import copy
import warnings
[docs]def replace_ImageToTensor(pipelines):
"""Replace the ImageToTensor transform in a data pipeline to
DefaultFormatBundle, which is normally useful in batch inference.
Args:
pipelines (list[dict]): Data pipeline configs.
Returns:
list: The new pipeline list with all ImageToTensor replaced by
DefaultFormatBundle.
Examples:
>>> pipelines = [
... dict(type='LoadImageFromFile'),
... dict(
... type='MultiScaleFlipAug',
... img_scale=(1333, 800),
... flip=False,
... transforms=[
... dict(type='Resize', keep_ratio=True),
... dict(type='RandomFlip'),
... dict(type='Normalize', mean=[0, 0, 0], std=[1, 1, 1]),
... dict(type='Pad', size_divisor=32),
... dict(type='ImageToTensor', keys=['img']),
... dict(type='Collect', keys=['img']),
... ])
... ]
>>> expected_pipelines = [
... dict(type='LoadImageFromFile'),
... dict(
... type='MultiScaleFlipAug',
... img_scale=(1333, 800),
... flip=False,
... transforms=[
... dict(type='Resize', keep_ratio=True),
... dict(type='RandomFlip'),
... dict(type='Normalize', mean=[0, 0, 0], std=[1, 1, 1]),
... dict(type='Pad', size_divisor=32),
... dict(type='DefaultFormatBundle'),
... dict(type='Collect', keys=['img']),
... ])
... ]
>>> assert expected_pipelines == replace_ImageToTensor(pipelines)
"""
pipelines = copy.deepcopy(pipelines)
for i, pipeline in enumerate(pipelines):
if pipeline['type'] == 'MultiScaleFlipAug':
assert 'transforms' in pipeline
pipeline['transforms'] = replace_ImageToTensor(
pipeline['transforms'])
elif pipeline['type'] == 'ImageToTensor':
warnings.warn(
'"ImageToTensor" pipeline is replaced by '
'"DefaultFormatBundle" for batch inference. It is '
'recommended to manually replace it in the test '
'data pipeline in your config file.', UserWarning)
pipelines[i] = {'type': 'DefaultFormatBundle'}
return pipelines