mindspore.dataset.vision.c_transforms.GaussianBlur

class mindspore.dataset.vision.c_transforms.GaussianBlur(kernel_size, sigma=None)[source]

Blur input image with the specified Gaussian kernel.

Parameters

kernel_size (Union[int, Sequence[int]]) – Size of the Gaussian kernel to use. The value must be positive and odd. if only an integer is provided, the kernel size will be (kernel_size, kernel_size). If a sequence of integer is provided, it must be a sequence of 2 values which represents (width, height).
sigma (Union[float, Sequence[float]], optional) – Standard deviation of the Gaussian kernel to use (default=None). The value must be positive. If only a float is provided, the sigma will be (sigma, sigma). If a sequence of float is provided, it must be a sequence of 2 values which represents (width, height). If None is provided, the sigma will be calculated as ((kernel_size - 1) * 0.5 - 1) * 0.3 + 0.8.

Raises

TypeError – If kernel_size is not of type int or Sequence[int].
TypeError – If sigma is not of type float or Sequence[float].
ValueError – If kernel_size is not positive and odd.
ValueError – If sigma is not positive.
RuntimeError – If given tensor shape is not <H, W> or <H, W, C>.

Supported Platforms:: CPU

Examples

>>> transforms_list = [c_vision.Decode(), c_vision.GaussianBlur(3, 3)]
>>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list,
...                                                 input_columns=["image"])