);
var_ref->setDelta(5.0f);
var_ref->setGamma(10.0f);
var_ref->setSorIterations(25);
var_ref->setFixedPointIterations(25);
Mat flow(frame1.size(), CV_32FC2);
flow.setTo(0.0f);
var_ref->calc(frame1, frame2, flow);
ASSERT_EQ(GT.rows, flow.rows);
ASSERT_EQ(GT.cols, flow.cols);
EXPECT_LE(calcRMSE(GT, flow), target_RMSE);
}
}} // namespace