Open Source Computer Vision Library https://opencv.org/
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///////////////////////////////////////////////////////////////////////////////////////
//
// 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) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Niko Li, newlife20080214@gmail.com
// Jia Haipeng, jiahaipeng95@gmail.com
// Shengen Yan, yanshengen@gmail.com
// Jiang Liyuan,jlyuan001.good@163.com
// Rock Li, Rock.Li@amd.com
// Zailong Wu, bullet@yeah.net
// Yao Wang, bitwangyaoyao@gmail.com
//
// 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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// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
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// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
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// * The name of the copyright holders may not be used to endorse or promote products
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//M*/
#include "../test_precomp.hpp"
#include "opencv2/ts/ocl_test.hpp"
#ifdef HAVE_OPENCL
namespace opencv_test {
namespace ocl {
///////////////////// HOG /////////////////////////////
PARAM_TEST_CASE(HOG, Size, MatType)
{
Size winSize;
int type;
Mat img;
UMat uimg;
virtual void SetUp()
{
winSize = GET_PARAM(0);
type = GET_PARAM(1);
img = readImage("cascadeandhog/images/image_00000000_0.png", IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
img.copyTo(uimg);
}
};
OCL_TEST_P(HOG, GetDescriptors)
{
HOGDescriptor hog;
hog.gammaCorrection = true;
hog.setSVMDetector(hog.getDefaultPeopleDetector());
std::vector<float> cpu_descriptors;
std::vector<float> gpu_descriptors;
OCL_OFF(hog.compute(img, cpu_descriptors, hog.winSize));
OCL_ON(hog.compute(uimg, gpu_descriptors, hog.winSize));
Mat cpu_desc(cpu_descriptors), gpu_desc(gpu_descriptors);
EXPECT_MAT_SIMILAR(cpu_desc, gpu_desc, 1e-1);
}
OCL_TEST_P(HOG, SVMDetector)
{
HOGDescriptor hog_first, hog_second;
// empty -> empty
hog_first.copyTo(hog_second);
// first -> both
hog_first.setSVMDetector(hog_first.getDefaultPeopleDetector());
hog_first.copyTo(hog_second);
// both -> both
hog_first.copyTo(hog_second);
// second -> empty
hog_first.setSVMDetector(cv::noArray());
hog_first.copyTo(hog_second);
}
OCL_TEST_P(HOG, Detect)
{
HOGDescriptor hog;
hog.winSize = winSize;
hog.gammaCorrection = true;
if (winSize.width == 48 && winSize.height == 96)
hog.setSVMDetector(hog.getDaimlerPeopleDetector());
else
hog.setSVMDetector(hog.getDefaultPeopleDetector());
std::vector<Rect> cpu_found;
std::vector<Rect> gpu_found;
OCL_OFF(hog.detectMultiScale(img, cpu_found, 0, Size(8, 8), Size(0, 0), 1.05, 6));
OCL_ON(hog.detectMultiScale(uimg, gpu_found, 0, Size(8, 8), Size(0, 0), 1.05, 6));
EXPECT_LT(checkRectSimilarity(img.size(), cpu_found, gpu_found), 0.05);
}
INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, HOG, testing::Combine(
testing::Values(Size(64, 128), Size(48, 96)),
testing::Values( MatType(CV_8UC1) ) ) );
}} // namespace
#endif