mindspore.dataset.vision.c_transforms.NormalizePad

class mindspore.dataset.vision.c_transforms.NormalizePad(mean, std, dtype='float32')[source]

Normalize the input image with respect to mean and standard deviation then pad an extra channel with value zero.

Parameters

mean (sequence) – List or tuple of mean values for each channel, with respect to channel order. The mean values must be in range (0.0, 255.0].
std (sequence) – List or tuple of standard deviations for each channel, with respect to channel order. The standard deviation values must be in range (0.0, 255.0].
dtype (str) – Set the output data type of normalized image (default is “float32”).

Examples

>>> decode_op = c_vision.Decode()
>>> normalize_pad_op = c_vision.NormalizePad(mean=[121.0, 115.0, 100.0],
...                                          std=[70.0, 68.0, 71.0],
...                                          dtype="float32")
>>> transforms_list = [decode_op, normalize_pad_op]
>>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list,
...                                                 input_columns=["image"])