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
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)));
}
}
-} // namespace
+} // namespace
\ No newline at end of file
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)
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)
{