Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
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// 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:
//
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// this list of conditions and the following disclaimer.
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#include "perf_precomp.hpp"
using namespace std;
using namespace std::tr1;
using namespace testing;
using namespace perf;
using namespace cv;
using namespace cv::superres;
using namespace cv::gpu;
namespace
{
class OneFrameSource_CPU : public FrameSource
{
public:
explicit OneFrameSource_CPU(const Mat& frame) : frame_(frame) {}
void nextFrame(OutputArray frame)
{
frame.getMatRef() = frame_;
}
void reset()
{
}
private:
Mat frame_;
};
class OneFrameSource_GPU : public FrameSource
{
public:
explicit OneFrameSource_GPU(const GpuMat& frame) : frame_(frame) {}
void nextFrame(OutputArray frame)
{
frame.getGpuMatRef() = frame_;
}
void reset()
{
}
private:
GpuMat frame_;
};
class ZeroOpticalFlow : public DenseOpticalFlowExt
{
public:
void calc(InputArray frame0, InputArray, OutputArray flow1, OutputArray flow2)
{
cv::Size size = frame0.size();
if (!flow2.needed())
{
flow1.create(size, CV_32FC2);
if (flow1.kind() == cv::_InputArray::GPU_MAT)
flow1.getGpuMatRef().setTo(cv::Scalar::all(0));
else
flow1.getMatRef().setTo(cv::Scalar::all(0));
}
else
{
flow1.create(size, CV_32FC1);
flow2.create(size, CV_32FC1);
if (flow1.kind() == cv::_InputArray::GPU_MAT)
flow1.getGpuMatRef().setTo(cv::Scalar::all(0));
else
flow1.getMatRef().setTo(cv::Scalar::all(0));
if (flow2.kind() == cv::_InputArray::GPU_MAT)
flow2.getGpuMatRef().setTo(cv::Scalar::all(0));
else
flow2.getMatRef().setTo(cv::Scalar::all(0));
}
}
void collectGarbage()
{
}
};
}
PERF_TEST_P(Size_MatType, SuperResolution_BTVL1,
Combine(Values(szSmall64, szSmall128),
Values(MatType(CV_8UC1), MatType(CV_8UC3))))
{
declare.time(5 * 60);
const Size size = get<0>(GetParam());
const int type = get<1>(GetParam());
Mat frame(size, type);
declare.in(frame, WARMUP_RNG);
const int scale = 2;
const int iterations = 50;
const int temporalAreaRadius = 1;
Ptr<DenseOpticalFlowExt> opticalFlow(new ZeroOpticalFlow);
if (PERF_RUN_GPU())
{
Ptr<SuperResolution> superRes = createSuperResolution_BTVL1_GPU();
superRes->set("scale", scale);
superRes->set("iterations", iterations);
superRes->set("temporalAreaRadius", temporalAreaRadius);
superRes->set("opticalFlow", opticalFlow);
superRes->setInput(new OneFrameSource_GPU(GpuMat(frame)));
GpuMat dst;
superRes->nextFrame(dst);
TEST_CYCLE_N(10) superRes->nextFrame(dst);
GPU_SANITY_CHECK(dst);
}
else
{
Ptr<SuperResolution> superRes = createSuperResolution_BTVL1();
superRes->set("scale", scale);
superRes->set("iterations", iterations);
superRes->set("temporalAreaRadius", temporalAreaRadius);
superRes->set("opticalFlow", opticalFlow);
superRes->setInput(new OneFrameSource_CPU(frame));
Mat dst;
superRes->nextFrame(dst);
TEST_CYCLE_N(10) superRes->nextFrame(dst);
CPU_SANITY_CHECK(dst);
}
}