def test_load_directory_data():
invalid_directory_path = 'invalid_directory_path'
valid_dummy_directory = resource_filename('EmoPy','tests/unittests/resources/dummy_data_directory')
empty_dummy_directory = resource_filename('EmoPy','tests/unittests/resources/dummy_empty_data_directory')
channels = 1
# should raise error when receives an invalid directory path
with pytest.raises(NotADirectoryError):
DirectoryDataLoader(datapath=invalid_directory_path)
# should raise error when tries to load empty directory
data_loader = DirectoryDataLoader(datapath=empty_dummy_directory)
with pytest.raises(AssertionError):
data_loader.load_data()
validation_split = 0.15
verbose = True
model_name = 'inception_v3'
target_dimensions = (128, 128)
target_dimensions2 = (490, 640)
#directory_path = r'C:\Users\localadmin\Desktop\final_proj\cohn-kanade-images2'
directory_path = r'D:\Degree\Final project\cohn-kanade-formated2'
data_loader = DirectoryDataLoader(datapath=directory_path,
validation_split=validation_split,
target_dimension=target_dimensions2,
out_channels=3)
dataset = data_loader.load_data()
if verbose:
dataset.print_data_details()
print('Creating training/testing data...')
train_images, train_labels = dataset.get_training_data()
train_gen = DataGenerator().fit(train_images, train_labels)
test_images, test_labels = dataset.get_test_data()
test_gen = DataGenerator().fit(test_images, test_labels)
print('Initializing neural network with InceptionV3 base model...')
model = TransferLearningNN(model_name=model_name,
emotion_map=dataset.get_emotion_index_map())
print('Training model...')
