Skip to content

Minor docs improvement #2403

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Jul 8, 2020
Merged

Minor docs improvement #2403

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
d9bfb50
Minor docs improvement
vfdev-5 Jul 8, 2020
7bbf0c1
Replaced link by already defined `filters`_
vfdev-5 Jul 8, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 7 additions & 3 deletions torchvision/transforms/functional.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -311,7 +311,7 @@ def normalize(tensor, mean, std, inplace=False):
return tensor


def resize(img: Tensor, size: List[int], interpolation: int = 2) -> Tensor:
def resize(img: Tensor, size: List[int], interpolation: int = Image.BILINEAR) -> Tensor:
r"""Resize the input image to the given size.
The image can be a PIL Image or a torch Tensor, in which case it is expected
to have [..., H, W] shape, where ... means an arbitrary number of leading dimensions
Expand All @@ -325,7 +325,9 @@ def resize(img: Tensor, size: List[int], interpolation: int = 2) -> Tensor:
:math:`\left(\text{size} \times \frac{\text{height}}{\text{width}}, \text{size}\right)`.
In torchscript mode padding as single int is not supported, use a tuple or
list of length 1: ``[size, ]``.
interpolation (int, optional): Desired interpolation. Default is bilinear.
interpolation (int, optional): Desired interpolation enum defined by `filters`_.
Default is ``PIL.Image.BILINEAR``. If input is Tensor, only ``PIL.Image.NEAREST``, ``PIL.Image.BILINEAR``
and ``PIL.Image.BICUBIC`` are supported.

Returns:
PIL Image or Tensor: Resized image.
Expand Down Expand Up @@ -455,7 +457,9 @@ def resized_crop(
height (int): Height of the crop box.
width (int): Width of the crop box.
size (sequence or int): Desired output size. Same semantics as ``resize``.
interpolation (int, optional): Desired interpolation. Default is ``PIL.Image.BILINEAR``.
interpolation (int, optional): Desired interpolation enum defined by `filters`_.
Default is ``PIL.Image.BILINEAR``. If input is Tensor, only ``PIL.Image.NEAREST``, ``PIL.Image.BILINEAR``
and ``PIL.Image.BICUBIC`` are supported.
Returns:
PIL Image or Tensor: Cropped image.
"""
Expand Down
8 changes: 6 additions & 2 deletions torchvision/transforms/transforms.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -222,7 +222,9 @@ class Resize(torch.nn.Module):
(size * height / width, size).
In torchscript mode padding as single int is not supported, use a tuple or
list of length 1: ``[size, ]``.
interpolation (int, optional): Desired interpolation. Default is ``PIL.Image.BILINEAR``
interpolation (int, optional): Desired interpolation enum defined by `filters`_.
Default is ``PIL.Image.BILINEAR``. If input is Tensor, only ``PIL.Image.NEAREST``, ``PIL.Image.BILINEAR``
and ``PIL.Image.BICUBIC`` are supported.
"""

def __init__(self, size, interpolation=Image.BILINEAR):
Expand Down Expand Up @@ -703,7 +705,9 @@ class RandomResizedCrop(torch.nn.Module):
made. If provided a tuple or list of length 1, it will be interpreted as (size[0], size[0]).
scale (tuple of float): range of size of the origin size cropped
ratio (tuple of float): range of aspect ratio of the origin aspect ratio cropped.
interpolation (int): Desired interpolation. Default: ``PIL.Image.BILINEAR``
interpolation (int): Desired interpolation enum defined by `filters`_.
Default is ``PIL.Image.BILINEAR``. If input is Tensor, only ``PIL.Image.NEAREST``, ``PIL.Image.BILINEAR``
and ``PIL.Image.BICUBIC`` are supported.
"""

def __init__(self, size, scale=(0.08, 1.0), ratio=(3. / 4., 4. / 3.), interpolation=Image.BILINEAR):
Expand Down