diff --git a/modules/haartraining/createsamples.cpp b/modules/haartraining/createsamples.cpp index 71debcc94..250af672f 100644 --- a/modules/haartraining/createsamples.cpp +++ b/modules/haartraining/createsamples.cpp @@ -49,6 +49,7 @@ #include #include #include +#include using namespace std; @@ -76,6 +77,8 @@ int main( int argc, char* argv[] ) int width = 24; int height = 24; + srand(time(0)); + if( argc == 1 ) { printf( "Usage: %s\n [-info ]\n" diff --git a/modules/haartraining/cvhaartraining.cpp b/modules/haartraining/cvhaartraining.cpp index 76fd6b265..2bb90adaa 100644 --- a/modules/haartraining/cvhaartraining.cpp +++ b/modules/haartraining/cvhaartraining.cpp @@ -1354,8 +1354,9 @@ void icvGetNextFromBackgroundData( CvBackgroundData* data, // printf( "Open background image: %s\n", data->filename[data->last] ); //#endif /* CV_VERBOSE */ - img = cvLoadImage( data->filename[data->last++], 0 ); + data->last = rand() % data->count; data->last %= data->count; + img = cvLoadImage( data->filename[data->last], 0 ); if( !img ) continue; data->round += data->last / data->count; diff --git a/modules/objdetect/include/opencv2/objdetect/objdetect.hpp b/modules/objdetect/include/opencv2/objdetect/objdetect.hpp index 0bfb37e05..3115a8650 100644 --- a/modules/objdetect/include/opencv2/objdetect/objdetect.hpp +++ b/modules/objdetect/include/opencv2/objdetect/objdetect.hpp @@ -311,11 +311,10 @@ public: Size minSize=Size(), Size maxSize=Size() ); - bool isOldFormatCascade() const; virtual Size getOriginalWindowSize() const; int getFeatureType() const; - bool setImage(const Mat&); + bool setImage( const Mat& ); protected: virtual bool detectSingleScale( const Mat& image, int stripCount, Size processingRectSize, diff --git a/modules/objdetect/src/cascadedetect.cpp b/modules/objdetect/src/cascadedetect.cpp index 200a3f885..4e18c2dda 100644 --- a/modules/objdetect/src/cascadedetect.cpp +++ b/modules/objdetect/src/cascadedetect.cpp @@ -872,7 +872,7 @@ Size CascadeClassifier::getOriginalWindowSize() const bool CascadeClassifier::setImage(const Mat& image) { - featureEvaluator->setImage(image, data.origWinSize); + return featureEvaluator->setImage(image, data.origWinSize); } void CascadeClassifier::detectMultiScale( const Mat& image, vector& objects,