action='store_true')
parser.add_argument(
"--long",
help=
"Run this command if preprocessed the data manually using --create(batch) and --append(long)",
action='store_true')
args = parser.parse_args()
if (len(sys.argv) <= 1):
parser.print_usage()
sys.exit()
trainer = TrainModel()
# Initiate Model
model = BaseModel.build(width, height, depth, classes)
# Load training data and labels
# train_data, train_labels = trainer.load_train_pickles()
# valid_data, valid_labels = trainer.load_valid_pickles()
# train_data, train_labels = convert_to_np_arrays("training_set")
# valid_data, valid_labels = convert_to_np_arrays("validation_set")
if (args.fast):
valid_data, valid_labels = process_fixed_data("validation_set", 150)
train_data, train_labels = process_fixed_data("training_set", 450)
elif (args.long):
train_data, train_labels = convert_to_np_arrays("training_set")
valid_data, valid_labels = convert_to_np_arrays("validation_set")
else:
