mindspore.dataset.vision.RandomAdjustSharpness

class mindspore.dataset.vision.RandomAdjustSharpness(degree, prob=0.5)[source]

Randomly adjust the sharpness of the input image with a given probability.

Parameters

degree (float) – Sharpness adjustment degree, which must be non negative. Degree of 0.0 gives a blurred image, degree of 1.0 gives the original image, and degree of 2.0 increases the sharpness by a factor of 2.
prob (float, optional) – Probability of the image being sharpness adjusted, which must be in range of [0.0, 1.0]. Default: 0.5.

Raises

TypeError – If degree is not of type float.
TypeError – If prob is not of type float.
ValueError – If degree is negative.
ValueError – If prob is not in range [0.0, 1.0].
RuntimeError – If given tensor shape is not <H, W> or <H, W, C>.

Supported Platforms:: CPU

Examples

>>> import mindspore.dataset as ds
>>> import mindspore.dataset.vision as vision
>>>
>>> image_folder_dataset = ds.ImageFolderDataset("/path/to/image_folder_dataset_directory")
>>> transforms_list = [vision.Decode(), vision.RandomAdjustSharpness(2.0, 0.5)]
>>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list,
...                                                 input_columns=["image"])

Tutorial Examples:

Illustration of vision transforms