TrivialAugmentWide

class torchvision.transforms.TrivialAugmentWide(num_magnitude_bins: int = 31, interpolation: InterpolationMode = InterpolationMode.NEAREST, fill: Optional[list[float]] = None)

Dataset-independent data-augmentation with TrivialAugment Wide, as described in “TrivialAugment: Tuning-free Yet State-of-the-Art Data Augmentation”. If the image is torch Tensor, it should be of type torch.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:

• num_magnitude_bins (int) – The number of different magnitude values.

• interpolation (InterpolationMode) – Desired interpolation enum defined by torchvision.transforms.InterpolationMode. Default is InterpolationMode.NEAREST. If input is Tensor, only InterpolationMode.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 TrivialAugmentWide:

Illustration of transforms

Illustration of transforms

forward(img: Tensor) → Tensor

img (PIL Image or Tensor): Image to be transformed.

Returns:

Transformed image.

Return type:

PIL Image or Tensor