mindspore.dataset.vision.ToNumpy
- class mindspore.dataset.vision.ToNumpy[source]
Convert the PIL input image to numpy.ndarray image.
- Supported Platforms:
CPU
Examples
>>> import numpy as np >>> import mindspore.dataset as ds >>> import mindspore.dataset.vision as vision >>> from mindspore.dataset.transforms import Compose >>> >>> # Use the transform in dataset pipeline mode >>> data = np.random.randint(0, 255, size=(1, 100, 100, 3)).astype(np.uint8) >>> numpy_slices_dataset = ds.NumpySlicesDataset(data, ["image"]) >>> # Use ToNumpy to explicitly select C++ implementation of subsequent op >>> transforms_list = Compose([vision.RandomHorizontalFlip(0.5), ... vision.ToNumpy(), ... vision.Resize((50, 60))]) >>> # apply the transform to dataset through map function >>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms_list, input_columns="image") >>> for item in numpy_slices_dataset.create_dict_iterator(num_epochs=1, output_numpy=True): ... print(item["image"].shape, item["image"].dtype) ... break (50, 60, 3) uint8 >>> >>> # Use the transform in eager mode >>> data = list(np.random.randint(0, 255, size=(32, 32, 3, 3)).astype(np.int32)) >>> output = vision.ToNumpy()(data) >>> print(type(output), output.shape, output.dtype) <class 'numpy.ndarray'> (32, 32, 3, 3) int32
- Tutorial Examples: