clip the found objects in HOG as well (http://code.opencv.org/issues/3825); added test to check CascadeClassifier on small images (http://code.opencv.org/issues/3710)
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@@ -1587,9 +1587,8 @@ bool CascadeClassifier::read(const FileNode &root)
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return ok;
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}
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static void clipObjects(Size sz, std::vector<Rect>& objects,
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std::vector<int>* a,
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std::vector<double>* b)
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void clipObjects(Size sz, std::vector<Rect>& objects,
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std::vector<int>* a, std::vector<double>* b)
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{
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size_t i, j = 0, n = objects.size();
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Rect win0 = Rect(0, 0, sz.width, sz.height);
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@@ -5,6 +5,9 @@
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namespace cv
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{
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void clipObjects(Size sz, std::vector<Rect>& objects,
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std::vector<int>* a, std::vector<double>* b);
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class FeatureEvaluator
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{
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public:
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@@ -41,6 +41,7 @@
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//M*/
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#include "precomp.hpp"
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#include "cascadedetect.hpp"
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#include "opencv2/core/core_c.h"
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#include "opencl_kernels_objdetect.hpp"
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@@ -1822,7 +1823,9 @@ static bool ocl_detectMultiScale(InputArray _img, std::vector<Rect> &found_locat
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all_candidates.push_back(Rect(Point2d(locations[j]) * scale, scaled_win_size));
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}
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found_locations.assign(all_candidates.begin(), all_candidates.end());
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cv::groupRectangles(found_locations, (int)group_threshold, 0.2);
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groupRectangles(found_locations, (int)group_threshold, 0.2);
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clipObjects(imgSize, found_locations, 0, 0);
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return true;
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}
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#endif //HAVE_OPENCL
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@@ -1878,6 +1881,7 @@ void HOGDescriptor::detectMultiScale(
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groupRectangles_meanshift(foundLocations, foundWeights, foundScales, finalThreshold, winSize);
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else
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groupRectangles(foundLocations, foundWeights, (int)finalThreshold, 0.2);
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clipObjects(imgSize, foundLocations, 0, &foundWeights);
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}
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void HOGDescriptor::detectMultiScale(InputArray img, std::vector<Rect>& foundLocations,
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