Skip to content

O
opencv
Commit fba62c92 authored by marina.kolpakova's avatar marina.kolpakova
Browse files
Options

fix compilation problem after rebase

parent 2bd35c43
Hide whitespace changes
Inline Side-by-side
Showing with 33 additions and 268 deletions
modules/gpu/perf/perf_objdetect.cpp
View file @ fba62c92
......@@ -89,244 +89,6 @@ PERF_TEST_P(HOG, CalTech, Values<string>("gpu/caltech/image_00000009_0.png", "gp
SANITY_CHECK(found_locations);
}
//================================================= ICF SoftCascade =================================================//
typedef pair<string, string> pair_string;
DEF_PARAM_TEST_1(SoftCascade, pair_string);
// struct SoftCascadeTest : public perf::TestBaseWithParam<roi_fixture_t>
// {
// typedef cv::gpu::SoftCascade::Detection detection_t;
// 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];
// }
// static std::string itoa(long i)
// {
// static char s[65];
// sprintf(s, "%ld", i);
// return std::string(s);
// }
// static 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";
// }
// static void print(std::ostream &out, const detection_t& d)
// {
// 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;
// }
// static void printTotal(std::ostream &out, int detbytes)
// {
// out << "\x1b[32m[ ]\x1b[0m Total detections " << (detbytes / sizeof(detection_t)) << std::endl;
// }
// static 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;
// }
// };
typedef std::tr1::tuple<std::string, std::string> fixture_t;
typedef perf::TestBaseWithParam<fixture_t> SoftCascadeTest;
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"))))
{
if (runOnGpu)
{
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, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1), trois;
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);
}
}
else
{
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>objectBoxes;
cascade.detectMultiScale(colored, rois, objectBoxes);
TEST_CYCLE()
{
cascade.detectMultiScale(colored, rois, objectBoxes);
}
}
}
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;
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)))
{
if (runOnGpu)
{
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);
}
}
else
{
FAIL();
}
}
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)))
{
if (runOnGpu)
{
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, rois, curr);
}
}
else
{
FAIL();
}
}
///////////////////////////////////////////////////////////////
// HaarClassifier
......@@ -383,7 +145,7 @@ PERF_TEST_P(ImageAndCascade, ObjDetect_LBPClassifier,
cv::Mat img = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
if (runOnGpu)
if (PERF_RUN_GPU())
{
cv::gpu::CascadeClassifier_GPU d_cascade;
ASSERT_TRUE(d_cascade.load(perf::TestBase::getDataPath(GetParam().second)));
......@@ -418,4 +180,4 @@ PERF_TEST_P(ImageAndCascade, ObjDetect_LBPClassifier,
}
}
} // namespace
} // namespace
\ No newline at end of file
modules/gpu/perf/perf_softcascade.cpp
View file @ fba62c92
......@@ -34,17 +34,17 @@ namespace {
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;
}
// 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)
......@@ -95,28 +95,30 @@ RUN_GPU(SoftCascadeTest, detect)
SANITY_CHECK(sortDetections(curr));
}
RUN_CPU(SoftCascadeTest, detect)
{
cv::Mat colored = readImage(GET_PARAM(1));
ASSERT_FALSE(colored.empty());
NO_CPU(SoftCascadeTest, detect)
cv::SoftCascade cascade;
ASSERT_TRUE(cascade.load(getDataPath(GET_PARAM(0))));
// RUN_CPU(SoftCascadeTest, detect)
// {
// cv::Mat colored = readImage(GET_PARAM(1));
// ASSERT_FALSE(colored.empty());
std::vector<cv::Rect> rois;
// cv::SoftCascade cascade;
// ASSERT_TRUE(cascade.load(getDataPath(GET_PARAM(0))));
typedef cv::SoftCascade::Detection Detection;
std::vector<Detection>objects;
cascade.detectMultiScale(colored, rois, objects);
// std::vector<cv::Rect> rois;
TEST_CYCLE()
{
cascade.detectMultiScale(colored, rois, objects);
}
// typedef cv::SoftCascade::Detection Detection;
// std::vector<Detection>objects;
// cascade.detectMultiScale(colored, rois, objects);
std::sort(objects.begin(), objects.end(), DetectionLess());
SANITY_CHECK(objects);
}
// TEST_CYCLE()
// {
// cascade.detectMultiScale(colored, rois, objects);
// }
// std::sort(objects.begin(), objects.end(), DetectionLess());
// SANITY_CHECK(objects);
// }
static cv::Rect getFromTable(int idx)
{
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment