Differences with torchvision.transforms.RandomResizedCrop

torchvision.transforms.RandomResizedCrop

class torchvision.transforms.RandomResizedCrop(size, scale=(0.08, 1.0), ratio=(0.75, 1.3333333333333333), interpolation=InterpolationMode.BILINEAR)

For more information, see torchvision.transforms.RandomResizedCrop.

mindspore.dataset.vision.RandomResizedCrop

class mindspore.dataset.vision.RandomResizedCrop(size, scale=(0.08, 1.0), ratio=(3. / 4., 4. / 3.), interpolation=Inter.BILINEAR, max_attempts=10)

For more information, see mindspore.dataset.vision.RandomResizedCrop.

Differences

PyTorch: Crop a random portion of image and resize it to a given size.

MindSpore: Crop a random portion of image and resize it to a given size.

Categories	Subcategories	PyTorch	MindSpore	Difference
Parameter	Parameter1	size	size	-
	Parameter2	scale	scale	-
	Parameter3	ratio	ratio	-
	Parameter4	interpolation	interpolation	-
	Parameter5	-	max_attempts	The maximum number of attempts to propose a valid crop_area

Code Example

from download import download
from PIL import Image

url = "https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/notebook/datasets/flamingos.jpg"
download(url, './flamingos.jpg', replace=True)
orig_img = Image.open('flamingos.jpg')

# PyTorch
import torchvision.transforms as T

op = T.RandomResizedCrop((32, 32), scale=(0.08, 1.0), ratio=(0.75, 0.8))
img_torch =op(orig_img)
print(img_torch.size)
# Out: (32, 32)

# MindSpore
import mindspore.dataset.vision as vision

op = vision.RandomResizedCrop((32, 32), scale=(0.08, 1.0), ratio=(0.75, 0.8))
img_ms = op(orig_img)
print(img_ms.size)
# Out: (32, 32)