mindspore.dataset.vision.py_transforms.RandomCrop
- class mindspore.dataset.vision.py_transforms.RandomCrop(size, padding=None, pad_if_needed=False, fill_value=0, padding_mode=Border.CONSTANT)[source]
Crop the input PIL Image at a random location with the specified size.
- Parameters
size (Union[int, sequence]) – The output size of the cropped image. If size is an integer, a square of size (size, size) is returned. If size is a sequence of length 2, it should be in shape of (height, width).
padding (Union[int, sequence], optional) – Padding on each border of the image (default=None). If padding is not None, pad the image before cropping. If a single number is provided, pad all borders with this value. If a sequence of length 2 is provided, pad the left/top border with the first value and right/bottom border with the second value. If a sequence of length 4 is provided, pad the left, top, right and bottom borders respectively.
pad_if_needed (bool, optional) – Pad the image if either side is smaller than the given output size (default=False).
fill_value (Union[int, tuple], optional) – Pixel fill value to pad the borders when padding_mode is Border.CONSTANT (default=0). If a tuple of length 3 is provided, it is used to fill R, G, B channels respectively.
padding_mode (Border, optional) –
The method of padding (default=Border.CONSTANT). It can be any of [Border.CONSTANT, Border.EDGE, Border.REFLECT, Border.SYMMETRIC].
Border.CONSTANT, means to pad with given constant values.
Border.EDGE, means to pad with the last value at the edge.
Border.REFLECT, means to pad with reflection of image omitting the last value at the edge.
Border.SYMMETRIC, means to pad with reflection of image repeating the last value at the edge.
- Raises
TypeError – If size is not of type integer or sequence of integer.
TypeError – If padding is not of type integer or sequence of integer.
TypeError – If pad_if_needed is not of type boolean.
TypeError – If fill_value is not of type integer or sequence of integer.
TypeError – If padding_mode is not of type Border.
ValueError – If size is not positive.
ValueError – If padding is negative.
ValueError – If fill_value is not in range [0, 255].
- Supported Platforms:
CPU
Examples
>>> from mindspore.dataset.transforms.py_transforms import Compose >>> transforms_list = Compose([py_vision.Decode(), ... py_vision.RandomCrop(224), ... py_vision.ToTensor()]) >>> # apply the transform to dataset through map function >>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list, ... input_columns="image")