AugMix¶
- class torchvision.transforms.v2.AugMix(severity: int = 3, mixture_width: int = 3, chain_depth: int = - 1, alpha: float = 1.0, all_ops: bool = True, interpolation: Union[InterpolationMode, int] = InterpolationMode.BILINEAR, fill: Union[int, float, Sequence[int], Sequence[float], None, Dict[Union[Type, str], Optional[Union[int, float, Sequence[int], Sequence[float]]]]] = None)[source]¶
AugMix data augmentation method based on “AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty”.
This transformation works on images and videos only.
If the input is
torch.Tensor
, it should be of typetorch.uint8
, and it is expected to have […, 1 or 3, H, W] shape, where … means an arbitrary number of leading dimensions. If img is PIL Image, it is expected to be in mode “L” or “RGB”.- Parameters:
severity (int, optional) – The severity of base augmentation operators. Default is
3
.mixture_width (int, optional) – The number of augmentation chains. Default is
3
.chain_depth (int, optional) – The depth of augmentation chains. A negative value denotes stochastic depth sampled from the interval [1, 3]. Default is
-1
.alpha (float, optional) – The hyperparameter for the probability distributions. Default is
1.0
.all_ops (bool, optional) – Use all operations (including brightness, contrast, color and sharpness). Default is
True
.interpolation (InterpolationMode, optional) – Desired interpolation enum defined by
torchvision.transforms.InterpolationMode
. Default isInterpolationMode.NEAREST
. If input is Tensor, onlyInterpolationMode.NEAREST
,InterpolationMode.BILINEAR
are supported.fill (sequence or number, optional) – Pixel fill value for the area outside the transformed image. If given a number, the value is used for all bands respectively.
Examples using
AugMix
:Illustration of transforms- forward(*inputs: Any) Any [source]¶
Define the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.