OpenCV_4.2.0/opencv_contrib-4.2.0/modules/face/samples/samplewriteconfigfile.cpp

64 lines
3.1 KiB
C++

#include "opencv2/core.hpp"
#include <iostream>
#include <string>
using namespace cv;
using namespace std;
int main(int argc,const char ** argv){
CommandLineParser parser(argc, argv,
"{ help h usage ? | | give the following arguments in following format }"
"{ filename f |. | (required) path to file which you want to create as config file [example - /data/config.xml] }"
"{ cascade_depth cd | 10 | (required) This stores the depth of cascade of regressors used for training.}"
"{ tree_depth td | 4 | (required) This stores the depth of trees created as weak learners during gradient boosting.}"
"{ num_trees_per_cascade_level| 500 | (required) This stores number of trees required per cascade level.}"
"{ learning_rate | 0.1 | (required) This stores the learning rate for gradient boosting.}"
"{ oversampling_amount | 20 | (required) This stores the oversampling amount for the samples.}"
"{ num_test_coordinates | 400 | (required) This stores number of test coordinates required for making the split.}"
"{ lambda | 0.1 | (required) This stores the value used for calculating the probabilty.}"
"{ num_test_splits | 20 | (required) This stores the number of test splits to be generated before making the best split.}"
);
// Read in the input arguments
if (parser.has("help")){
parser.printMessage();
cerr << "TIP: Use absolute paths to avoid any problems with the software!" << endl;
return 0;
}
//These variables have been initialised as defined in the research paper "One millisecond face alignment" CVPR 2014
int cascade_depth = 15;
int tree_depth = 4;
int num_trees_per_cascade_level = 500;
float learning_rate = float(0.1);
int oversampling_amount = 20;
int num_test_coordinates = 400;
float lambda = float(0.1);
int num_test_splits = 20;
cascade_depth = parser.get<int>("cascade_depth");
tree_depth = parser.get<int>("tree_depth");
num_trees_per_cascade_level = parser.get<int>("num_trees_per_cascade_level");
learning_rate = parser.get<float>("learning_rate");
oversampling_amount = parser.get<int>("oversampling_amount");
num_test_coordinates = parser.get<int>("num_test_coordinates");
lambda = parser.get<float>("lambda");
num_test_splits = parser.get<int>("num_test_splits");
string filename(parser.get<string>("filename"));
FileStorage fs(filename, FileStorage::WRITE);
if (!fs.isOpened())
{
cerr << "Failed to open " << filename << endl;
parser.printMessage();
return -1;
}
fs << "cascade_depth" << cascade_depth;
fs << "tree_depth"<< tree_depth;
fs << "num_trees_per_cascade_level" << num_trees_per_cascade_level;
fs << "learning_rate" << learning_rate;
fs << "oversampling_amount" << oversampling_amount;
fs << "num_test_coordinates" << num_test_coordinates;
fs << "lambda" << lambda ;
fs << "num_test_splits"<< num_test_splits;
fs.release();
cout << "Write Done." << endl;
return 0;
}