mindspore.dataset.vision.ResizeWithBBox

class mindspore.dataset.vision.ResizeWithBBox(size, interpolation=Inter.LINEAR)[source]

Resize the input image to the given size and adjust bounding boxes accordingly.

Parameters

  • size (Union[int, Sequence[int]]) – The output size of the resized image. If size is an integer, smaller edge of the image will be resized to this value with the same image aspect ratio. If size is a sequence of length 2, it should be (height, width).

  • interpolation (Inter, optional) –

    Image interpolation mode. Default: Inter.LINEAR. It can be any of [Inter.LINEAR, Inter.NEAREST, Inter.BICUBIC].

    • Inter.LINEAR, means interpolation method is bilinear interpolation.

    • Inter.NEAREST, means interpolation method is nearest-neighbor interpolation.

    • Inter.BICUBIC, means interpolation method is bicubic interpolation.

Raises

  • TypeError – If size is not of type int or Sequence[int].

  • TypeError – If interpolation is not of type Inter.

  • ValueError – If size is not positive.

  • RuntimeError – If given tensor shape is not <H, W> or <H, W, C>.

Supported Platforms:

CPU

Examples

>>> from mindspore.dataset.vision import Inter
>>> decode_op = vision.Decode()
>>> bbox_op = vision.ResizeWithBBox(50, Inter.NEAREST)
>>> transforms_list = [decode_op, bbox_op]
>>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list,
...                                                 input_columns=["image"])