mindspore.dataset.vision.RandomEqualize
- class mindspore.dataset.vision.RandomEqualize(prob=0.5)[source]
Apply histogram equalization on the input image with a given probability.
- Parameters
prob (float, optional) – Probability of the image being equalized, which must be in range of [0.0, 1.0]. Default:
0.5
.- Raises
TypeError – If prob is not of type float.
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.RandomEqualize(0.5)] >>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list, ... input_columns=["image"])
- Tutorial Examples: