mindspore.dataset.vision.AdjustGamma

class mindspore.dataset.vision.AdjustGamma(gamma, gain=1)

Apply gamma correction on input image. Input image is expected to be in […, H, W, C] or [H, W] format.

\[I_{\text{out}} = 255 \times \text{gain} \times \left(\frac{I_{\text{in}}}{255}\right)^{\gamma}\]

See Gamma Correction for more details.

Parameters

• gamma (float) – Non negative real number. The output image pixel value is exponentially related to the input image pixel value. gamma larger than 1 make the shadows darker, while gamma smaller than 1 make dark regions lighter.

• gain (float, optional) – The constant multiplier (default=1).

Raises

• TypeError – If gain is not of type float.

• TypeError – If gamma is not of type float.

• ValueError – If gamma is less than 0.

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

Supported Platforms:

CPU

Examples

>>> transforms_list = [vision.Decode(), vision.AdjustGamma(gamma=10.0, gain=1.0)]
>>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list,
...                                                 input_columns=["image"])

execute_py(img)

Execute method.

Parameters

img (PIL Image) – Image to be gamma adjusted.

Returns

PIL Image, gamma adjusted image.