From 7e943808b6f136f9d736a0f2cedbcb6077f9c366 Mon Sep 17 00:00:00 2001 From: Suleyman TURKMEN Date: Thu, 23 Jul 2020 14:39:40 +0300 Subject: [PATCH] Update train_HOG.cpp --- samples/cpp/train_HOG.cpp | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/samples/cpp/train_HOG.cpp b/samples/cpp/train_HOG.cpp index 356ff0e..4a160fe 100644 --- a/samples/cpp/train_HOG.cpp +++ b/samples/cpp/train_HOG.cpp @@ -74,9 +74,9 @@ void load_images( const String & dirname, vector< Mat > & img_lst, bool showImag for ( size_t i = 0; i < files.size(); ++i ) { Mat img = imread( files[i] ); // load the image - if ( img.empty() ) // invalid image, skip it. + if ( img.empty() ) { - cout << files[i] << " is invalid!" << endl; + cout << files[i] << " is invalid!" << endl; // invalid image, skip it. continue; } @@ -95,16 +95,13 @@ void sample_neg( const vector< Mat > & full_neg_lst, vector< Mat > & neg_lst, co box.width = size.width; box.height = size.height; - const int size_x = box.width; - const int size_y = box.height; - srand( (unsigned int)time( NULL ) ); for ( size_t i = 0; i < full_neg_lst.size(); i++ ) if ( full_neg_lst[i].cols > box.width && full_neg_lst[i].rows > box.height ) { - box.x = rand() % ( full_neg_lst[i].cols - size_x ); - box.y = rand() % ( full_neg_lst[i].rows - size_y ); + box.x = rand() % ( full_neg_lst[i].cols - box.width ); + box.y = rand() % ( full_neg_lst[i].rows - box.height ); Mat roi = full_neg_lst[i]( box ); neg_lst.push_back( roi.clone() ); } @@ -259,7 +256,7 @@ int main( int argc, char** argv ) load_images( pos_dir, pos_lst, visualization ); if ( pos_lst.size() > 0 ) { - clog << "...[done]" << endl; + clog << "...[done] " << pos_lst.size() << " files." << endl; } else { @@ -287,22 +284,25 @@ int main( int argc, char** argv ) } clog << "Negative images are being loaded..."; - load_images( neg_dir, full_neg_lst, false ); + load_images( neg_dir, full_neg_lst, visualization ); + clog << "...[done] " << full_neg_lst.size() << " files." << endl; + + clog << "Negative images are being processed..."; sample_neg( full_neg_lst, neg_lst, pos_image_size ); - clog << "...[done]" << endl; + clog << "...[done] " << neg_lst.size() << " files." << endl; clog << "Histogram of Gradients are being calculated for positive images..."; computeHOGs( pos_image_size, pos_lst, gradient_lst, flip_samples ); size_t positive_count = gradient_lst.size(); labels.assign( positive_count, +1 ); - clog << "...[done] ( positive count : " << positive_count << " )" << endl; + clog << "...[done] ( positive images count : " << positive_count << " )" << endl; clog << "Histogram of Gradients are being calculated for negative images..."; computeHOGs( pos_image_size, neg_lst, gradient_lst, flip_samples ); size_t negative_count = gradient_lst.size() - positive_count; labels.insert( labels.end(), negative_count, -1 ); CV_Assert( positive_count < labels.size() ); - clog << "...[done] ( negative count : " << negative_count << " )" << endl; + clog << "...[done] ( negative images count : " << negative_count << " )" << endl; Mat train_data; convert_to_ml( gradient_lst, train_data ); @@ -324,7 +324,7 @@ int main( int argc, char** argv ) if ( train_twice ) { - clog << "Testing trained detector on negative images. This may take a few minutes..."; + clog << "Testing trained detector on negative images. This might take a few minutes..."; HOGDescriptor my_hog; my_hog.winSize = pos_image_size; -- 2.7.4