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Open Source Computer Vision Library
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148 lines
5.3 KiB
148 lines
5.3 KiB
6 years ago
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/*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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namespace opencv_test { namespace {
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static string getDataDir() { return TS::ptr()->get_data_path(); }
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static string getRubberWhaleFrame1() { return getDataDir() + "optflow/RubberWhale1.png"; }
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static string getRubberWhaleFrame2() { return getDataDir() + "optflow/RubberWhale2.png"; }
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static string getRubberWhaleGroundTruth() { return getDataDir() + "optflow/RubberWhale.flo"; }
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static bool isFlowCorrect(float u) { return !cvIsNaN(u) && (fabs(u) < 1e9); }
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static float calcRMSE(Mat flow1, Mat flow2)
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{
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float sum = 0;
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int counter = 0;
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const int rows = flow1.rows;
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const int cols = flow1.cols;
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for (int y = 0; y < rows; ++y)
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{
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for (int x = 0; x < cols; ++x)
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{
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Vec2f flow1_at_point = flow1.at<Vec2f>(y, x);
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Vec2f flow2_at_point = flow2.at<Vec2f>(y, x);
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float u1 = flow1_at_point[0];
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float v1 = flow1_at_point[1];
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float u2 = flow2_at_point[0];
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float v2 = flow2_at_point[1];
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if (isFlowCorrect(u1) && isFlowCorrect(u2) && isFlowCorrect(v1) && isFlowCorrect(v2))
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{
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sum += (u1 - u2) * (u1 - u2) + (v1 - v2) * (v1 - v2);
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counter++;
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}
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}
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}
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return (float)sqrt(sum / (1e-9 + counter));
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}
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bool readRubberWhale(Mat &dst_frame_1, Mat &dst_frame_2, Mat &dst_GT)
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{
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const string frame1_path = getRubberWhaleFrame1();
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const string frame2_path = getRubberWhaleFrame2();
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const string gt_flow_path = getRubberWhaleGroundTruth();
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dst_frame_1 = imread(frame1_path);
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dst_frame_2 = imread(frame2_path);
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dst_GT = readOpticalFlow(gt_flow_path);
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if (dst_frame_1.empty() || dst_frame_2.empty() || dst_GT.empty())
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return false;
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else
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return true;
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}
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TEST(DenseOpticalFlow_DIS, ReferenceAccuracy)
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{
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Mat frame1, frame2, GT;
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ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
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int presets[] = {DISOpticalFlow::PRESET_ULTRAFAST, DISOpticalFlow::PRESET_FAST, DISOpticalFlow::PRESET_MEDIUM};
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float target_RMSE[] = {0.86f, 0.74f, 0.49f};
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cvtColor(frame1, frame1, COLOR_BGR2GRAY);
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cvtColor(frame2, frame2, COLOR_BGR2GRAY);
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Ptr<DenseOpticalFlow> algo;
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// iterate over presets:
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for (int i = 0; i < 3; i++)
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{
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Mat flow;
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algo = DISOpticalFlow::create(presets[i]);
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algo->calc(frame1, frame2, flow);
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ASSERT_EQ(GT.rows, flow.rows);
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ASSERT_EQ(GT.cols, flow.cols);
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EXPECT_LE(calcRMSE(GT, flow), target_RMSE[i]);
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}
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}
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TEST(DenseOpticalFlow_VariationalRefinement, ReferenceAccuracy)
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{
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Mat frame1, frame2, GT;
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ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
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float target_RMSE = 0.86f;
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cvtColor(frame1, frame1, COLOR_BGR2GRAY);
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cvtColor(frame2, frame2, COLOR_BGR2GRAY);
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Ptr<VariationalRefinement> var_ref;
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var_ref = VariationalRefinement::create();
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var_ref->setAlpha(20.0f);
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var_ref->setDelta(5.0f);
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var_ref->setGamma(10.0f);
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var_ref->setSorIterations(25);
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var_ref->setFixedPointIterations(25);
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Mat flow(frame1.size(), CV_32FC2);
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flow.setTo(0.0f);
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var_ref->calc(frame1, frame2, flow);
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ASSERT_EQ(GT.rows, flow.rows);
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ASSERT_EQ(GT.cols, flow.cols);
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EXPECT_LE(calcRMSE(GT, flow), target_RMSE);
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}
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}} // namespace
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