277 lines
7.8 KiB
C++
277 lines
7.8 KiB
C++
#include "perf_precomp.hpp"
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#define GPU_PERF_TEST_P(fixture, name, params) \
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class fixture##_##name : public fixture {\
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public:\
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fixture##_##name() {}\
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protected:\
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virtual void __cpu();\
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virtual void __gpu();\
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virtual void PerfTestBody();\
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};\
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TEST_P(fixture##_##name, name /*perf*/){ RunPerfTestBody(); if (PERF_RUN_GPU()) __gpu(); else __cpu();}\
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INSTANTIATE_TEST_CASE_P(/*none*/, fixture##_##name, params);\
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void fixture##_##name::PerfTestBody()
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#define RUN_CPU(fixture, name)\
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void fixture##_##name::__cpu()
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#define RUN_GPU(fixture, name)\
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void fixture##_##name::__gpu()
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#define NO_CPU(fixture, name)\
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void fixture##_##name::__cpu() { FAIL() << "No such CPU implementation analogy";}
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namespace {
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struct DetectionLess
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{
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bool operator()(const cv::gpu::SoftCascade::Detection& a,
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const cv::gpu::SoftCascade::Detection& b) const
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{
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if (a.x != b.x) return a.x < b.x;
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else if (a.y != b.y) return a.y < b.y;
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else if (a.w != b.w) return a.w < b.w;
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else return a.h < b.h;
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}
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bool operator()(const cv::SoftCascade::Detection& a,
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const cv::SoftCascade::Detection& b) const
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{
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const cv::Rect& ra = a.rect;
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const cv::Rect& rb = b.rect;
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if (ra.x != rb.x) return ra.x < rb.x;
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else if (ra.y != rb.y) return ra.y < rb.y;
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else if (ra.width != rb.width) return ra.width < rb.width;
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else return ra.height < rb.height;
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}
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};
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cv::Mat sortDetections(cv::gpu::GpuMat& objects)
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{
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cv::Mat detections(objects);
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typedef cv::gpu::SoftCascade::Detection Detection;
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Detection* begin = (Detection*)(detections.ptr<char>(0));
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Detection* end = (Detection*)(detections.ptr<char>(0) + detections.cols);
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std::sort(begin, end, DetectionLess());
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return detections;
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}
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}
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typedef std::tr1::tuple<std::string, std::string> fixture_t;
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typedef perf::TestBaseWithParam<fixture_t> SoftCascadeTest;
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GPU_PERF_TEST_P(SoftCascadeTest, detect,
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testing::Combine(
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testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
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testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png"))))
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{ }
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RUN_GPU(SoftCascadeTest, detect)
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{
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cv::Mat cpu = readImage (GET_PARAM(1));
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ASSERT_FALSE(cpu.empty());
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cv::gpu::GpuMat colored(cpu);
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cv::gpu::SoftCascade cascade;
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ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GET_PARAM(0))));
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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);
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cv::gpu::transpose(rois, trois);
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cv::gpu::GpuMat curr = objectBoxes;
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cascade.detectMultiScale(colored, trois, curr);
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TEST_CYCLE()
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{
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curr = objectBoxes;
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cascade.detectMultiScale(colored, trois, curr);
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}
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SANITY_CHECK(sortDetections(curr));
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}
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RUN_CPU(SoftCascadeTest, detect)
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{
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cv::Mat colored = readImage(GET_PARAM(1));
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ASSERT_FALSE(colored.empty());
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cv::SoftCascade cascade;
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ASSERT_TRUE(cascade.load(getDataPath(GET_PARAM(0))));
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std::vector<cv::Rect> rois;
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typedef cv::SoftCascade::Detection Detection;
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std::vector<Detection>objects;
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cascade.detectMultiScale(colored, rois, objects);
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TEST_CYCLE()
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{
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cascade.detectMultiScale(colored, rois, objects);
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}
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std::sort(objects.begin(), objects.end(), DetectionLess());
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SANITY_CHECK(objects);
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}
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static cv::Rect getFromTable(int idx)
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{
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static const cv::Rect rois[] =
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{
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cv::Rect( 65, 20, 35, 80),
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cv::Rect( 95, 35, 45, 40),
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cv::Rect( 45, 35, 45, 40),
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cv::Rect( 25, 27, 50, 45),
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cv::Rect(100, 50, 45, 40),
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cv::Rect( 60, 30, 45, 40),
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cv::Rect( 40, 55, 50, 40),
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cv::Rect( 48, 37, 72, 80),
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cv::Rect( 48, 32, 85, 58),
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cv::Rect( 48, 0, 32, 27)
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};
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return rois[idx];
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}
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typedef std::tr1::tuple<std::string, std::string, int> roi_fixture_t;
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typedef perf::TestBaseWithParam<roi_fixture_t> SoftCascadeTestRoi;
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GPU_PERF_TEST_P(SoftCascadeTestRoi, detectInRoi,
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testing::Combine(
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testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
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testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")),
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testing::Range(0, 5)))
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{}
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RUN_GPU(SoftCascadeTestRoi, detectInRoi)
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{
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cv::Mat cpu = readImage (GET_PARAM(1));
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ASSERT_FALSE(cpu.empty());
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cv::gpu::GpuMat colored(cpu);
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cv::gpu::SoftCascade cascade;
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ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GET_PARAM(0))));
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cv::gpu::GpuMat objectBoxes(1, 16384 * 20, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
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rois.setTo(0);
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int nroi = GET_PARAM(2);
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cv::RNG rng;
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for (int i = 0; i < nroi; ++i)
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{
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cv::Rect r = getFromTable(rng(10));
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cv::gpu::GpuMat sub(rois, r);
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sub.setTo(1);
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}
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cv::gpu::GpuMat trois;
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cv::gpu::transpose(rois, trois);
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cv::gpu::GpuMat curr = objectBoxes;
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cascade.detectMultiScale(colored, trois, curr);
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TEST_CYCLE()
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{
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curr = objectBoxes;
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cascade.detectMultiScale(colored, trois, curr);
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}
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SANITY_CHECK(sortDetections(curr));
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}
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NO_CPU(SoftCascadeTestRoi, detectInRoi)
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GPU_PERF_TEST_P(SoftCascadeTestRoi, detectEachRoi,
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testing::Combine(
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testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
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testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")),
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testing::Range(0, 10)))
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{}
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RUN_GPU(SoftCascadeTestRoi, detectEachRoi)
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{
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cv::Mat cpu = readImage (GET_PARAM(1));
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ASSERT_FALSE(cpu.empty());
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cv::gpu::GpuMat colored(cpu);
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cv::gpu::SoftCascade cascade;
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ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GET_PARAM(0))));
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cv::gpu::GpuMat objectBoxes(1, 16384 * 20, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
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rois.setTo(0);
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int idx = GET_PARAM(2);
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cv::Rect r = getFromTable(idx);
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cv::gpu::GpuMat sub(rois, r);
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sub.setTo(1);
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cv::gpu::GpuMat curr = objectBoxes;
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cv::gpu::GpuMat trois;
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cv::gpu::transpose(rois, trois);
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cascade.detectMultiScale(colored, trois, curr);
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TEST_CYCLE()
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{
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curr = objectBoxes;
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cascade.detectMultiScale(colored, trois, curr);
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}
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SANITY_CHECK(sortDetections(curr));
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}
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NO_CPU(SoftCascadeTestRoi, detectEachRoi)
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GPU_PERF_TEST_P(SoftCascadeTest, detectOnIntegral,
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testing::Combine(
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testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
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testing::Values(std::string("cv/cascadeandhog/integrals.xml"))))
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{ }
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static std::string itoa(long i)
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{
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static char s[65];
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sprintf(s, "%ld", i);
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return std::string(s);
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}
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RUN_GPU(SoftCascadeTest, detectOnIntegral)
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{
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cv::FileStorage fs(perf::TestBase::getDataPath(GET_PARAM(1)), cv::FileStorage::READ);
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ASSERT_TRUE(fs.isOpened());
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cv::gpu::GpuMat hogluv(121 * 10, 161, CV_32SC1);
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for (int i = 0; i < 10; ++i)
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{
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cv::Mat channel;
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fs[std::string("channel") + itoa(i)] >> channel;
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cv::gpu::GpuMat gchannel(hogluv, cv::Rect(0, 121 * i, 161, 121));
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gchannel.upload(channel);
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}
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cv::gpu::SoftCascade cascade;
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ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GET_PARAM(0))));
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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);
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cv::gpu::transpose(rois, trois);
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cv::gpu::GpuMat curr = objectBoxes;
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cascade.detectMultiScale(hogluv, trois, curr);
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TEST_CYCLE()
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{
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curr = objectBoxes;
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cascade.detectMultiScale(hogluv, trois, curr);
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}
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SANITY_CHECK(sortDetections(curr));
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}
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NO_CPU(SoftCascadeTest, detectOnIntegral) |