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args.py
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args.py
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from argparse import ArgumentParser
def get_arguments():
"""Defines command-line arguments, and parses them.
"""
parser = ArgumentParser()
# Execution mode
parser.add_argument(
"--mode",
"-m",
choices=['train', 'test', 'full'],
default='train',
help=("train: performs training and validation; test: tests the model "
"found in \"--save-dir\" with name \"--name\" on \"--dataset\"; "
"full: combines train and test modes. Default: train"))
parser.add_argument(
"--resume",
action='store_true',
help=("The model found in \"--save-dir/--name/\" and filename "
"\"--name.h5\" is loaded."))
# Hyperparameters
parser.add_argument(
"--batch-size",
"-b",
type=int,
default=10,
help="The batch size. Default: 10")
parser.add_argument(
"--epochs",
type=int,
default=300,
help="Number of training epochs. Default: 300")
parser.add_argument(
"--learning-rate",
"-lr",
type=float,
default=5e-4,
help="The learning rate. Default: 5e-4")
parser.add_argument(
"--lr-decay",
type=float,
default=0.1,
help="The learning rate decay factor. Default: 0.5")
parser.add_argument(
"--lr-decay-epochs",
type=int,
default=100,
help="The number of epochs before adjusting the learning rate. "
"Default: 100")
parser.add_argument(
"--weight-decay",
"-wd",
type=float,
default=2e-4,
help="L2 regularization factor. Default: 2e-4")
# Dataset
parser.add_argument(
"--dataset",
choices=['camvid', 'cityscapes'],
default='camvid',
help="Dataset to use. Default: camvid")
parser.add_argument(
"--dataset-dir",
type=str,
default="data/CamVid",
help="Path to the root directory of the selected dataset. "
"Default: data/CamVid")
parser.add_argument(
"--height",
type=int,
default=360,
help="The image height. Default: 360")
parser.add_argument(
"--width",
type=int,
default=480,
help="The image width. Default: 480")
parser.add_argument(
"--weighing",
choices=['enet', 'mfb', 'none'],
default='ENet',
help="The class weighing technique to apply to the dataset. "
"Default: enet")
parser.add_argument(
"--with-unlabeled",
dest='ignore_unlabeled',
action='store_false',
help="The unlabeled class is not ignored.")
# Settings
parser.add_argument(
"--workers",
type=int,
default=4,
help="Number of subprocesses to use for data loading. Default: 4")
parser.add_argument(
"--print-step",
action='store_true',
help="Print loss every step")
parser.add_argument(
"--imshow-batch",
action='store_true',
help=("Displays batch images when loading the dataset and making "
"predictions."))
parser.add_argument(
"--device",
default='cuda',
help="Device on which the network will be trained. Default: cuda")
# Storage settings
parser.add_argument(
"--name",
type=str,
default='ENet',
help="Name given to the model when saving. Default: ENet")
parser.add_argument(
"--save-dir",
type=str,
default='save',
help="The directory where models are saved. Default: save")
return parser.parse_args()