remove input frame size constraints
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3cb9afb4e7
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@ -56,6 +56,18 @@ PERF_TEST_P(ImageName_MinSize, CascadeClassifierLBPFrontalFace,
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typedef std::tr1::tuple<std::string, std::string> fixture;
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typedef perf::TestBaseWithParam<fixture> detect;
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namespace {
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typedef cv::SoftCascade::Detection detection_t;
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void extractRacts(std::vector<detection_t> objectBoxes, vector<Rect> rects)
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{
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rects.clear();
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for (int i = 0; i < (int)objectBoxes.size(); ++i)
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rects.push_back(objectBoxes[i].rect);
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}
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}
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PERF_TEST_P(detect, SoftCascade,
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testing::Combine(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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@ -76,5 +88,9 @@ PERF_TEST_P(detect, SoftCascade,
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{
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cascade.detectMultiScale(colored, rois, objectBoxes);
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}
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SANITY_CHECK(objectBoxes);
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vector<Rect> rects;
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extractRacts(objectBoxes, rects);
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std::sort(rects.begin(), rects.end(), comparators::RectLess());
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SANITY_CHECK(rects);
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}
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@ -44,44 +44,6 @@
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#include <opencv2/objdetect/objdetect.hpp>
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#include <opencv2/core/core.hpp>
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template<typename T>
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struct Decimate {
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int shrinkage;
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Decimate(const int sr) : shrinkage(sr) {}
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void operator()(const cv::Mat& in, cv::Mat& out) const
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{
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int cols = in.cols / shrinkage;
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int rows = in.rows / shrinkage;
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out.create(rows, cols, in.type());
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CV_Assert(cols * shrinkage == in.cols);
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CV_Assert(rows * shrinkage == in.rows);
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for (int outIdx_y = 0; outIdx_y < rows; ++outIdx_y)
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{
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T* outPtr = out.ptr<T>(outIdx_y);
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for (int outIdx_x = 0; outIdx_x < cols; ++outIdx_x)
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{
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// do desimate
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int inIdx_y = outIdx_y * shrinkage;
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int inIdx_x = outIdx_x * shrinkage;
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int sum = 0;
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for (int y = inIdx_y; y < inIdx_y + shrinkage; ++y)
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for (int x = inIdx_x; x < inIdx_x + shrinkage; ++x)
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sum += in.at<T>(y, x);
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sum /= shrinkage * shrinkage;
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outPtr[outIdx_x] = cv::saturate_cast<T>(sum);
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}
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}
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}
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};
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void cv::IntegralChannels::createHogBins(const cv::Mat gray, std::vector<cv::Mat>& integrals, int bins) const
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{
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CV_Assert(gray.type() == CV_8UC1);
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@ -89,8 +51,6 @@ void cv::IntegralChannels::createHogBins(const cv::Mat gray, std::vector<cv::Mat
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int w = gray.cols;
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CV_Assert(!(w % shrinkage) && !(h % shrinkage));
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Decimate<uchar> decimate(shrinkage);
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cv::Mat df_dx, df_dy, mag, angle;
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cv::Sobel(gray, df_dx, CV_32F, 1, 0, 3, 0.125);
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cv::Sobel(gray, df_dy, CV_32F, 0, 1, 3, 0.125);
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@ -121,13 +81,13 @@ void cv::IntegralChannels::createHogBins(const cv::Mat gray, std::vector<cv::Mat
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for(int i = 0; i < bins; ++i)
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{
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cv::Mat shrunk, sum;
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decimate(hist[i], shrunk);
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cv::resize(hist[i], shrunk, cv::Size(), 1.0 / shrinkage, 1.0 / shrinkage, CV_INTER_AREA);
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cv::integral(shrunk, sum, cv::noArray(), CV_32S);
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integrals.push_back(sum);
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}
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cv::Mat shrMag;
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decimate(nmag, shrMag);
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cv::resize(nmag, shrMag, cv::Size(), 1.0 / shrinkage, 1.0 / shrinkage, CV_INTER_AREA);
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cv::integral(shrMag, mag, cv::noArray(), CV_32S);
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integrals.push_back(mag);
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}
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@ -137,8 +97,6 @@ void cv::IntegralChannels::createLuvBins(const cv::Mat frame, std::vector<cv::Ma
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CV_Assert(frame.type() == CV_8UC3);
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CV_Assert(!(frame.cols % shrinkage) && !(frame.rows % shrinkage));
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Decimate<uchar> decimate(shrinkage);
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cv::Mat luv;
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cv::cvtColor(frame, luv, CV_BGR2Luv);
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@ -148,7 +106,7 @@ void cv::IntegralChannels::createLuvBins(const cv::Mat frame, std::vector<cv::Ma
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for (size_t i = 0; i < splited.size(); ++i)
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{
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cv::Mat shrunk, sum;
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decimate(splited[i], shrunk);
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cv::resize(splited[i], shrunk, cv::Size(), 1.0 / shrinkage, 1.0 / shrinkage, CV_INTER_AREA);
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cv::integral(shrunk, sum, cv::noArray(), CV_32S);
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integrals.push_back(sum);
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}
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@ -396,16 +396,6 @@ struct cv::SoftCascade::Filds
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if (fabs(scale - maxScale) < FLT_EPSILON) break;
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scale = std::min(maxScale, expf(log(scale) + logFactor));
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std::cout << "level " << sc << " scale "
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<< levels[sc].origScale
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<< " octeve "
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<< levels[sc].octave->scale
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<< " "
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<< levels[sc].relScale
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<< " [" << levels[sc].objSize.width
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<< " " << levels[sc].objSize.height << "] ["
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<< levels[sc].workRect.width << " " << levels[sc].workRect.height << "]" << std::endl;
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}
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}
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@ -523,10 +513,7 @@ bool cv::SoftCascade::read( const cv::FileStorage& fs)
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filds = new Filds;
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Filds& flds = *filds;
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if (!flds.fill(fs.getFirstTopLevelNode(), minScale, maxScale)) return false;
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// flds.calcLevels(FRAME_WIDTH, FRAME_HEIGHT, scales);
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return true;
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return flds.fill(fs.getFirstTopLevelNode(), minScale, maxScale);
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}
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void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::Rect>& /*rois*/,
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@ -535,9 +522,6 @@ void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::R
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// only color images are supperted
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CV_Assert(image.type() == CV_8UC3);
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// only this window size allowed
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CV_Assert(image.cols == 640 && image.rows == 480);
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Filds& fld = *filds;
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fld.calcLevels(image.size(), scales);
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@ -68,29 +68,29 @@ TEST(SoftCascade, detect)
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cascade.detectMultiScale(colored, rois, objects);
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cv::Mat out = colored.clone();
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int level = 0, total = 0;
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int levelWidth = objects[0].rect.width;
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// cv::Mat out = colored.clone();
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// int level = 0, total = 0;
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// int levelWidth = objects[0].rect.width;
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for(int i = 0 ; i < (int)objects.size(); ++i)
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{
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if (objects[i].rect.width != levelWidth)
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{
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std::cout << "Level: " << level << " total " << total << std::endl;
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cv::imshow("out", out);
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cv::waitKey(0);
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out = colored.clone();
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levelWidth = objects[i].rect.width;
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total = 0;
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level++;
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}
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cv::rectangle(out, objects[i].rect, cv::Scalar(255, 0, 0, 255), 1);
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std::cout << "detection: " << objects[i].rect.x
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<< " " << objects[i].rect.y
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<< " " << objects[i].rect.width
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<< " " << objects[i].rect.height << std::endl;
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total++;
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}
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std::cout << "detected: " << (int)objects.size() << std::endl;
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ASSERT_EQ((int)objects.size(), 1469);
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// for(int i = 0 ; i < (int)objects.size(); ++i)
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// {
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// if (objects[i].rect.width != levelWidth)
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// {
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// std::cout << "Level: " << level << " total " << total << std::endl;
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// cv::imshow("out", out);
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// cv::waitKey(0);
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// out = colored.clone();
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// levelWidth = objects[i].rect.width;
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// total = 0;
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// level++;
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// }
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// cv::rectangle(out, objects[i].rect, cv::Scalar(255, 0, 0, 255), 1);
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// std::cout << "detection: " << objects[i].rect.x
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// << " " << objects[i].rect.y
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// << " " << objects[i].rect.width
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// << " " << objects[i].rect.height << std::endl;
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// total++;
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// }
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// std::cout << "detected: " << (int)objects.size() << std::endl;
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ASSERT_EQ((int)objects.size(), 3668);
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}
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