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Pass train-crop-mode to create_loader/transforms from train.py args

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Ross Wightman 2024-01-24 16:19:02 -08:00
parent 53a4888328
commit 809a9e14e2
3 changed files with 10 additions and 0 deletions
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2
timm/data/loader.py
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@ -196,6 +196,7 @@ def create_loader(
re_mode: str = 'const', re_mode: str = 'const',
re_count: int = 1, re_count: int = 1,
re_split: bool = False, re_split: bool = False,
train_crop_mode: Optional[str] = None,
scale: Optional[Tuple[float, float]] = None, scale: Optional[Tuple[float, float]] = None,
ratio: Optional[Tuple[float, float]] = None, ratio: Optional[Tuple[float, float]] = None,
hflip: float = 0.5, hflip: float = 0.5,
@ -280,6 +281,7 @@ def create_loader(
input_size, input_size,
is_training=is_training, is_training=is_training,
no_aug=no_aug, no_aug=no_aug,
train_crop_mode=train_crop_mode,
scale=scale, scale=scale,
ratio=ratio, ratio=ratio,
hflip=hflip, hflip=hflip,

5
timm/data/transforms_factory.py
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@ -83,6 +83,7 @@ def transforms_imagenet_train(
Args: Args:
img_size: Target image size. img_size: Target image size.
train_crop_mode: Training random crop mode ('rrc', 'rkrc', 'rkrr').
scale: Random resize scale range (crop area, < 1.0 => zoom in). scale: Random resize scale range (crop area, < 1.0 => zoom in).
ratio: Random aspect ratio range (crop ratio for RRC, ratio adjustment factor for RKR). ratio: Random aspect ratio range (crop ratio for RRC, ratio adjustment factor for RKR).
hflip: Horizontal flip probability. hflip: Horizontal flip probability.
@ -112,6 +113,7 @@ def transforms_imagenet_train(
* normalizes and converts the branches above with the third, final transform * normalizes and converts the branches above with the third, final transform
""" """
train_crop_mode = train_crop_mode or 'rrc' train_crop_mode = train_crop_mode or 'rrc'
assert train_crop_mode in {'rrc', 'rkrc', 'rkrr'}
if train_crop_mode in ('rkrc', 'rkrr'): if train_crop_mode in ('rkrc', 'rkrr'):
# FIXME integration of RKR is a WIP # FIXME integration of RKR is a WIP
scale = tuple(scale or (0.8, 1.00)) scale = tuple(scale or (0.8, 1.00))
@ -318,6 +320,7 @@ def create_transform(
input_size: Union[int, Tuple[int, int], Tuple[int, int, int]] = 224, input_size: Union[int, Tuple[int, int], Tuple[int, int, int]] = 224,
is_training: bool = False, is_training: bool = False,
no_aug: bool = False, no_aug: bool = False,
train_crop_mode: Optional[str] = None,
scale: Optional[Tuple[float, float]] = None, scale: Optional[Tuple[float, float]] = None,
ratio: Optional[Tuple[float, float]] = None, ratio: Optional[Tuple[float, float]] = None,
hflip: float = 0.5, hflip: float = 0.5,
@ -347,6 +350,7 @@ def create_transform(
input_size: Target input size (channels, height, width) tuple or size scalar. input_size: Target input size (channels, height, width) tuple or size scalar.
is_training: Return training (random) transforms. is_training: Return training (random) transforms.
no_aug: Disable augmentation for training (useful for debug). no_aug: Disable augmentation for training (useful for debug).
train_crop_mode: Training random crop mode ('rrc', 'rkrc', 'rkrr').
scale: Random resize scale range (crop area, < 1.0 => zoom in). scale: Random resize scale range (crop area, < 1.0 => zoom in).
ratio: Random aspect ratio range (crop ratio for RRC, ratio adjustment factor for RKR). ratio: Random aspect ratio range (crop ratio for RRC, ratio adjustment factor for RKR).
hflip: Horizontal flip probability. hflip: Horizontal flip probability.
@ -400,6 +404,7 @@ def create_transform(
elif is_training: elif is_training:
transform = transforms_imagenet_train( transform = transforms_imagenet_train(
img_size, img_size,
train_crop_mode=train_crop_mode,
scale=scale, scale=scale,
ratio=ratio, ratio=ratio,
hflip=hflip, hflip=hflip,

3
train.py
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@ -245,6 +245,8 @@ group.add_argument('--decay-rate', '--dr', type=float, default=0.1, metavar='RAT
group = parser.add_argument_group('Augmentation and regularization parameters') group = parser.add_argument_group('Augmentation and regularization parameters')
group.add_argument('--no-aug', action='store_true', default=False, group.add_argument('--no-aug', action='store_true', default=False,
help='Disable all training augmentation, override other train aug args') help='Disable all training augmentation, override other train aug args')
group.add_argument('--train-crop-mode', type=str, default=None,
help='Crop-mode in train'),
group.add_argument('--scale', type=float, nargs='+', default=[0.08, 1.0], metavar='PCT', group.add_argument('--scale', type=float, nargs='+', default=[0.08, 1.0], metavar='PCT',
help='Random resize scale (default: 0.08 1.0)') help='Random resize scale (default: 0.08 1.0)')
group.add_argument('--ratio', type=float, nargs='+', default=[3. / 4., 4. / 3.], metavar='RATIO', group.add_argument('--ratio', type=float, nargs='+', default=[3. / 4., 4. / 3.], metavar='RATIO',
@ -685,6 +687,7 @@ def main():
re_mode=args.remode, re_mode=args.remode,
re_count=args.recount, re_count=args.recount,
re_split=args.resplit, re_split=args.resplit,
train_crop_mode=args.train_crop_mode,
scale=args.scale, scale=args.scale,
ratio=args.ratio, ratio=args.ratio,
hflip=args.hflip, hflip=args.hflip,