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https://github.com/opencv/opencv.git
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using argv[0] represent binary executable files' name in help() function
in sample codes instead of cpp files' name.
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@@ -8,14 +8,14 @@
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using namespace cv;
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using namespace cv::ml;
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static void help()
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static void help(char** argv)
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{
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printf(
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"\nThis sample demonstrates how to use different decision trees and forests including boosting and random trees.\n"
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"Usage:\n\t./tree_engine [-r=<response_column>] [-ts=type_spec] <csv filename>\n"
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"Usage:\n\t%s [-r=<response_column>] [-ts=type_spec] <csv filename>\n"
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"where -r=<response_column> specified the 0-based index of the response (0 by default)\n"
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"-ts= specifies the var type spec in the form ord[n1,n2-n3,n4-n5,...]cat[m1-m2,m3,m4-m5,...]\n"
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"<csv filename> is the name of training data file in comma-separated value format\n\n");
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"<csv filename> is the name of training data file in comma-separated value format\n\n", argv[0]);
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}
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static void train_and_print_errs(Ptr<StatModel> model, const Ptr<TrainData>& data)
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@@ -37,7 +37,7 @@ int main(int argc, char** argv)
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cv::CommandLineParser parser(argc, argv, "{ help h | | }{r | 0 | }{ts | | }{@input | | }");
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if (parser.has("help"))
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{
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help();
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help(argv);
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return 0;
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}
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std::string filename = parser.get<std::string>("@input");
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@@ -48,7 +48,7 @@ int main(int argc, char** argv)
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if( filename.empty() || !parser.check() )
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{
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parser.printErrors();
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help();
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help(argv);
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return 0;
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}
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printf("\nReading in %s...\n\n",filename.c_str());
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