mindspore.dataset.vision.AdjustBrightness

class mindspore.dataset.vision.AdjustBrightness(brightness_factor)[source]

Adjust the brightness of the input image.

Parameters

brightness_factor (float) – How much to adjust the brightness, must be non negative. 0 gives a black image, 1 gives the original image, while 2 increases the brightness by a factor of 2.

Raises

TypeError – If brightness_factor is not of type float.
ValueError – If brightness_factor is less than 0.
RuntimeError – If shape of the input image is not <H, W, C>.

Supported Platforms:: CPU Ascend

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.AdjustBrightness(brightness_factor=2.0)]
>>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list,
...                                                 input_columns=["image"])

Tutorial Examples:

Illustration of vision transforms

device(device_target='CPU')[source]

Set the device for the current operator execution.

Parameters

device_target (str, optional) – The operator will be executed on this device. Currently supports CPU . Default: CPU .

Raises

TypeError – If device_target is not of type str.
ValueError – If device_target is not CPU .

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().device("CPU"), vision.AdjustBrightness(2.0).device("Ascend")]
>>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list, input_columns=["image"])

Tutorial Examples:

Illustration of vision transforms