mirror of
https://github.com/opencv/opencv.git
synced 2024-12-30 21:25:58 +08:00
279 lines
8.1 KiB
C++
279 lines
8.1 KiB
C++
/*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.
|
|
//
|
|
//
|
|
// License Agreement
|
|
// For Open Source Computer Vision Library
|
|
//
|
|
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
|
|
// Copyright (C) 2009, Willow Garage Inc., 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 the copyright holders 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"
|
|
|
|
class AllignedFrameSource : public cv::superres::FrameSource
|
|
{
|
|
public:
|
|
AllignedFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale);
|
|
|
|
void nextFrame(cv::OutputArray frame);
|
|
void reset();
|
|
|
|
private:
|
|
cv::Ptr<cv::superres::FrameSource> base_;
|
|
cv::Mat origFrame_;
|
|
int scale_;
|
|
};
|
|
|
|
AllignedFrameSource::AllignedFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale) :
|
|
base_(base), scale_(scale)
|
|
{
|
|
CV_Assert( !base_.empty() );
|
|
}
|
|
|
|
void AllignedFrameSource::nextFrame(cv::OutputArray frame)
|
|
{
|
|
base_->nextFrame(origFrame_);
|
|
|
|
if (origFrame_.rows % scale_ == 0 && origFrame_.cols % scale_ == 0)
|
|
{
|
|
cv::superres::arrCopy(origFrame_, frame);
|
|
}
|
|
else
|
|
{
|
|
cv::Rect ROI(0, 0, (origFrame_.cols / scale_) * scale_, (origFrame_.rows / scale_) * scale_);
|
|
cv::superres::arrCopy(origFrame_(ROI), frame);
|
|
}
|
|
}
|
|
|
|
void AllignedFrameSource::reset()
|
|
{
|
|
base_->reset();
|
|
}
|
|
|
|
class DegradeFrameSource : public cv::superres::FrameSource
|
|
{
|
|
public:
|
|
DegradeFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale);
|
|
|
|
void nextFrame(cv::OutputArray frame);
|
|
void reset();
|
|
|
|
private:
|
|
cv::Ptr<cv::superres::FrameSource> base_;
|
|
cv::Mat origFrame_;
|
|
cv::Mat blurred_;
|
|
cv::Mat deg_;
|
|
double iscale_;
|
|
};
|
|
|
|
DegradeFrameSource::DegradeFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale) :
|
|
base_(base), iscale_(1.0 / scale)
|
|
{
|
|
CV_Assert( !base_.empty() );
|
|
}
|
|
|
|
void addGaussNoise(cv::Mat& image, double sigma)
|
|
{
|
|
cv::Mat noise(image.size(), CV_32FC(image.channels()));
|
|
cvtest::TS::ptr()->get_rng().fill(noise, cv::RNG::NORMAL, 0.0, sigma);
|
|
|
|
cv::addWeighted(image, 1.0, noise, 1.0, 0.0, image, image.depth());
|
|
}
|
|
|
|
void addSpikeNoise(cv::Mat& image, int frequency)
|
|
{
|
|
cv::Mat_<uchar> mask(image.size(), 0);
|
|
|
|
for (int y = 0; y < mask.rows; ++y)
|
|
{
|
|
for (int x = 0; x < mask.cols; ++x)
|
|
{
|
|
if (cvtest::TS::ptr()->get_rng().uniform(0, frequency) < 1)
|
|
mask(y, x) = 255;
|
|
}
|
|
}
|
|
|
|
image.setTo(cv::Scalar::all(255), mask);
|
|
}
|
|
|
|
void DegradeFrameSource::nextFrame(cv::OutputArray frame)
|
|
{
|
|
base_->nextFrame(origFrame_);
|
|
|
|
cv::GaussianBlur(origFrame_, blurred_, cv::Size(5, 5), 0);
|
|
cv::resize(blurred_, deg_, cv::Size(), iscale_, iscale_, cv::INTER_NEAREST);
|
|
|
|
addGaussNoise(deg_, 10.0);
|
|
addSpikeNoise(deg_, 500);
|
|
|
|
cv::superres::arrCopy(deg_, frame);
|
|
}
|
|
|
|
void DegradeFrameSource::reset()
|
|
{
|
|
base_->reset();
|
|
}
|
|
|
|
double MSSIM(const cv::Mat& i1, const cv::Mat& i2)
|
|
{
|
|
const double C1 = 6.5025;
|
|
const double C2 = 58.5225;
|
|
|
|
const int depth = CV_32F;
|
|
|
|
cv::Mat I1, I2;
|
|
i1.convertTo(I1, depth);
|
|
i2.convertTo(I2, depth);
|
|
|
|
cv::Mat I2_2 = I2.mul(I2); // I2^2
|
|
cv::Mat I1_2 = I1.mul(I1); // I1^2
|
|
cv::Mat I1_I2 = I1.mul(I2); // I1 * I2
|
|
|
|
cv::Mat mu1, mu2;
|
|
cv::GaussianBlur(I1, mu1, cv::Size(11, 11), 1.5);
|
|
cv::GaussianBlur(I2, mu2, cv::Size(11, 11), 1.5);
|
|
|
|
cv::Mat mu1_2 = mu1.mul(mu1);
|
|
cv::Mat mu2_2 = mu2.mul(mu2);
|
|
cv::Mat mu1_mu2 = mu1.mul(mu2);
|
|
|
|
cv::Mat sigma1_2, sigma2_2, sigma12;
|
|
|
|
cv::GaussianBlur(I1_2, sigma1_2, cv::Size(11, 11), 1.5);
|
|
sigma1_2 -= mu1_2;
|
|
|
|
cv::GaussianBlur(I2_2, sigma2_2, cv::Size(11, 11), 1.5);
|
|
sigma2_2 -= mu2_2;
|
|
|
|
cv::GaussianBlur(I1_I2, sigma12, cv::Size(11, 11), 1.5);
|
|
sigma12 -= mu1_mu2;
|
|
|
|
cv::Mat t1, t2;
|
|
cv::Mat numerator;
|
|
cv::Mat denominator;
|
|
|
|
// t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
|
|
t1 = 2 * mu1_mu2 + C1;
|
|
t2 = 2 * sigma12 + C2;
|
|
numerator = t1.mul(t2);
|
|
|
|
// t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))
|
|
t1 = mu1_2 + mu2_2 + C1;
|
|
t2 = sigma1_2 + sigma2_2 + C2;
|
|
denominator = t1.mul(t2);
|
|
|
|
// ssim_map = numerator./denominator;
|
|
cv::Mat ssim_map;
|
|
cv::divide(numerator, denominator, ssim_map);
|
|
|
|
// mssim = average of ssim map
|
|
cv::Scalar mssim = cv::mean(ssim_map);
|
|
|
|
if (i1.channels() == 1)
|
|
return mssim[0];
|
|
|
|
return (mssim[0] + mssim[1] + mssim[3]) / 3;
|
|
}
|
|
|
|
class SuperResolution : public testing::Test
|
|
{
|
|
public:
|
|
void RunTest(cv::Ptr<cv::superres::SuperResolution> superRes);
|
|
};
|
|
|
|
void SuperResolution::RunTest(cv::Ptr<cv::superres::SuperResolution> superRes)
|
|
{
|
|
const std::string inputVideoName = cvtest::TS::ptr()->get_data_path() + "car.avi";
|
|
const int scale = 2;
|
|
const int iterations = 100;
|
|
const int temporalAreaRadius = 2;
|
|
|
|
ASSERT_FALSE( superRes.empty() );
|
|
|
|
const int btvKernelSize = superRes->getInt("btvKernelSize");
|
|
|
|
superRes->set("scale", scale);
|
|
superRes->set("iterations", iterations);
|
|
superRes->set("temporalAreaRadius", temporalAreaRadius);
|
|
|
|
cv::Ptr<cv::superres::FrameSource> goldSource(new AllignedFrameSource(cv::superres::createFrameSource_Video(inputVideoName), scale));
|
|
cv::Ptr<cv::superres::FrameSource> lowResSource(new DegradeFrameSource(new AllignedFrameSource(cv::superres::createFrameSource_Video(inputVideoName), scale), scale));
|
|
|
|
// skip first frame
|
|
cv::Mat frame;
|
|
|
|
lowResSource->nextFrame(frame);
|
|
goldSource->nextFrame(frame);
|
|
|
|
cv::Rect inner(btvKernelSize, btvKernelSize, frame.cols - 2 * btvKernelSize, frame.rows - 2 * btvKernelSize);
|
|
|
|
superRes->setInput(lowResSource);
|
|
|
|
double srAvgMSSIM = 0.0;
|
|
const int count = 10;
|
|
|
|
cv::Mat goldFrame, superResFrame;
|
|
for (int i = 0; i < count; ++i)
|
|
{
|
|
goldSource->nextFrame(goldFrame);
|
|
ASSERT_FALSE( goldFrame.empty() );
|
|
|
|
superRes->nextFrame(superResFrame);
|
|
ASSERT_FALSE( superResFrame.empty() );
|
|
|
|
const double srMSSIM = MSSIM(goldFrame(inner), superResFrame);
|
|
|
|
srAvgMSSIM += srMSSIM;
|
|
}
|
|
|
|
srAvgMSSIM /= count;
|
|
|
|
EXPECT_GE( srAvgMSSIM, 0.5 );
|
|
}
|
|
|
|
TEST_F(SuperResolution, BTVL1)
|
|
{
|
|
RunTest(cv::superres::createSuperResolution_BTVL1());
|
|
}
|
|
|
|
#if defined(HAVE_CUDA) && defined(HAVE_OPENCV_GPUARITHM) && defined(HAVE_OPENCV_GPUWARPING) && defined(HAVE_OPENCV_GPUFILTERS)
|
|
|
|
TEST_F(SuperResolution, BTVL1_GPU)
|
|
{
|
|
RunTest(cv::superres::createSuperResolution_BTVL1_GPU());
|
|
}
|
|
|
|
#endif
|