opencv/modules/gpu/perf/perf_softcascade.cpp

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#include "perf_precomp.hpp"
#define GPU_PERF_TEST_P(fixture, name, params) \
class fixture##_##name : public fixture {\
public:\
fixture##_##name() {}\
protected:\
virtual void __cpu();\
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virtual void __gpu();\
virtual void PerfTestBody();\
};\
TEST_P(fixture##_##name, name /*perf*/){ RunPerfTestBody(); if (runOnGpu) __gpu(); else __cpu();}\
INSTANTIATE_TEST_CASE_P(/*none*/, fixture##_##name, params);\
void fixture##_##name::PerfTestBody()
#define RUN_CPU(fixture, name)\
void fixture##_##name::__cpu()
#define RUN_GPU(fixture, name)\
void fixture##_##name::__gpu()
#define FAIL_NO_CPU(fixture, name)\
void fixture##_##name::__cpu() { FAIL() << "No such CPU implementation analogy";}
namespace {
struct DetectionLess
{
bool operator()(const cv::gpu::SoftCascade::Detection& a,
const cv::gpu::SoftCascade::Detection& b) const
{
if (a.x != b.x) return a.x < b.x;
else if (a.y != b.y) return a.y < b.y;
else if (a.w != b.w) return a.w < b.w;
else return a.h < b.h;
}
bool operator()(const cv::SoftCascade::Detection& a,
const cv::SoftCascade::Detection& b) const
{
const cv::Rect& ra = a.rect;
const cv::Rect& rb = b.rect;
if (ra.x != rb.x) return ra.x < rb.x;
else if (ra.y != rb.y) return ra.y < rb.y;
else if (ra.width != rb.width) return ra.width < rb.width;
else return ra.height < rb.height;
}
};
cv::Mat sortDetections(cv::gpu::GpuMat& objects)
{
cv::Mat detections(objects);
typedef cv::gpu::SoftCascade::Detection Detection;
Detection* begin = (Detection*)(detections.ptr<char>(0));
Detection* end = (Detection*)(detections.ptr<char>(0) + detections.cols);
std::sort(begin, end, DetectionLess());
return detections;
}
}
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typedef std::tr1::tuple<std::string, std::string> fixture_t;
typedef perf::TestBaseWithParam<fixture_t> SoftCascadeTest;
GPU_PERF_TEST_P(SoftCascadeTest, detect,
testing::Combine(
testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png"))))
{ }
RUN_GPU(SoftCascadeTest, detect)
{
cv::Mat cpu = readImage (GET_PARAM(1));
ASSERT_FALSE(cpu.empty());
cv::gpu::GpuMat colored(cpu);
cv::gpu::SoftCascade cascade;
ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GET_PARAM(0))));
cv::gpu::GpuMat objectBoxes(1, 10000 * sizeof(cv::gpu::SoftCascade::Detection), CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1), trois;
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rois.setTo(1);
cv::gpu::transpose(rois, trois);
cv::gpu::GpuMat curr = objectBoxes;
cascade.detectMultiScale(colored, trois, curr);
TEST_CYCLE()
{
curr = objectBoxes;
cascade.detectMultiScale(colored, trois, curr);
}
SANITY_CHECK(sortDetections(curr));
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}
RUN_CPU(SoftCascadeTest, detect)
{
cv::Mat colored = readImage(GET_PARAM(1));
ASSERT_FALSE(colored.empty());
cv::SoftCascade cascade;
ASSERT_TRUE(cascade.load(getDataPath(GET_PARAM(0))));
std::vector<cv::Rect> rois;
typedef cv::SoftCascade::Detection Detection;
std::vector<Detection>objects;
cascade.detectMultiScale(colored, rois, objects);
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TEST_CYCLE()
{
cascade.detectMultiScale(colored, rois, objects);
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}
std::sort(objects.begin(), objects.end(), DetectionLess());
SANITY_CHECK(objects);
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}
static cv::Rect getFromTable(int idx)
{
static const cv::Rect rois[] =
{
cv::Rect( 65, 20, 35, 80),
cv::Rect( 95, 35, 45, 40),
cv::Rect( 45, 35, 45, 40),
cv::Rect( 25, 27, 50, 45),
cv::Rect(100, 50, 45, 40),
cv::Rect( 60, 30, 45, 40),
cv::Rect( 40, 55, 50, 40),
cv::Rect( 48, 37, 72, 80),
cv::Rect( 48, 32, 85, 58),
cv::Rect( 48, 0, 32, 27)
};
return rois[idx];
}
typedef std::tr1::tuple<std::string, std::string, int> roi_fixture_t;
typedef perf::TestBaseWithParam<roi_fixture_t> SoftCascadeTestRoi;
GPU_PERF_TEST_P(SoftCascadeTestRoi, detectInRoi,
testing::Combine(
testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")),
testing::Range(0, 5)))
{}
RUN_GPU(SoftCascadeTestRoi, detectInRoi)
{
cv::Mat cpu = readImage (GET_PARAM(1));
ASSERT_FALSE(cpu.empty());
cv::gpu::GpuMat colored(cpu);
cv::gpu::SoftCascade cascade;
ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GET_PARAM(0))));
cv::gpu::GpuMat objectBoxes(1, 16384 * 20, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
rois.setTo(0);
int nroi = GET_PARAM(2);
cv::RNG rng;
for (int i = 0; i < nroi; ++i)
{
cv::Rect r = getFromTable(rng(10));
cv::gpu::GpuMat sub(rois, r);
sub.setTo(1);
}
cv::gpu::GpuMat trois;
cv::gpu::transpose(rois, trois);
cv::gpu::GpuMat curr = objectBoxes;
cascade.detectMultiScale(colored, trois, curr);
TEST_CYCLE()
{
curr = objectBoxes;
cascade.detectMultiScale(colored, trois, curr);
}
SANITY_CHECK(sortDetections(curr));
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}
FAIL_NO_CPU(SoftCascadeTestRoi, detectInRoi)
GPU_PERF_TEST_P(SoftCascadeTestRoi, detectEachRoi,
testing::Combine(
testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")),
testing::Range(0, 10)))
{}
RUN_GPU(SoftCascadeTestRoi, detectEachRoi)
{
cv::Mat cpu = readImage (GET_PARAM(1));
ASSERT_FALSE(cpu.empty());
cv::gpu::GpuMat colored(cpu);
cv::gpu::SoftCascade cascade;
ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GET_PARAM(0))));
cv::gpu::GpuMat objectBoxes(1, 16384 * 20, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
rois.setTo(0);
int idx = GET_PARAM(2);
cv::Rect r = getFromTable(idx);
cv::gpu::GpuMat sub(rois, r);
sub.setTo(1);
cv::gpu::GpuMat curr = objectBoxes;
cv::gpu::GpuMat trois;
cv::gpu::transpose(rois, trois);
cascade.detectMultiScale(colored, trois, curr);
TEST_CYCLE()
{
curr = objectBoxes;
cascade.detectMultiScale(colored, trois, curr);
}
SANITY_CHECK(sortDetections(curr));
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}
FAIL_NO_CPU(SoftCascadeTestRoi, detectEachRoi)