bool CvCascadeParams::read( const FileNode &node )
{
if ( node.empty() )
return false;
string stageTypeStr, featureTypeStr;
FileNode rnode = node[CC_STAGE_TYPE];
if ( !rnode.isString() )
return false;
rnode >> stageTypeStr;
stageType = !stageTypeStr.compare( CC_BOOST ) ? BOOST : -1;
if (stageType == -1)
return false;
rnode = node[CC_FEATURE_TYPE];
if ( !rnode.isString() )
return false;
rnode >> featureTypeStr;
featureType = !featureTypeStr.compare( CC_HAAR ) ? CvFeatureParams::HAAR :
!featureTypeStr.compare( CC_LBP ) ? CvFeatureParams::LBP :
!featureTypeStr.compare( CC_HOG ) ? CvFeatureParams::HOG :
-1;
if (featureType == -1)
return false;
node[CC_HEIGHT] >> winSize.height;
node[CC_WIDTH] >> winSize.width;
return winSize.height > 0 && winSize.width > 0;
}
void read(const FileNode& fn)
{
FileNode n = fn["name"];
CV_Assert(n.isString() && String(n) == name);
max_iter = fn["max_iter"];
threshold = fn["threshold"];
}
void read(const FileNode& fn)
{
FileNode n = fn["name"];
CV_Assert(n.isString() && String(n) == name);
wcon = fn["contrast_weight"];
wsat = fn["saturation_weight"];
wexp = fn["exposure_weight"];
}
void read(const FileNode& fn)
{
FileNode n = fn["name"];
CV_Assert(n.isString() && String(n) == name);
gamma = fn["gamma"];
scale = fn["scale"];
saturation = fn["saturation"];
}
void read(const FileNode& fn)
{
FileNode n = fn["name"];
CV_Assert(n.isString() && String(n) == name);
max_bits = fn["max_bits"];
exclude_range = fn["exclude_range"];
int cut_val = fn["cut"];
cut = (cut_val != 0);
}
void read(const FileNode& fn)
{
FileNode n = fn["name"];
CV_Assert(n.isString() && String(n) == name);
samples = fn["samples"];
lambda = fn["lambda"];
int random_val = fn["random"];
random = (random_val != 0);
}
void read(const FileNode& fn)
{
FileNode n = fn["name"];
CV_Assert(n.isString() && String(n) == name);
gamma = fn["gamma"];
intensity = fn["intensity"];
light_adapt = fn["light_adapt"];
color_adapt = fn["color_adapt"];
}
void read(const FileNode& fn)
{
FileNode n = fn["name"];
CV_Assert(n.isString() && String(n) == name);
gamma = fn["gamma"];
contrast = fn["contrast"];
sigma_color = fn["sigma_color"];
sigma_space = fn["sigma_space"];
saturation = fn["saturation"];
}
bool CvHaarFeatureParams::read( const FileNode &node )
{
if( !CvFeatureParams::read( node ) )
return false;
FileNode rnode = node[CC_ISINTEGRAL];
if( !rnode.isString() )
return false;
String intStr;
rnode >> intStr;
isIntegral = !intStr.compare( "0" ) ? false : !true;
return true;
}
bool CvHaarFeatureParams::read( const FileNode &node )
{
if( !CvFeatureParams::read( node ) )
return false;
FileNode rnode = node[CC_MODE];
if( !rnode.isString() )
return false;
String modeStr;
rnode >> modeStr;
mode = !modeStr.compare( CC_MODE_BASIC ) ? BASIC :
!modeStr.compare( CC_MODE_CORE ) ? CORE :
!modeStr.compare( CC_MODE_ALL ) ? ALL : -1;
return (mode >= 0);
}
void read(const FileNode& fn)
{
FileNode n = fn["name"];
CV_Assert(n.isString() && String(n) == name_);
params.minDisparity = (int)fn["minDisparity"];
params.numDisparities = (int)fn["numDisparities"];
params.kernelSize = (int)fn["blockSize"];
params.speckleWindowSize = (int)fn["speckleWindowSize"];
params.speckleRange = (int)fn["speckleRange"];
params.disp12MaxDiff = (int)fn["disp12MaxDiff"];
params.preFilterType = (int)fn["preFilterType"];
params.preFilterSize = (int)fn["preFilterSize"];
params.preFilterCap = (int)fn["preFilterCap"];
params.textureThreshold = (int)fn["textureThreshold"];
params.uniquenessRatio = (int)fn["uniquenessRatio"];
}
void read(const FileNode& fn)
{
FileNode n = fn["name"];
CV_Assert(n.isString() && String(n) == name);
gamma = fn["gamma"];
}