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Open Source Computer Vision Library
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285 lines
8.2 KiB
285 lines
8.2 KiB
/*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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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage Inc., 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 the copyright holders 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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class AllignedFrameSource : public cv::superres::FrameSource |
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{ |
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public: |
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AllignedFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale); |
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void nextFrame(cv::OutputArray frame); |
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void reset(); |
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private: |
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cv::Ptr<cv::superres::FrameSource> base_; |
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cv::Mat origFrame_; |
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int scale_; |
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}; |
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AllignedFrameSource::AllignedFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale) : |
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base_(base), scale_(scale) |
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{ |
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CV_Assert( !base_.empty() ); |
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} |
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void AllignedFrameSource::nextFrame(cv::OutputArray frame) |
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{ |
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base_->nextFrame(origFrame_); |
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if (origFrame_.rows % scale_ == 0 && origFrame_.cols % scale_ == 0) |
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{ |
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cv::superres::arrCopy(origFrame_, frame); |
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} |
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else |
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{ |
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cv::Rect ROI(0, 0, (origFrame_.cols / scale_) * scale_, (origFrame_.rows / scale_) * scale_); |
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cv::superres::arrCopy(origFrame_(ROI), frame); |
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} |
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} |
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void AllignedFrameSource::reset() |
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{ |
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base_->reset(); |
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} |
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class DegradeFrameSource : public cv::superres::FrameSource |
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{ |
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public: |
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DegradeFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale); |
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void nextFrame(cv::OutputArray frame); |
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void reset(); |
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private: |
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cv::Ptr<cv::superres::FrameSource> base_; |
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cv::Mat origFrame_; |
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cv::Mat blurred_; |
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cv::Mat deg_; |
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double iscale_; |
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}; |
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DegradeFrameSource::DegradeFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale) : |
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base_(base), iscale_(1.0 / scale) |
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{ |
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CV_Assert( !base_.empty() ); |
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} |
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void addGaussNoise(cv::Mat& image, double sigma) |
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{ |
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cv::Mat noise(image.size(), CV_32FC(image.channels())); |
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cvtest::TS::ptr()->get_rng().fill(noise, cv::RNG::NORMAL, 0.0, sigma); |
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cv::addWeighted(image, 1.0, noise, 1.0, 0.0, image, image.depth()); |
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} |
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void addSpikeNoise(cv::Mat& image, int frequency) |
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{ |
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cv::Mat_<uchar> mask(image.size(), 0); |
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for (int y = 0; y < mask.rows; ++y) |
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{ |
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for (int x = 0; x < mask.cols; ++x) |
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{ |
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if (cvtest::TS::ptr()->get_rng().uniform(0, frequency) < 1) |
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mask(y, x) = 255; |
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} |
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} |
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image.setTo(cv::Scalar::all(255), mask); |
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} |
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void DegradeFrameSource::nextFrame(cv::OutputArray frame) |
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{ |
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base_->nextFrame(origFrame_); |
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cv::GaussianBlur(origFrame_, blurred_, cv::Size(5, 5), 0); |
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cv::resize(blurred_, deg_, cv::Size(), iscale_, iscale_, cv::INTER_NEAREST); |
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addGaussNoise(deg_, 10.0); |
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addSpikeNoise(deg_, 500); |
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cv::superres::arrCopy(deg_, frame); |
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} |
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void DegradeFrameSource::reset() |
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{ |
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base_->reset(); |
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} |
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double MSSIM(const cv::Mat& i1, const cv::Mat& i2) |
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{ |
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const double C1 = 6.5025; |
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const double C2 = 58.5225; |
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const int depth = CV_32F; |
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cv::Mat I1, I2; |
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i1.convertTo(I1, depth); |
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i2.convertTo(I2, depth); |
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cv::Mat I2_2 = I2.mul(I2); // I2^2 |
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cv::Mat I1_2 = I1.mul(I1); // I1^2 |
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cv::Mat I1_I2 = I1.mul(I2); // I1 * I2 |
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cv::Mat mu1, mu2; |
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cv::GaussianBlur(I1, mu1, cv::Size(11, 11), 1.5); |
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cv::GaussianBlur(I2, mu2, cv::Size(11, 11), 1.5); |
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cv::Mat mu1_2 = mu1.mul(mu1); |
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cv::Mat mu2_2 = mu2.mul(mu2); |
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cv::Mat mu1_mu2 = mu1.mul(mu2); |
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cv::Mat sigma1_2, sigma2_2, sigma12; |
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cv::GaussianBlur(I1_2, sigma1_2, cv::Size(11, 11), 1.5); |
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sigma1_2 -= mu1_2; |
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cv::GaussianBlur(I2_2, sigma2_2, cv::Size(11, 11), 1.5); |
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sigma2_2 -= mu2_2; |
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cv::GaussianBlur(I1_I2, sigma12, cv::Size(11, 11), 1.5); |
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sigma12 -= mu1_mu2; |
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cv::Mat t1, t2; |
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cv::Mat numerator; |
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cv::Mat denominator; |
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// t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2)) |
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t1 = 2 * mu1_mu2 + C1; |
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t2 = 2 * sigma12 + C2; |
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numerator = t1.mul(t2); |
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// t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2)) |
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t1 = mu1_2 + mu2_2 + C1; |
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t2 = sigma1_2 + sigma2_2 + C2; |
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denominator = t1.mul(t2); |
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// ssim_map = numerator./denominator; |
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cv::Mat ssim_map; |
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cv::divide(numerator, denominator, ssim_map); |
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// mssim = average of ssim map |
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cv::Scalar mssim = cv::mean(ssim_map); |
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if (i1.channels() == 1) |
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return mssim[0]; |
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return (mssim[0] + mssim[1] + mssim[3]) / 3; |
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} |
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class SuperResolution : public testing::Test |
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{ |
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public: |
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void RunTest(cv::Ptr<cv::superres::SuperResolution> superRes); |
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}; |
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void SuperResolution::RunTest(cv::Ptr<cv::superres::SuperResolution> superRes) |
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{ |
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const std::string inputVideoName = cvtest::TS::ptr()->get_data_path() + "car.avi"; |
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const int scale = 2; |
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const int iterations = 100; |
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const int temporalAreaRadius = 2; |
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ASSERT_FALSE( superRes.empty() ); |
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const int btvKernelSize = superRes->getInt("btvKernelSize"); |
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superRes->set("scale", scale); |
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superRes->set("iterations", iterations); |
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superRes->set("temporalAreaRadius", temporalAreaRadius); |
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cv::Ptr<cv::superres::FrameSource> goldSource(new AllignedFrameSource(cv::superres::createFrameSource_Video(inputVideoName), scale)); |
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cv::Ptr<cv::superres::FrameSource> lowResSource(new DegradeFrameSource(new AllignedFrameSource(cv::superres::createFrameSource_Video(inputVideoName), scale), scale)); |
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// skip first frame |
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cv::Mat frame; |
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lowResSource->nextFrame(frame); |
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goldSource->nextFrame(frame); |
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cv::Rect inner(btvKernelSize, btvKernelSize, frame.cols - 2 * btvKernelSize, frame.rows - 2 * btvKernelSize); |
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superRes->setInput(lowResSource); |
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double srAvgMSSIM = 0.0; |
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const int count = 10; |
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cv::Mat goldFrame, superResFrame; |
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for (int i = 0; i < count; ++i) |
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{ |
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goldSource->nextFrame(goldFrame); |
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ASSERT_FALSE( goldFrame.empty() ); |
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superRes->nextFrame(superResFrame); |
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ASSERT_FALSE( superResFrame.empty() ); |
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const double srMSSIM = MSSIM(goldFrame(inner), superResFrame); |
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srAvgMSSIM += srMSSIM; |
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} |
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srAvgMSSIM /= count; |
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EXPECT_GE( srAvgMSSIM, 0.5 ); |
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} |
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TEST_F(SuperResolution, BTVL1) |
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{ |
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RunTest(cv::superres::createSuperResolution_BTVL1()); |
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} |
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#if defined(HAVE_OPENCV_GPU) && defined(HAVE_CUDA) |
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TEST_F(SuperResolution, BTVL1_GPU) |
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{ |
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RunTest(cv::superres::createSuperResolution_BTVL1_GPU()); |
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} |
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#endif |
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#if defined(HAVE_OPENCV_OCL) && defined(HAVE_OPENCL) |
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TEST_F(SuperResolution, BTVL1_OCL) |
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{ |
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std::vector<cv::ocl::Info> infos; |
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cv::ocl::getDevice(infos); |
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RunTest(cv::superres::createSuperResolution_BTVL1_OCL()); |
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} |
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#endif
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