from collections.abc import Sequence
from mmcv.utils import build_from_cfg
from ..registry import PIPELINES
[docs]@PIPELINES.register_module()
class Compose(object):
"""Compose a data pipeline with a sequence of transforms.
Args:
transforms (list[dict | callable]):
Either config dicts of transforms or transform objects.
"""
def __init__(self, transforms):
assert isinstance(transforms, Sequence)
self.transforms = []
for transform in transforms:
if isinstance(transform, dict):
transform = build_from_cfg(transform, PIPELINES)
self.transforms.append(transform)
elif callable(transform):
self.transforms.append(transform)
else:
raise TypeError(f'transform must be callable or a dict, '
f'but got {type(transform)}')
def __call__(self, data):
"""Call function.
Args:
data (dict): A dict containing the necessary information and
data for augmentation.
Returns:
dict: A dict containing the processed data and information.
"""
for t in self.transforms:
data = t(data)
if data is None:
return None
return data
def __repr__(self):
format_string = self.__class__.__name__ + '('
for t in self.transforms:
format_string += '\n'
format_string += f' {t}'
format_string += '\n)'
return format_string