add test that stores detections on the specific scale
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@ -71,4 +71,63 @@ TEST(SoftCascade, detect)
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// });
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}
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class SCSpecific : public ::testing::TestWithParam<std::tr1::tuple<std::string, int> > {
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};
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namespace {
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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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}
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TEST_P(SCSpecific, detect)
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{
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std::string xml = cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml";
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cv::gpu::SoftCascade cascade;
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ASSERT_TRUE(cascade.load(xml));
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std::string path = GET_PARAM(0);
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cv::Mat coloredCpu = cv::imread(cvtest::TS::ptr()->get_data_path() + path);
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ASSERT_FALSE(coloredCpu.empty());
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GpuMat colored(coloredCpu), objectBoxes(1, 1000, CV_8UC1), rois;
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int level = GET_PARAM(1);
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cascade.detectMultiScale(colored, rois, objectBoxes, 1, level);
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cv::Mat dt(objectBoxes);
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typedef cv::gpu::SoftCascade::Detection detection_t;
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detection_t* dts = (detection_t*)dt.data;
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cv::Mat result(coloredCpu);
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std::cout << "Total detections " << (dt.cols / sizeof(detection_t)) << std::endl;
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for(int i = 0; i < (int)(dt.cols / sizeof(detection_t)); ++i)
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{
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detection_t d = dts[i];
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std::cout << "detection: [" << std::setw(4) << d.x << " " << std::setw(4) << d.y
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<< "] [" << std::setw(4) << d.w << " " << std::setw(4) << d.h << "] "
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<< std::setw(12) << d.confidence << std::endl;
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cv::rectangle(result, cv::Rect(d.x, d.y, d.w, d.h), cv::Scalar(255, 0, 0, 255), 1);
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}
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std::cout << "Result stored in " << "/home/kellan/gpu_res_1_oct_" + itoa(level) << "_"
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+ itoa((dt.cols / sizeof(detection_t))) + ".png" << std::endl;
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cv::imwrite("/home/kellan/gpu_res_1_oct_" + itoa(level) + "_" + itoa((dt.cols / sizeof(detection_t))) + ".png",
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result);
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cv::imshow("res", result);
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cv::waitKey(0);
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}
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INSTANTIATE_TEST_CASE_P(inLevel, SCSpecific,
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testing::Combine(
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testing::Values(std::string("../cv/cascadeandhog/bahnhof/image_00000000_0.png")),
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testing::Range(0, 47)
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));
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#endif
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