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()
