def train_test_dog_breed_detector(do_model_test=True):
'''
Trains and tests the dog breed detector model
:param do_model_test: set to True for running prediction on the test data
:return: dog breed detector model
'''
# get train and validation data and labels
data_extractor = DataExtractor('dog_images/train', 'dog_images/valid',
'dog_images/test')
train_data = data_extractor.load_train_data()
train_labels, train_num_dog_breeds = data_extractor.load_train_labels()
valid_data = data_extractor.load_valid_data()
valid_labels, valid_num_dog_breeds = data_extractor.load_valid_labels()
assert train_num_dog_breeds == valid_num_dog_breeds
# create and init the model
model = DogBreedDetectorModel(num_dog_breeds=train_num_dog_breeds)
model.init_model(train_data)
# train the model
if not model.load_model():
model.train(train_data, train_labels, valid_data, valid_labels)
# load test data and predict
if do_model_test:
test_data = data_extractor.load_test_data()
test_labels, test_num_dog_breeds = data_extractor.load_test_labels()
assert train_num_dog_breeds == test_num_dog_breeds
model.predict(test_data, test_labels)
return model
