Commit 50b636c1 authored by Davis King's avatar Davis King

Added notes that the object detector validation methods also output MAP values.

parent 77ce2775
......@@ -247,12 +247,13 @@ int main()
object_detector<image_scanner_type> detector = trainer.train(images, object_locations);
// We can easily test the new detector against our training data. This print statement will indicate that it
// has perfect precision and recall on this simple task.
cout << "Test detector (precision,recall): " << test_object_detection_function(detector, images, object_locations) << endl;
// We can easily test the new detector against our training data. This print
// statement will indicate that it has perfect precision and recall on this simple
// task. It will also print the mean average precision (MAP).
cout << "Test detector (precision,recall,MAP): " << test_object_detection_function(detector, images, object_locations) << endl;
// The cross validation should also indicate perfect precision and recall.
cout << "3-fold cross validation (precision,recall): "
cout << "3-fold cross validation (precision,recall,MAP): "
<< cross_validate_object_detection_trainer(trainer, images, object_locations, 3) << endl;
......
......@@ -207,11 +207,11 @@ int main()
object_detector<image_scanner_type> detector = trainer.train(images, object_locations);
// We can easily test the new detector against our training data. This print statement will indicate that it
// has perfect precision and recall on this simple task.
cout << "Test detector (precision,recall): " << test_object_detection_function(detector, images, object_locations) << endl;
// has perfect precision and recall on this simple task. It will also print the mean average precision (MAP).
cout << "Test detector (precision,recall,MAP): " << test_object_detection_function(detector, images, object_locations) << endl;
// The cross validation should also indicate perfect precision and recall.
cout << "3-fold cross validation (precision,recall): "
cout << "3-fold cross validation (precision,recall,MAP): "
<< cross_validate_object_detection_trainer(trainer, images, object_locations, 3) << endl;
......
......@@ -189,7 +189,7 @@ int main(int argc, char** argv)
fout.close();
cout << "Testing detector on training data..." << endl;
cout << "Test detector (precision,recall): " << test_object_detection_function(detector, images, object_locations) << endl;
cout << "Test detector (precision,recall,MAP): " << test_object_detection_function(detector, images, object_locations) << endl;
}
else
{
......@@ -197,7 +197,7 @@ int main(int argc, char** argv)
randomize_samples(images, object_locations);
// The cross validation should also indicate perfect precision and recall.
cout << num_folds << "-fold cross validation (precision,recall): "
cout << num_folds << "-fold cross validation (precision,recall,MAP): "
<< cross_validate_object_detection_trainer(trainer, images, object_locations, num_folds) << endl;
}
......@@ -252,7 +252,7 @@ int main(int argc, char** argv)
if (parser.option("test"))
{
cout << "Testing detector on data..." << endl;
cout << "Results (precision,recall): " << test_object_detection_function(detector, images, object_locations) << endl;
cout << "Results (precision,recall,MAP): " << test_object_detection_function(detector, images, object_locations) << endl;
return EXIT_SUCCESS;
}
}
......
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