mirror of
https://github.com/opencv/opencv.git
synced 2024-11-30 06:10:02 +08:00
318 lines
9.2 KiB
C++
318 lines
9.2 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) 2008-2012, 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"
|
|
|
|
#ifdef HAVE_CUDA
|
|
|
|
using cv::gpu::GpuMat;
|
|
|
|
// show detection results on input image with cv::imshow
|
|
//#define SHOW_DETECTIONS
|
|
|
|
#if defined SHOW_DETECTIONS
|
|
# define SHOW(res) \
|
|
cv::imshow(#res, res); \
|
|
cv::waitKey(0);
|
|
#else
|
|
# define SHOW(res)
|
|
#endif
|
|
|
|
static std::string path(std::string relative)
|
|
{
|
|
return cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/" + relative;
|
|
}
|
|
|
|
TEST(SCascadeTest, readCascade)
|
|
{
|
|
std::string xml = path("cascades/inria_caltech-17.01.2013.xml");
|
|
cv::FileStorage fs(xml, cv::FileStorage::READ);
|
|
|
|
cv::gpu::SCascade cascade;
|
|
|
|
ASSERT_TRUE(fs.isOpened());
|
|
ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
|
|
}
|
|
|
|
namespace
|
|
{
|
|
typedef cv::gpu::SCascade::Detection Detection;
|
|
|
|
cv::Rect getFromTable(int idx)
|
|
{
|
|
static const cv::Rect rois[] =
|
|
{
|
|
cv::Rect( 65 * 4, 20 * 4, 35 * 4, 80 * 4),
|
|
cv::Rect( 95 * 4, 35 * 4, 45 * 4, 40 * 4),
|
|
cv::Rect( 45 * 4, 35 * 4, 45 * 4, 40 * 4),
|
|
cv::Rect( 25 * 4, 27 * 4, 50 * 4, 45 * 4),
|
|
cv::Rect(100 * 4, 50 * 4, 45 * 4, 40 * 4),
|
|
|
|
cv::Rect( 60 * 4, 30 * 4, 45 * 4, 40 * 4),
|
|
cv::Rect( 40 * 4, 55 * 4, 50 * 4, 40 * 4),
|
|
cv::Rect( 48 * 4, 37 * 4, 72 * 4, 80 * 4),
|
|
cv::Rect( 48 * 4, 32 * 4, 85 * 4, 58 * 4),
|
|
cv::Rect( 48 * 4, 0 * 4, 32 * 4, 27 * 4)
|
|
};
|
|
|
|
return rois[idx];
|
|
}
|
|
|
|
|
|
void print(std::ostream &out, const Detection& d)
|
|
{
|
|
#if defined SHOW_DETECTIONS
|
|
out << "\x1b[32m[ detection]\x1b[0m ("
|
|
<< std::setw(4) << d.x
|
|
<< " "
|
|
<< std::setw(4) << d.y
|
|
<< ") ("
|
|
<< std::setw(4) << d.w
|
|
<< " "
|
|
<< std::setw(4) << d.h
|
|
<< ") "
|
|
<< std::setw(12) << d.confidence
|
|
<< std::endl;
|
|
#else
|
|
(void)out; (void)d;
|
|
#endif
|
|
}
|
|
|
|
void printTotal(std::ostream &out, int detbytes)
|
|
{
|
|
#if defined SHOW_DETECTIONS
|
|
out << "\x1b[32m[ ]\x1b[0m Total detections " << (detbytes / sizeof(Detection)) << std::endl;
|
|
#else
|
|
(void)out; (void)detbytes;
|
|
#endif
|
|
}
|
|
|
|
std::string itoa(long i)
|
|
{
|
|
static char s[65];
|
|
sprintf(s, "%ld", i);
|
|
return std::string(s);
|
|
}
|
|
|
|
#if defined SHOW_DETECTIONS
|
|
std::string getImageName(int level)
|
|
{
|
|
time_t rawtime;
|
|
struct tm * timeinfo;
|
|
char buffer [80];
|
|
|
|
time ( &rawtime );
|
|
timeinfo = localtime ( &rawtime );
|
|
|
|
strftime (buffer,80,"%Y-%m-%d--%H-%M-%S",timeinfo);
|
|
return "gpu_rec_level_" + itoa(level)+ "_" + std::string(buffer) + ".png";
|
|
}
|
|
|
|
void writeResult(const cv::Mat& result, const int level)
|
|
{
|
|
std::string path = cv::tempfile(getImageName(level).c_str());
|
|
cv::imwrite(path, result);
|
|
std::cout << "\x1b[32m" << "[ ]" << std::endl << "[ stored in]"<< "\x1b[0m" << path << std::endl;
|
|
}
|
|
#endif
|
|
}
|
|
|
|
PARAM_TEST_CASE(SCascadeTestRoi, cv::gpu::DeviceInfo, std::string, std::string, int)
|
|
{
|
|
virtual void SetUp()
|
|
{
|
|
cv::gpu::setDevice(GET_PARAM(0).deviceID());
|
|
}
|
|
};
|
|
|
|
GPU_TEST_P(SCascadeTestRoi, Detect)
|
|
{
|
|
cv::Mat coloredCpu = cv::imread(path(GET_PARAM(2)));
|
|
ASSERT_FALSE(coloredCpu.empty());
|
|
|
|
cv::gpu::SCascade cascade;
|
|
|
|
cv::FileStorage fs(path(GET_PARAM(1)), cv::FileStorage::READ);
|
|
ASSERT_TRUE(fs.isOpened());
|
|
|
|
ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
|
|
|
|
GpuMat colored(coloredCpu), objectBoxes(1, 16384, CV_8UC1), rois(colored.size(), CV_8UC1);
|
|
rois.setTo(0);
|
|
|
|
int nroi = GET_PARAM(3);
|
|
cv::Mat result(coloredCpu);
|
|
cv::RNG rng;
|
|
for (int i = 0; i < nroi; ++i)
|
|
{
|
|
cv::Rect r = getFromTable(rng(10));
|
|
GpuMat sub(rois, r);
|
|
sub.setTo(1);
|
|
cv::rectangle(result, r, cv::Scalar(0, 0, 255, 255), 1);
|
|
}
|
|
objectBoxes.setTo(0);
|
|
|
|
cascade.detect(colored, rois, objectBoxes);
|
|
|
|
cv::Mat dt(objectBoxes);
|
|
typedef cv::gpu::SCascade::Detection Detection;
|
|
|
|
Detection* dts = ((Detection*)dt.data) + 1;
|
|
int* count = dt.ptr<int>(0);
|
|
|
|
printTotal(std::cout, *count);
|
|
|
|
for (int i = 0; i < *count; ++i)
|
|
{
|
|
Detection d = dts[i];
|
|
print(std::cout, d);
|
|
cv::rectangle(result, cv::Rect(d.x, d.y, d.w, d.h), cv::Scalar(255, 0, 0, 255), 1);
|
|
}
|
|
|
|
SHOW(result);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(GPU_SoftCascade, SCascadeTestRoi, testing::Combine(
|
|
ALL_DEVICES,
|
|
testing::Values(std::string("cascades/inria_caltech-17.01.2013.xml"),
|
|
std::string("cascades/sc_cvpr_2012_to_opencv_new_format.xml")),
|
|
testing::Values(std::string("images/image_00000000_0.png")),
|
|
testing::Range(0, 5)));
|
|
|
|
////////////////////////////////////////
|
|
|
|
namespace {
|
|
|
|
struct Fixture
|
|
{
|
|
std::string path;
|
|
int expected;
|
|
|
|
Fixture(){}
|
|
Fixture(std::string p, int e): path(p), expected(e) {}
|
|
};
|
|
}
|
|
|
|
PARAM_TEST_CASE(SCascadeTestAll, cv::gpu::DeviceInfo, Fixture)
|
|
{
|
|
|
|
std::string xml;
|
|
int expected;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
cv::gpu::setDevice(GET_PARAM(0).deviceID());
|
|
xml = path(GET_PARAM(1).path);
|
|
expected = GET_PARAM(1).expected;
|
|
}
|
|
};
|
|
|
|
GPU_TEST_P(SCascadeTestAll, detect)
|
|
{
|
|
cv::gpu::SCascade cascade;
|
|
|
|
cv::FileStorage fs(xml, cv::FileStorage::READ);
|
|
ASSERT_TRUE(fs.isOpened());
|
|
|
|
ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
|
|
|
|
cv::Mat coloredCpu = cv::imread(path("images/image_00000000_0.png"));
|
|
ASSERT_FALSE(coloredCpu.empty());
|
|
|
|
GpuMat colored(coloredCpu), objectBoxes, rois(colored.size(), CV_8UC1);
|
|
rois.setTo(1);
|
|
|
|
cascade.detect(colored, rois, objectBoxes);
|
|
|
|
typedef cv::gpu::SCascade::Detection Detection;
|
|
cv::Mat dt(objectBoxes);
|
|
|
|
|
|
Detection* dts = ((Detection*)dt.data) + 1;
|
|
int* count = dt.ptr<int>(0);
|
|
|
|
printTotal(std::cout, *count);
|
|
|
|
for (int i = 0; i < *count; ++i)
|
|
{
|
|
Detection d = dts[i];
|
|
print(std::cout, d);
|
|
cv::rectangle(coloredCpu, cv::Rect(d.x, d.y, d.w, d.h), cv::Scalar(255, 0, 0, 255), 1);
|
|
}
|
|
|
|
SHOW(coloredCpu);
|
|
ASSERT_EQ(*count, expected);
|
|
}
|
|
|
|
GPU_TEST_P(SCascadeTestAll, detectStream)
|
|
{
|
|
cv::gpu::SCascade cascade;
|
|
|
|
cv::FileStorage fs(xml, cv::FileStorage::READ);
|
|
ASSERT_TRUE(fs.isOpened());
|
|
|
|
ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
|
|
|
|
cv::Mat coloredCpu = cv::imread(path("images/image_00000000_0.png"));
|
|
ASSERT_FALSE(coloredCpu.empty());
|
|
|
|
GpuMat colored(coloredCpu), objectBoxes(1, 100000, CV_8UC1), rois(colored.size(), CV_8UC1);
|
|
rois.setTo(cv::Scalar::all(1));
|
|
|
|
cv::gpu::Stream s;
|
|
|
|
objectBoxes.setTo(0);
|
|
cascade.detect(colored, rois, objectBoxes, s);
|
|
s.waitForCompletion();
|
|
|
|
typedef cv::gpu::SCascade::Detection Detection;
|
|
cv::Mat detections(objectBoxes);
|
|
int a = *(detections.ptr<int>(0));
|
|
ASSERT_EQ(a, expected);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(GPU_SoftCascade, SCascadeTestAll, testing::Combine( ALL_DEVICES,
|
|
testing::Values(Fixture("cascades/inria_caltech-17.01.2013.xml", 7),
|
|
Fixture("cascades/sc_cvpr_2012_to_opencv_new_format.xml", 1291))));
|
|
|
|
#endif
|