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fix format
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@LielinJiang
LielinJiang committed Aug 31, 2021
1 parent 53099c8 commit 34285ee
Showing 1 changed file with 51 additions and 51 deletions.
102 changes: 51 additions & 51 deletions python/paddle/vision/transforms/transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -310,9 +310,9 @@ class ToTensor(BaseTransform):
'CHW'. Default: 'CHW'.
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray): The input image with shape (H x W x C).
- output (np.ndarray): A tensor with shape (C x H x W) or (H x W x C) according option data_format.
Shape:
- img(PIL.Image|np.ndarray): The input image with shape (H x W x C).
- output(np.ndarray): A tensor with shape (C x H x W) or (H x W x C) according option data_format.
Returns:
A callable object of ToTensor.
Expand Down Expand Up @@ -375,9 +375,9 @@ class Resize(BaseTransform):
- "lanczos": cv2.INTER_LANCZOS4
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): A resized image.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): A resized image.
Returns:
A callable object of Resize.
Expand Down Expand Up @@ -436,9 +436,9 @@ class RandomResizedCrop(BaseTransform):
- "lanczos": cv2.INTER_LANCZOS4
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): A cropped image.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): A cropped image.
Returns:
A callable object of RandomResizedCrop.
Expand Down Expand Up @@ -524,9 +524,9 @@ class CenterCrop(BaseTransform):
size (int|list|tuple): Target size of output image, with (height, width) shape.
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): A cropped image.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): A cropped image.
Returns:
A callable object of CenterCrop.
Expand Down Expand Up @@ -565,9 +565,9 @@ class RandomHorizontalFlip(BaseTransform):
prob (float, optional): Probability of the input data being flipped. Should be in [0, 1]. Default: 0.5
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): A horiziotal flipped image.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): A horiziotal flipped image.
Returns:
A callable object of RandomHorizontalFlip.
Expand Down Expand Up @@ -606,9 +606,9 @@ class RandomVerticalFlip(BaseTransform):
prob (float, optional): Probability of the input data being flipped. Default: 0.5
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): A vertical flipped image.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): A vertical flipped image.
Returns:
A callable object of RandomVerticalFlip.
Expand Down Expand Up @@ -655,9 +655,9 @@ class Normalize(BaseTransform):
to_rgb (bool, optional): Whether to convert to rgb. Default: False.
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): A normalized array or tensor.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): A normalized array or tensor.
Returns:
A callable object of Normalize.
Expand Down Expand Up @@ -715,9 +715,9 @@ class Transpose(BaseTransform):
order (list|tuple, optional): Target order of input data. Default: (2, 0, 1).
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (np.ndarray|Paddle.Tensor): A transposed array or tensor. If input
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(np.ndarray|Paddle.Tensor): A transposed array or tensor. If input
is a PIL.Image, output will be converted to np.ndarray automatically.
Returns:
Expand Down Expand Up @@ -764,9 +764,9 @@ class BrightnessTransform(BaseTransform):
non negative number. 0 gives the original image
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): An image with a transform in brghtness.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): An image with a transform in brghtness.
Returns:
A callable object of BrightnessTransform.
Expand Down Expand Up @@ -807,9 +807,9 @@ class ContrastTransform(BaseTransform):
non negative number. 0 gives the original image
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): An image with a transform in contrast.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): An image with a transform in contrast.
Returns:
A callable object of ContrastTransform.
Expand Down Expand Up @@ -852,9 +852,9 @@ class SaturationTransform(BaseTransform):
non negative number. 0 gives the original image
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): An image with a transform in saturation.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): An image with a transform in saturation.
Returns:
A callable object of SaturationTransform.
Expand Down Expand Up @@ -895,9 +895,9 @@ class HueTransform(BaseTransform):
between 0 and 0.5, 0 gives the original image
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): An image with a transform in hue.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): An image with a transform in hue.
Returns:
A callable object of HueTransform.
Expand Down Expand Up @@ -945,9 +945,9 @@ class ColorJitter(BaseTransform):
Chosen uniformly from [-hue, hue]. Should have 0<= hue <= 0.5.
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): A color jittered image.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): A color jittered image.
Returns:
A callable object of ColorJitter.
Expand Down Expand Up @@ -1031,9 +1031,9 @@ class RandomCrop(BaseTransform):
desired size to avoid raising an exception. Default: False.
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): A random cropped image.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): A random cropped image.
Returns:
A callable object of RandomCrop.
Expand Down Expand Up @@ -1140,9 +1140,9 @@ class Pad(BaseTransform):
will result in ``[2, 1, 1, 2, 3, 4, 4, 3]``.
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): A paded image.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): A paded image.
Returns:
A callable object of Pad.
Expand Down Expand Up @@ -1220,9 +1220,9 @@ class RandomRotation(BaseTransform):
Default is the center of the image.
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): A rotated image.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): A rotated image.
Returns:
A callable object of RandomRotation.
Expand Down Expand Up @@ -1294,9 +1294,9 @@ class Grayscale(BaseTransform):
num_output_channels (int): (1 or 3) number of channels desired for output image
keys (list[str]|tuple[str], optional): Same as ``BaseTransform``. Default: None.
Shapes:
- img (PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output (PIL.Image|np.ndarray|Paddle.Tensor): Grayscale version of the input image.
Shape:
- img(PIL.Image|np.ndarray|Paddle.Tensor): The input image with shape (H x W x C).
- output(PIL.Image|np.ndarray|Paddle.Tensor): Grayscale version of the input image.
- If output_channels == 1 : returned image is single channel
- If output_channels == 3 : returned image is 3 channel with r == g == b
Expand Down

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