mindspore.dataset.vision.py_transforms.Pad
- class mindspore.dataset.vision.py_transforms.Pad(padding, fill_value=0, padding_mode=Border.CONSTANT)[source]
Pad the input PIL image according to padding parameters.
- Parameters
padding (Union[int, sequence]) – The number of pixels to pad the image. If a single number is provided, pad all borders with this value. If a tuple or list of 2 values is provided, pad the left and top with the first value and the right and bottom with the second value. If 4 values are provided as a list or tuple, pad the left, top, right and bottom respectively.
fill_value (Union[int, tuple], optional) – The pixel intensity of the borders, only valid for padding_mode Border.CONSTANT (default=0). If it is an integer, it is used for all RGB channels. If it is a 3-tuple, it is used to fill R, G, B channels respectively.
padding_mode (Border mode, optional) –
The method of padding (default=Border.CONSTANT). It can be any of [Border.CONSTANT, Border.EDGE, Border.REFLECT, Border.SYMMETRIC].
Border.CONSTANT, means it fills the border with constant values.
Border.EDGE, means it pads with the last value on the edge.
Border.REFLECT, means it reflects the values on the edge omitting the last value of edge.
Border.SYMMETRIC, means it reflects the values on the edge repeating the last value of edge.
Examples
>>> import mindspore.dataset.vision.py_transforms as py_vision >>> from mindspore.dataset.transforms.py_transforms import Compose >>> >>> Compose([py_vision.Decode(), >>> # adds 10 pixels (default black) to each side of the border of the image >>> py_vision.Pad(padding=10), >>> py_vision.ToTensor()])