update argmyparse.py

segmentation/argmyparse.py

@@ -52,25 +52,42 @@ def get_common_training_parser(parser):
  help='momentum sgd (default: 0.9)')
  parser.add_argument('--weight_decay', type=float, default=2e-5,
  help='weight_decay (default: 2e-5)')
- parser.add_argument('--batch_size', type=int, default=1,
+ parser.add_argument('-b', '--batch_size', type=int, default=1,
  help="batch_size")
-
+ parser.add_argument("--normalize_way", type=str, default="imagenet", choices=["imagenet", "None"],
+ help="normalize way")
+
  # ---------- Optional Hyperparameters ---------- #
- parser.add_argument('--augment', action="store_true",
- help='whether you use data-augmentation or not')
-
- # ---------- Input Image Setting ---------- #
+ # parser.add_argument('--augment', action="store_true",
+ # help='whether you use data-augmentation or not')
+ parser.add_argument('--crop_size', type=int, default=-1,
+ help='crop size (default: -1): 512 is good for cityscapes')
+ # 512 is derived from https://github.com/mitmul/chainer-pspnet/blob/05545d5ed254ec557697442cf98b1a2c5135216a/datasets/cityscapes/cityscapes_transformed.py#L13
+ parser.add_argument('--rotate_angle', type=int, default=0,
+ help='crop size (default: -1): lower than 10 is good(?)')
+
+ parser.add_argument('--loss_weights_file', type=str, default=None,
+ help='Use this when you control the loss per class')
+ parser.add_argument("--add_bg_loss", action="store_true",
+ help='whether you add background loss or not')
+ parser.add_argument("--fix_bn", action="store_true",
+ help='whether you fix the paramters of batch normalization layer')
+ parser.add_argument("--no_dropout", action="store_true",
+ help='whether you use dropout')
+
+ # ---------- Input Information Setting ---------- #
  parser.add_argument("--input_ch", type=int, default=3,
  choices=[1, 3, 4])
  parser.add_argument('--train_img_shape', default=(1024, 512), nargs=2, metavar=("W", "H"),
  help="W H")
-
+ parser.add_argument("--background_id", type=int, default=255,
+ help="background id")
+
  # ---------- Whether to Resume ---------- #
  parser.add_argument("--resume", type=str, default=None, metavar="PTH.TAR",
  help="model(pth) path")
  return parser
 
-
 def get_src_only_training_parser(parser=None):
  if parser is None:
  parser = argparse.ArgumentParser(description='PyTorch Segmentation Adaptation')