void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "minDisparity" << params.minDisparity
<< "numDisparities" << params.numDisparities
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "minDisparity" << params.minDisparity
<< "numDisparities" << params.numDisparities
/** Returns the algorithm string identifier.
This string is used as top level xml/yml node tag when the object is saved to a file or string. */
CV_WRAP virtual String getDefaultName() const;
+
+protected:
+ void writeFormat(FileStorage& fs) const;
};
struct Param {
{
FileStorage fs(filename, FileStorage::WRITE);
fs << getDefaultName() << "{";
- fs << "format" << (int)3;
write(fs);
fs << "}";
}
return String("my_object");
}
+void Algorithm::writeFormat(FileStorage& fs) const
+{
+ fs << "format" << (int)3;
+}
+
}
/* End of file. */
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << "Canny_CUDA"
<< "low_thresh" << low_thresh_
<< "high_thresh" << high_thresh_
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << "HoughCirclesDetector_CUDA"
<< "dp" << dp_
<< "minDist" << minDist_
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << "HoughLinesDetector_CUDA"
<< "rho" << rho_
<< "theta" << theta_
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << "PHoughLinesDetector_CUDA"
<< "rho" << rho_
<< "theta" << theta_
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "descriptor" << descriptor;
fs << "descriptor_channels" << descriptor_channels;
fs << "descriptor_size" << descriptor_size;
void SimpleBlobDetectorImpl::write( cv::FileStorage& fs ) const
{
+ writeFormat(fs);
params.write(fs);
}
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "extended" << (int)extended;
fs << "upright" << (int)upright;
fs << "threshold" << threshold;
void FlannBasedMatcher::write( FileStorage& fs) const
{
+ writeFormat(fs);
fs << "indexParams" << "[";
if (indexParams)
return;
int i, l_count = layer_count();
+ writeFormat(fs);
fs << "layer_sizes" << layer_sizes;
write_params( fs );
if( roots.empty() )
CV_Error( CV_StsBadArg, "RTrees have not been trained" );
+ writeFormat(fs);
writeParams(fs);
int k, ntrees = (int)roots.size();
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "training_params" << "{";
write_params(fs);
fs << "}";
void write( FileStorage& fs ) const
{
+ writeFormat(fs);
impl->write(fs);
}
{
CV_Error(CV_StsBadArg,"file can't open. Check file path");
}
+ writeFormat(fs);
string desc = "Logisitic Regression Classifier";
fs<<"classifier"<<desc.c_str();
fs<<"alpha"<<this->params.alpha;
{
int nclasses = (int)cls_labels.total(), i;
+ writeFormat(fs);
fs << "var_count" << (var_idx.empty() ? nallvars : (int)var_idx.total());
fs << "var_all" << nallvars;
if( roots.empty() )
CV_Error( CV_StsBadArg, "RTrees have not been trained" );
+ writeFormat(fs);
writeParams(fs);
fs << "oob_error" << oobError;
if( !isTrained() )
CV_Error( CV_StsParseError, "SVM model data is invalid, check sv_count, var_* and class_count tags" );
+ writeFormat(fs);
write_params( fs );
fs << "var_count" << var_count;
if( !isTrained() )
CV_Error( CV_StsParseError, "SVMSGD model data is invalid, it hasn't been trained" );
+ writeFormat(fs);
writeParams( fs );
fs << "weights" << weights_;
void DTreesImpl::write( FileStorage& fs ) const
{
+ writeFormat(fs);
writeParams(fs);
writeTree(fs, roots[0]);
}
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name
<< "max_bits" << max_bits
<< "exclude_range" << exclude_range
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name
<< "samples" << samples
<< "lambda" << lambda
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name
<< "max_iter" << max_iter
<< "threshold" << threshold;
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name
<< "contrast_weight" << wcon
<< "saturation_weight" << wsat
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name
<< "gamma" << gamma;
}
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name
<< "gamma" << gamma
<< "bias" << bias
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name
<< "gamma" << gamma
<< "contrast" << contrast
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name
<< "gamma" << gamma
<< "intensity" << intensity
void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name
<< "gamma" << gamma
<< "scale" << scale
//! write/read
virtual void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "affine_type" << int(fullAffine);
}
//! write/read
virtual void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "distance" << distanceFlag
<< "rank" << rankProportion;
//! write/read
virtual void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "flag" << flag
<< "dummies" << nDummies
//! write/read
virtual void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "flag" << flag
<< "dummies" << nDummies
//! write/read
virtual void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "dummies" << nDummies
<< "default" << defaultCost;
//! write/read
virtual void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "dummies" << nDummies
<< "default" << defaultCost;
//! write/read
virtual void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "nRads" << nRadialBins
<< "nAngs" << nAngularBins
//! write/read
virtual void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "regularization" << regularizationParameter;
}
virtual void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "history" << history
<< "nsamples" << nN
virtual void write(FileStorage& fs) const
{
+ writeFormat(fs);
fs << "name" << name_
<< "history" << history
<< "nmixtures" << nmixtures