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# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.data import transforms as T
from .transforms.custom_augmentation_impl import EfficientDetResizeCrop
def build_custom_augmentation(cfg, is_train, scale=None, size=None, \
min_size=None, max_size=None):
"""
Create a list of default :class:`Augmentation` from config.
Now it includes resizing and flipping.
Returns:
list[Augmentation]
"""
if cfg.INPUT.CUSTOM_AUG == 'ResizeShortestEdge':
if is_train:
min_size = cfg.INPUT.MIN_SIZE_TRAIN if min_size is None else min_size
max_size = cfg.INPUT.MAX_SIZE_TRAIN if max_size is None else max_size
sample_style = cfg.INPUT.MIN_SIZE_TRAIN_SAMPLING
else:
min_size = cfg.INPUT.MIN_SIZE_TEST
max_size = cfg.INPUT.MAX_SIZE_TEST
sample_style = "choice"
augmentation = [T.ResizeShortestEdge(min_size, max_size, sample_style)]
elif cfg.INPUT.CUSTOM_AUG == 'EfficientDetResizeCrop':
if is_train:
scale = cfg.INPUT.SCALE_RANGE if scale is None else scale
size = cfg.INPUT.TRAIN_SIZE if size is None else size
else:
scale = (1, 1)
size = cfg.INPUT.TEST_SIZE
augmentation = [EfficientDetResizeCrop(size, scale)]
else:
assert 0, cfg.INPUT.CUSTOM_AUG
if is_train:
augmentation.append(T.RandomFlip())
return augmentation
build_custom_transform_gen = build_custom_augmentation
"""
Alias for backward-compatibility.
""" |