MultiScaleFlipAug¶
- class mmcv.transforms.MultiScaleFlipAug(transforms: List[dict], scales: Optional[Union[Tuple, List[Tuple]]] = None, scale_factor: Optional[Union[float, List[float]]] = None, allow_flip: bool = False, flip_direction: Union[str, List[str]] = 'horizontal', resize_cfg: dict = {'keep_ratio': True, 'type': 'Resize'}, flip_cfg: dict = {'type': 'RandomFlip'})[源代码]¶
Test-time augmentation with multiple scales and flipping.
An example configuration is as followed:
dict( type='MultiScaleFlipAug', scales=[(1333, 400), (1333, 800)], flip=True, transforms=[ dict(type='Normalize', **img_norm_cfg), dict(type='Pad', size_divisor=1), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']) ])
resultswill be resized using all the sizes inscales. Ifflipis True, then flipped results will also be added into output list.For the above configuration, there are four combinations of resize and flip:
Resize to (1333, 400) + no flip
Resize to (1333, 400) + flip
Resize to (1333, 800) + no flip
resize to (1333, 800) + flip
The four results are then transformed with
transformsargument. After that, results are wrapped into lists of the same length as below:dict( inputs=[...], data_samples=[...] )
Where the length of
inputsanddata_samplesare both 4.Required Keys:
Depending on the requirements of the
transformsparameter.
Modified Keys:
All output keys of each transform.
- 参数
transforms (list[dict]) – Transforms to be applied to each resized and flipped data.
scales (tuple | list[tuple] | None) – Images scales for resizing.
scale_factor (float or tuple[float]) – Scale factors for resizing. Defaults to None.
allow_flip (bool) – Whether apply flip augmentation. Defaults to False.
flip_direction (str | list[str]) – Flip augmentation directions, options are “horizontal”, “vertical” and “diagonal”. If flip_direction is a list, multiple flip augmentations will be applied. It has no effect when flip == False. Defaults to “horizontal”.
resize_cfg (dict) – Base config for resizing. Defaults to
dict(type='Resize', keep_ratio=True).flip_cfg (dict) – Base config for flipping. Defaults to
dict(type='RandomFlip').