Commit e1955759 authored by Mathieu Barnachon's avatar Mathieu Barnachon

Fix some warning.

Adding missing credit for a function.
parent a4ceb7b6
...@@ -150,6 +150,7 @@ void sample_neg( const vector< Mat > & full_neg_lst, vector< Mat > & neg_lst, co ...@@ -150,6 +150,7 @@ void sample_neg( const vector< Mat > & full_neg_lst, vector< Mat > & neg_lst, co
} }
} }
// From http://www.juergenwiki.de/work/wiki/doku.php?id=public:hog_descriptor_computation_and_visualization
Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues, const Size & size ) Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues, const Size & size )
{ {
const int DIMX = size.width; const int DIMX = size.width;
...@@ -158,7 +159,6 @@ Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues, ...@@ -158,7 +159,6 @@ Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues,
Mat visu; Mat visu;
resize(color_origImg, visu, Size(color_origImg.cols*zoomFac, color_origImg.rows*zoomFac)); resize(color_origImg, visu, Size(color_origImg.cols*zoomFac, color_origImg.rows*zoomFac));
int blockSize = 16;
int cellSize = 8; int cellSize = 8;
int gradientBinSize = 9; int gradientBinSize = 9;
float radRangeForOneBin = CV_PI/(float)gradientBinSize; // dividing 180 into 9 bins, how large (in rad) is one bin? float radRangeForOneBin = CV_PI/(float)gradientBinSize; // dividing 180 into 9 bins, how large (in rad) is one bin?
...@@ -166,7 +166,6 @@ Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues, ...@@ -166,7 +166,6 @@ Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues,
// prepare data structure: 9 orientation / gradient strenghts for each cell // prepare data structure: 9 orientation / gradient strenghts for each cell
int cells_in_x_dir = DIMX / cellSize; int cells_in_x_dir = DIMX / cellSize;
int cells_in_y_dir = DIMY / cellSize; int cells_in_y_dir = DIMY / cellSize;
int totalnrofcells = cells_in_x_dir * cells_in_y_dir;
float*** gradientStrengths = new float**[cells_in_y_dir]; float*** gradientStrengths = new float**[cells_in_y_dir];
int** cellUpdateCounter = new int*[cells_in_y_dir]; int** cellUpdateCounter = new int*[cells_in_y_dir];
for (int y=0; y<cells_in_y_dir; y++) for (int y=0; y<cells_in_y_dir; y++)
...@@ -201,8 +200,8 @@ Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues, ...@@ -201,8 +200,8 @@ Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues,
for (int cellNr=0; cellNr<4; cellNr++) for (int cellNr=0; cellNr<4; cellNr++)
{ {
// compute corresponding cell nr // compute corresponding cell nr
int cellx = blockx; cellx = blockx;
int celly = blocky; celly = blocky;
if (cellNr==1) celly++; if (cellNr==1) celly++;
if (cellNr==2) cellx++; if (cellNr==2) cellx++;
if (cellNr==3) if (cellNr==3)
...@@ -440,7 +439,7 @@ int main( int argc, char** argv ) ...@@ -440,7 +439,7 @@ int main( int argc, char** argv )
load_images( argv[1], argv[2], pos_lst ); load_images( argv[1], argv[2], pos_lst );
labels.assign( pos_lst.size(), +1 ); labels.assign( pos_lst.size(), +1 );
const int old = labels.size(); const unsigned int old = labels.size();
load_images( argv[3], argv[4], full_neg_lst ); load_images( argv[3], argv[4], full_neg_lst );
sample_neg( full_neg_lst, neg_lst, Size( 96,160 ) ); sample_neg( full_neg_lst, neg_lst, Size( 96,160 ) );
labels.insert( labels.end(), neg_lst.size(), -1 ); labels.insert( labels.end(), neg_lst.size(), -1 );
......
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