Open Source Computer Vision Library https://opencv.org/
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/*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.
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// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
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// 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,
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//M*/
#include "perf_precomp.hpp"
using namespace std;
using namespace testing;
using namespace perf;
///////////////////////////////////////////////////////////////
// HOG
DEF_PARAM_TEST_1(Image, string);
PERF_TEST_P(Image, ObjDetect_HOG,
Values<string>("gpu/hog/road.png",
"gpu/caltech/image_00000009_0.png",
"gpu/caltech/image_00000032_0.png",
"gpu/caltech/image_00000165_0.png",
"gpu/caltech/image_00000261_0.png",
"gpu/caltech/image_00000469_0.png",
"gpu/caltech/image_00000527_0.png",
"gpu/caltech/image_00000574_0.png"))
{
declare.time(300.0);
const cv::Mat img = readImage(GetParam(), cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
if (PERF_RUN_CUDA())
{
const cv::cuda::GpuMat d_img(img);
std::vector<cv::Rect> gpu_found_locations;
cv::Ptr<cv::cuda::HOG> d_hog = cv::cuda::HOG::create();
d_hog->setSVMDetector(d_hog->getDefaultPeopleDetector());
TEST_CYCLE() d_hog->detectMultiScale(d_img, gpu_found_locations);
SANITY_CHECK(gpu_found_locations);
}
else
{
std::vector<cv::Rect> cpu_found_locations;
cv::Ptr<cv::cuda::HOG> d_hog = cv::cuda::HOG::create();
cv::HOGDescriptor hog;
hog.setSVMDetector(d_hog->getDefaultPeopleDetector());
TEST_CYCLE() hog.detectMultiScale(img, cpu_found_locations);
SANITY_CHECK(cpu_found_locations);
}
}
///////////////////////////////////////////////////////////////
// HaarClassifier
typedef pair<string, string> pair_string;
DEF_PARAM_TEST_1(ImageAndCascade, pair_string);
PERF_TEST_P(ImageAndCascade, ObjDetect_HaarClassifier,
Values<pair_string>(make_pair("gpu/haarcascade/group_1_640x480_VGA.pgm", "gpu/perf/haarcascade_frontalface_alt.xml")))
{
const cv::Mat img = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
if (PERF_RUN_CUDA())
{
cv::Ptr<cv::cuda::CascadeClassifier> d_cascade =
cv::cuda::CascadeClassifier::create(perf::TestBase::getDataPath(GetParam().second));
const cv::cuda::GpuMat d_img(img);
cv::cuda::GpuMat objects_buffer;
TEST_CYCLE() d_cascade->detectMultiScale(d_img, objects_buffer);
std::vector<cv::Rect> gpu_rects;
d_cascade->convert(objects_buffer, gpu_rects);
cv::groupRectangles(gpu_rects, 3, 0.2);
SANITY_CHECK(gpu_rects);
}
else
{
cv::CascadeClassifier cascade;
ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath("gpu/perf/haarcascade_frontalface_alt.xml")));
std::vector<cv::Rect> cpu_rects;
TEST_CYCLE() cascade.detectMultiScale(img, cpu_rects);
SANITY_CHECK(cpu_rects);
}
}
///////////////////////////////////////////////////////////////
// LBP cascade
PERF_TEST_P(ImageAndCascade, ObjDetect_LBPClassifier,
Values<pair_string>(make_pair("gpu/haarcascade/group_1_640x480_VGA.pgm", "gpu/lbpcascade/lbpcascade_frontalface.xml")))
{
const cv::Mat img = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
if (PERF_RUN_CUDA())
{
cv::Ptr<cv::cuda::CascadeClassifier> d_cascade =
cv::cuda::CascadeClassifier::create(perf::TestBase::getDataPath(GetParam().second));
const cv::cuda::GpuMat d_img(img);
cv::cuda::GpuMat objects_buffer;
TEST_CYCLE() d_cascade->detectMultiScale(d_img, objects_buffer);
std::vector<cv::Rect> gpu_rects;
d_cascade->convert(objects_buffer, gpu_rects);
cv::groupRectangles(gpu_rects, 3, 0.2);
SANITY_CHECK(gpu_rects);
}
else
{
cv::CascadeClassifier cascade;
ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath("gpu/lbpcascade/lbpcascade_frontalface.xml")));
std::vector<cv::Rect> cpu_rects;
TEST_CYCLE() cascade.detectMultiScale(img, cpu_rects);
SANITY_CHECK(cpu_rects);
}
}