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Fix warnings as errors.

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This commit is contained in:
Mathieu Barnachon 2013-11-24 15:32:52 +01:00
parent 63c23cce65
commit e015691b41
1 changed files with 20 additions and 15 deletions
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35
samples/cpp/train_HOG.cpp
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@ -38,7 +38,7 @@ void get_svm_detector(const SVM& svm, vector< float > & hog_detector )
decision_func != 0 &&
decision_func->alpha != 0 &&
decision_func->sv_count == sv_total );
float svi = 0.f;
hog_detector.clear(); //clear stuff in vector.
@ -108,11 +108,15 @@ void load_images( const string & prefix, const string & filename, vector< Mat >
exit( -1 );
}
while( 1 )
bool end_of_parsing = false;
while( !end_of_parsing )
{
getline( file, line );
if( line == "" ) // no more file to read
{
end_of_parsing = true;
break;
}
Mat img = imread( (prefix+line).c_str() ); // load the image
if( !img.data ) // invalid image, just skip it.
continue;
@ -133,7 +137,7 @@ void sample_neg( const vector< Mat > & full_neg_lst, vector< Mat > & neg_lst, co
const int size_x = box.width;
const int size_y = box.height;
srand( time( NULL ) );
srand( (unsigned int)time( NULL ) );
vector< Mat >::const_iterator img = full_neg_lst.begin();
vector< Mat >::const_iterator end = full_neg_lst.end();
@ -152,16 +156,16 @@ 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 )
{
{
const int DIMX = size.width;
const int DIMY = size.height;
float zoomFac = 3;
Mat visu;
resize(color_origImg, visu, Size(color_origImg.cols*zoomFac, color_origImg.rows*zoomFac));
resize(color_origImg, visu, Size( (int)(color_origImg.cols*zoomFac), (int)(color_origImg.rows*zoomFac) ) );
int cellSize = 8;
int gradientBinSize = 9;
float radRangeForOneBin = CV_PI/(float)gradientBinSize; // dividing 180° into 9 bins, how large (in rad) is one bin?
float radRangeForOneBin = (float)(CV_PI/(float)gradientBinSize); // dividing 180° into 9 bins, how large (in rad) is one bin?
// prepare data structure: 9 orientation / gradient strenghts for each cell
int cells_in_x_dir = DIMX / cellSize;
@ -194,7 +198,7 @@ Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues,
for (int blockx=0; blockx<blocks_in_x_dir; blockx++)
{
for (int blocky=0; blocky<blocks_in_y_dir; blocky++)
for (int blocky=0; blocky<blocks_in_y_dir; blocky++)
{
// 4 cells per block ...
for (int cellNr=0; cellNr<4; cellNr++)
@ -259,7 +263,7 @@ Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues,
int mx = drawX + cellSize/2;
int my = drawY + cellSize/2;
rectangle(visu, Point(drawX*zoomFac,drawY*zoomFac), Point((drawX+cellSize)*zoomFac,(drawY+cellSize)*zoomFac), CV_RGB(100,100,100), 1);
rectangle(visu, Point((int)(drawX*zoomFac), (int)(drawY*zoomFac)), Point((int)((drawX+cellSize)*zoomFac), (int)((drawY+cellSize)*zoomFac)), CV_RGB(100,100,100), 1);
// draw in each cell all 9 gradient strengths
for (int bin=0; bin<gradientBinSize; bin++)
@ -274,7 +278,7 @@ Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues,
float dirVecX = cos( currRad );
float dirVecY = sin( currRad );
float maxVecLen = cellSize/2;
float maxVecLen = (float)(cellSize/2.f);
float scale = 2.5; // just a visualization scale, to see the lines better
// compute line coordinates
@ -284,7 +288,7 @@ Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues,
float y2 = my + dirVecY * currentGradStrength * maxVecLen * scale;
// draw gradient visualization
line(visu, Point(x1*zoomFac,y1*zoomFac), Point(x2*zoomFac,y2*zoomFac), CV_RGB(0,255,0), 1);
line(visu, Point((int)(x1*zoomFac),(int)(y1*zoomFac)), Point((int)(x2*zoomFac),(int)(y2*zoomFac)), CV_RGB(0,255,0), 1);
} // for (all bins)
@ -297,7 +301,7 @@ Mat get_hogdescriptor_visu(Mat& color_origImg, vector<float>& descriptorValues,
{
for (int x=0; x<cells_in_x_dir; x++)
{
delete[] gradientStrengths[y][x];
delete[] gradientStrengths[y][x];
}
delete[] gradientStrengths[y];
delete[] cellUpdateCounter[y];
@ -399,7 +403,8 @@ void test_it( const Size & size )
exit( -1 );
}
while( true )
bool end_of_process = false;
while( !end_of_process )
{
video >> img;
if( !img.data )
@ -416,9 +421,9 @@ void test_it( const Size & size )
draw_locations( draw, locations, trained );
imshow( "Video", draw );
key = waitKey( 10 );
key = (char)waitKey( 10 );
if( 27 == key )
break;
end_of_process = true;
}
}
@ -439,7 +444,7 @@ int main( int argc, char** argv )
load_images( argv[1], argv[2], pos_lst );
labels.assign( pos_lst.size(), +1 );
const unsigned int old = labels.size();
const unsigned int old = (unsigned int)labels.size();
load_images( argv[3], argv[4], full_neg_lst );
sample_neg( full_neg_lst, neg_lst, Size( 96,160 ) );
labels.insert( labels.end(), neg_lst.size(), -1 );