mindspore.dataset.vision.Normalize
- class mindspore.dataset.vision.Normalize(mean, std, is_hwc=True)[source]
Normalize the input image with respect to mean and standard deviation. This operation will normalize the input image with: output[channel] = (input[channel] - mean[channel]) / std[channel], where channel >= 1.
Note
This operation is executed on the CPU by default, but it is also supported to be executed on the GPU or Ascend via heterogeneous acceleration.
- 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].
is_hwc (bool, optional) – Whether the input image is HWC.
True
- HWC format,False
- CHW format. Default:True
.
- Raises
TypeError – If mean is not of type sequence.
TypeError – If std is not of type sequence.
TypeError – If is_hwc is not of type bool.
ValueError – If mean is not in range [0.0, 255.0].
ValueError – If std is not in range (0.0, 255.0].
RuntimeError – If given tensor format is not <H, W> or <…, H, W, C>.
- Supported Platforms:
CPU
GPU
Ascend
Examples
>>> import mindspore.dataset as ds >>> import mindspore.dataset.vision as vision >>> >>> image_folder_dataset = ds.ImageFolderDataset("/path/to/image_folder_dataset_directory") >>> decode_op = vision.Decode() ## Decode output is expected to be HWC format >>> normalize_op = vision.Normalize(mean=[121.0, 115.0, 100.0], std=[70.0, 68.0, 71.0], is_hwc=True) >>> transforms_list = [decode_op, normalize_op] >>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list, ... input_columns=["image"])
- Tutorial Examples:
- 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 >>> from mindspore.dataset.vision import Inter >>> >>> decode_op = vision.Decode() >>> resize_op = vision.Resize([100, 75], Inter.BICUBIC) >>> transforms_list = [decode_op, resize_op] >>> image_folder_dataset = ds.ImageFolderDataset("/path/to/image_folder_dataset_directory") >>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list, ... input_columns=["image"]) >>> normalize_op = vision.Normalize(mean=[121.0, 115.0, 100.0], std=[70.0, 68.0, 71.0]).device("Ascend") >>> image_folder_dataset = image_folder_dataset.map(operations=normalize_op, input_columns=["image"])
- Tutorial Examples: