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.
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//
// 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,
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//M*/
#include "test_precomp.hpp"
#ifdef HAVE_CUDA
using namespace cvtest;
///////////////////////////////////////////////////////////////////////////////////////////////////////
// HistEven
struct HistEven : testing::TestWithParam<cv::gpu::DeviceInfo>
{
cv::gpu::DeviceInfo devInfo;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(HistEven, Accuracy)
{
cv::Mat img = readImage("stereobm/aloe-L.png");
ASSERT_FALSE(img.empty());
cv::Mat hsv;
cv::cvtColor(img, hsv, cv::COLOR_BGR2HSV);
int hbins = 30;
float hranges[] = {0.0f, 180.0f};
std::vector<cv::Mat> srcs;
cv::split(hsv, srcs);
cv::gpu::GpuMat hist;
cv::gpu::histEven(loadMat(srcs[0]), hist, hbins, (int)hranges[0], (int)hranges[1]);
cv::MatND histnd;
int histSize[] = {hbins};
const float* ranges[] = {hranges};
int channels[] = {0};
cv::calcHist(&hsv, 1, channels, cv::Mat(), histnd, 1, histSize, ranges);
cv::Mat hist_gold = histnd;
hist_gold = hist_gold.t();
hist_gold.convertTo(hist_gold, CV_32S);
EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, HistEven, ALL_DEVICES);
///////////////////////////////////////////////////////////////////////////////////////////////////////
// CalcHist
namespace
{
void calcHistGold(const cv::Mat& src, cv::Mat& hist)
{
hist.create(1, 256, CV_32SC1);
hist.setTo(cv::Scalar::all(0));
int* hist_row = hist.ptr<int>();
for (int y = 0; y < src.rows; ++y)
{
const uchar* src_row = src.ptr(y);
for (int x = 0; x < src.cols; ++x)
++hist_row[src_row[x]];
}
}
}
PARAM_TEST_CASE(CalcHist, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(CalcHist, Accuracy)
{
cv::Mat src = randomMat(size, CV_8UC1);
cv::gpu::GpuMat hist;
cv::gpu::calcHist(loadMat(src), hist);
cv::Mat hist_gold;
calcHistGold(src, hist_gold);
EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, CalcHist, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES));
///////////////////////////////////////////////////////////////////////////////////////////////////////
// EqualizeHist
PARAM_TEST_CASE(EqualizeHist, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(EqualizeHist, Accuracy)
{
cv::Mat src = randomMat(size, CV_8UC1);
cv::gpu::GpuMat dst;
cv::gpu::equalizeHist(loadMat(src), dst);
cv::Mat dst_gold;
cv::equalizeHist(src, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 3.0);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, EqualizeHist, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES));
///////////////////////////////////////////////////////////////////////////////////////////////////////
// CLAHE
namespace
{
IMPLEMENT_PARAM_CLASS(ClipLimit, double)
}
PARAM_TEST_CASE(CLAHE, cv::gpu::DeviceInfo, cv::Size, ClipLimit)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
double clipLimit;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
clipLimit = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(CLAHE, Accuracy)
{
cv::Mat src = randomMat(size, CV_8UC1);
cv::Ptr<cv::gpu::CLAHE> clahe = cv::gpu::createCLAHE(clipLimit);
cv::gpu::GpuMat dst;
clahe->apply(loadMat(src), dst);
cv::Ptr<cv::CLAHE> clahe_gold = cv::createCLAHE(clipLimit);
cv::Mat dst_gold;
clahe_gold->apply(src, dst_gold);
ASSERT_MAT_NEAR(dst_gold, dst, 1.0);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, CLAHE, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(0.0, 40.0)));
#endif // HAVE_CUDA