Differences with torchvision.transforms.RandomAffine
torchvision.transforms.RandomAffine
class torchvision.transforms.RandomAffine(degrees, translate=None, scale=None, shear=None, interpolation=<InterpolationMode.NEAREST: 'nearest'>, fill=0, fillcolor=None, resample=None)
For more information, see torchvision.transforms.RandomAffine.
mindspore.dataset.vision.RandomAffine
class mindspore.dataset.vision.RandomAffine(degrees, translate=None, scale=None, shear=None, resample=Inter.NEAREST, fill_value=0)
For more information, see mindspore.dataset.vision.RandomAffine.
Differences
PyTorch: Apply random affine transformation to a tensor image. The rotation center position can be specified.
MindSpore: Apply random affine transformation to the input image. The rotation center is in the center of the image.
Categories |
Subcategories |
PyTorch |
MindSpore |
Difference |
---|---|---|---|---|
Parameter |
Parameter1 |
degrees |
degrees |
- |
Parameter2 |
translate |
translate |
- |
|
Parameter3 |
scale |
scale |
- |
|
Parameter4 |
shear |
shear |
- |
|
Parameter5 |
interpolation |
resample |
- |
|
Parameter6 |
fill |
fill_value |
- |
|
Parameter7 |
fillcolor |
- |
Deprecated in PyTorch, same with fill |
|
Parameter8 |
resample |
- |
Deprecated in PyTorch, same with interpolation |
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
affine_transfomer = T.RandomAffine(degrees=(30, 70), translate=(0.1, 0.3), fill=0)
img_torch = affine_transfomer(orig_img)
# MindSpore
import mindspore.dataset.vision as vision
import mindspore.dataset.transforms as transforms
affine_transfomer = vision.RandomAffine(degrees=(30, 70), translate=(0.1, 0.3), fill_value=0)
img_ms = affine_transfomer(orig_img)