def create_character_classifier(save_to_file_path): example_dir = File("../../character_examples").getPath() nr_of_training_examples = 100 nr_of_test_examples = 0 extractor = SimpleImageFeatureExtractor(nr_of_divisions=7, size_classification_factor=1.3) training_examples, test_examples = extractor.extract_training_and_test_examples(example_dir, nr_of_training_examples, nr_of_test_examples) classifier = CharacterClassifier(training_examples, nr_of_hmms_to_try=1, fraction_of_examples_for_test=0, train_with_examples=False, initialisation_method=SpecializedHMM.InitMethod.count_based, feature_extractor=extractor) classifier_string = classifier.to_string() file = open(save_to_file_path,'w') file.write(classifier_string) file.close()
def create_character_classifier(save_to_file_path): example_dir = File("../../character_examples").getPath() nr_of_training_examples = 100 nr_of_test_examples = 0 extractor = SimpleImageFeatureExtractor(nr_of_divisions=11, size_classification_factor=4.6) training_examples, test_examples = extractor.extract_training_and_test_examples( example_dir, nr_of_training_examples, nr_of_test_examples) classifier = CharacterClassifier( training_examples, nr_of_hmms_to_try=1, fraction_of_examples_for_test=0, train_with_examples=False, initialisation_method=SpecializedHMM.InitMethod.count_based, feature_extractor=extractor) #test_result = str(classifier.test(test_examples)) #print(test_result) classifier_string = classifier.to_string() file = open(save_to_file_path + ".dat", 'w') file.write(classifier_string) file.close()