mindspore.dataset.vision.py_transforms.ToTensor
- class mindspore.dataset.vision.py_transforms.ToTensor(output_type=np.float32)[source]
Convert the input PIL Image or numpy.ndarray of shape (H, W, C) in the range [0, 255] to numpy.ndarray of shape (C, H, W) in the range [0.0, 1.0] with the desired dtype.
Note
The values in the input image will be rescaled from [0, 255] to [0.0, 1.0]. The dtype will be cast to output_type. The number of channels remains the same.
- Parameters
output_type (numpy.dtype, optional) – The dtype of the numpy.ndarray output (default=np.float32).
- Raises
- Supported Platforms:
CPU
Examples
>>> from mindspore.dataset.transforms.py_transforms import Compose >>> # create a list of transformations to be applied to the "image" column of each data row >>> transforms_list = Compose([py_vision.Decode(), ... py_vision.RandomHorizontalFlip(0.5), ... py_vision.ToTensor()]) >>> # apply the transform to dataset through map function >>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list, ... input_columns="image")