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