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Unverified Commit 38aab83a authored by vfdev's avatar vfdev Committed by GitHub
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Added warning to the documentation of F_pil and F_t functions (2547) (#2664) 

* Fixes #2547

- Added warning to the documentation of F_pil and F_t functions

* Update functional_tensor.py
parent 55477476
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Showing with 192 additions and 29 deletions
torchvision/transforms/functional_pil.py
View file @ 38aab83a
......@@ -35,7 +35,12 @@ def _get_image_num_channels(img: Any) -> int:
@torch.jit.unused
def hflip(img):
"""Horizontally flip the given PIL Image.
"""PRIVATE METHOD. Horizontally flip the given PIL Image.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): Image to be flipped.
......@@ -51,7 +56,12 @@ def hflip(img):
@torch.jit.unused
def vflip(img):
"""Vertically flip the given PIL Image.
"""PRIVATE METHOD. Vertically flip the given PIL Image.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): Image to be flipped.
......@@ -67,7 +77,12 @@ def vflip(img):
@torch.jit.unused
def adjust_brightness(img, brightness_factor):
"""Adjust brightness of an RGB image.
"""PRIVATE METHOD. Adjust brightness of an RGB image.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): Image to be adjusted.
......@@ -88,7 +103,13 @@ def adjust_brightness(img, brightness_factor):
@torch.jit.unused
def adjust_contrast(img, contrast_factor):
"""Adjust contrast of an Image.
"""PRIVATE METHOD. Adjust contrast of an Image.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): PIL Image to be adjusted.
contrast_factor (float): How much to adjust the contrast. Can be any
......@@ -107,7 +128,13 @@ def adjust_contrast(img, contrast_factor):
@torch.jit.unused
def adjust_saturation(img, saturation_factor):
"""Adjust color saturation of an image.
"""PRIVATE METHOD. Adjust color saturation of an image.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): PIL Image to be adjusted.
saturation_factor (float): How much to adjust the saturation. 0 will
......@@ -126,7 +153,12 @@ def adjust_saturation(img, saturation_factor):
@torch.jit.unused
def adjust_hue(img, hue_factor):
"""Adjust hue of an image.
"""PRIVATE METHOD. Adjust hue of an image.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
The image hue is adjusted by converting the image to HSV and
cyclically shifting the intensities in the hue channel (H).
......@@ -174,7 +206,12 @@ def adjust_hue(img, hue_factor):
@torch.jit.unused
def adjust_gamma(img, gamma, gain=1):
r"""Perform gamma correction on an image.
r"""PRIVATE METHOD. Perform gamma correction on an image.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Also known as Power Law Transform. Intensities in RGB mode are adjusted
based on the following equation:
......@@ -210,7 +247,12 @@ def adjust_gamma(img, gamma, gain=1):
@torch.jit.unused
def pad(img, padding, fill=0, padding_mode="constant"):
r"""Pad the given PIL.Image on all sides with the given "pad" value.
r"""PRIVATE METHOD. Pad the given PIL.Image on all sides with the given "pad" value.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): Image to be padded.
......@@ -309,7 +351,12 @@ def pad(img, padding, fill=0, padding_mode="constant"):
@torch.jit.unused
def crop(img: Image.Image, top: int, left: int, height: int, width: int) -> Image.Image:
"""Crop the given PIL Image.
"""PRIVATE METHOD. Crop the given PIL Image.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): Image to be cropped. (0,0) denotes the top left corner of the image.
......@@ -329,7 +376,12 @@ def crop(img: Image.Image, top: int, left: int, height: int, width: int) -> Imag
@torch.jit.unused
def resize(img, size, interpolation=Image.BILINEAR):
r"""Resize the input PIL Image to the given size.
r"""PRIVATE METHOD. Resize the input PIL Image to the given size.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): Image to be resized.
......@@ -370,7 +422,12 @@ def resize(img, size, interpolation=Image.BILINEAR):
@torch.jit.unused
def _parse_fill(fill, img, min_pil_version, name="fillcolor"):
"""Helper function to get the fill color for rotate, perspective transforms, and pad.
"""PRIVATE METHOD. Helper function to get the fill color for rotate, perspective transforms, and pad.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
fill (n-tuple or int or float): Pixel fill value for area outside the transformed
......@@ -409,7 +466,12 @@ def _parse_fill(fill, img, min_pil_version, name="fillcolor"):
@torch.jit.unused
def affine(img, matrix, resample=0, fillcolor=None):
"""Apply affine transformation on the PIL Image keeping image center invariant.
"""PRIVATE METHOD. Apply affine transformation on the PIL Image keeping image center invariant.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): image to be rotated.
......@@ -433,7 +495,12 @@ def affine(img, matrix, resample=0, fillcolor=None):
@torch.jit.unused
def rotate(img, angle, resample=0, expand=False, center=None, fill=None):
"""Rotate PIL image by angle.
"""PRIVATE METHOD. Rotate PIL image by angle.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): image to be rotated.
......@@ -467,7 +534,12 @@ def rotate(img, angle, resample=0, expand=False, center=None, fill=None):
@torch.jit.unused
def perspective(img, perspective_coeffs, interpolation=Image.BICUBIC, fill=None):
"""Perform perspective transform of the given PIL Image.
"""PRIVATE METHOD. Perform perspective transform of the given PIL Image.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): Image to be transformed.
......@@ -491,7 +563,12 @@ def perspective(img, perspective_coeffs, interpolation=Image.BICUBIC, fill=None)
@torch.jit.unused
def to_grayscale(img, num_output_channels):
"""Convert PIL image of any mode (RGB, HSV, LAB, etc) to grayscale version of image.
"""PRIVATE METHOD. Convert PIL image of any mode (RGB, HSV, LAB, etc) to grayscale version of image.
.. warning::
Module ``transforms.functional_pil`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (PIL Image): Image to be converted to grayscale.
......
torchvision/transforms/functional_tensor.py
View file @ 38aab83a
......@@ -28,7 +28,12 @@ def _get_image_num_channels(img: Tensor) -> int:
def vflip(img: Tensor) -> Tensor:
"""Vertically flip the given the Image Tensor.
"""PRIVATE METHOD. Vertically flip the given the Image Tensor.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (Tensor): Image Tensor to be flipped in the form [C, H, W].
......@@ -43,7 +48,12 @@ def vflip(img: Tensor) -> Tensor:
def hflip(img: Tensor) -> Tensor:
"""Horizontally flip the given the Image Tensor.
"""PRIVATE METHOD. Horizontally flip the given the Image Tensor.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (Tensor): Image Tensor to be flipped in the form [C, H, W].
......@@ -58,7 +68,12 @@ def hflip(img: Tensor) -> Tensor:
def crop(img: Tensor, top: int, left: int, height: int, width: int) -> Tensor:
"""Crop the given Image Tensor.
"""PRIVATE METHOD. Crop the given Image Tensor.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (Tensor): Image to be cropped in the form [..., H, W]. (0,0) denotes the top left corner of the image.
......@@ -77,7 +92,13 @@ def crop(img: Tensor, top: int, left: int, height: int, width: int) -> Tensor:
def rgb_to_grayscale(img: Tensor, num_output_channels: int = 1) -> Tensor:
"""Convert the given RGB Image Tensor to Grayscale.
"""PRIVATE METHOD. Convert the given RGB Image Tensor to Grayscale.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
For RGB to Grayscale conversion, ITU-R 601-2 luma transform is performed which
is L = R * 0.2989 + G * 0.5870 + B * 0.1140
......@@ -114,7 +135,12 @@ def rgb_to_grayscale(img: Tensor, num_output_channels: int = 1) -> Tensor:
def adjust_brightness(img: Tensor, brightness_factor: float) -> Tensor:
"""Adjust brightness of an RGB image.
"""PRIVATE METHOD. Adjust brightness of an RGB image.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (Tensor): Image to be adjusted.
......@@ -135,7 +161,12 @@ def adjust_brightness(img: Tensor, brightness_factor: float) -> Tensor:
def adjust_contrast(img: Tensor, contrast_factor: float) -> Tensor:
"""Adjust contrast of an RGB image.
"""PRIVATE METHOD. Adjust contrast of an RGB image.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (Tensor): Image to be adjusted.
......@@ -158,7 +189,12 @@ def adjust_contrast(img: Tensor, contrast_factor: float) -> Tensor:
def adjust_hue(img: Tensor, hue_factor: float) -> Tensor:
"""Adjust hue of an image.
"""PRIVATE METHOD. Adjust hue of an image.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
The image hue is adjusted by converting the image to HSV and
cyclically shifting the intensities in the hue channel (H).
......@@ -205,7 +241,12 @@ def adjust_hue(img: Tensor, hue_factor: float) -> Tensor:
def adjust_saturation(img: Tensor, saturation_factor: float) -> Tensor:
"""Adjust color saturation of an RGB image.
"""PRIVATE METHOD. Adjust color saturation of an RGB image.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (Tensor): Image to be adjusted.
......@@ -226,7 +267,12 @@ def adjust_saturation(img: Tensor, saturation_factor: float) -> Tensor:
def adjust_gamma(img: Tensor, gamma: float, gain: float = 1) -> Tensor:
r"""Adjust gamma of an RGB image.
r"""PRIVATE METHOD. Adjust gamma of an RGB image.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Also known as Power Law Transform. Intensities in RGB mode are adjusted
based on the following equation:
......@@ -269,6 +315,11 @@ def adjust_gamma(img: Tensor, gamma: float, gain: float = 1) -> Tensor:
def center_crop(img: Tensor, output_size: BroadcastingList2[int]) -> Tensor:
"""DEPRECATED. Crop the Image Tensor and resize it to desired size.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
.. warning::
This method is deprecated and will be removed in future releases.
......@@ -307,6 +358,11 @@ def center_crop(img: Tensor, output_size: BroadcastingList2[int]) -> Tensor:
def five_crop(img: Tensor, size: BroadcastingList2[int]) -> List[Tensor]:
"""DEPRECATED. Crop the given Image Tensor into four corners and the central crop.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
.. warning::
This method is deprecated and will be removed in future releases.
......@@ -356,6 +412,11 @@ def ten_crop(img: Tensor, size: BroadcastingList2[int], vertical_flip: bool = Fa
"""DEPRECATED. Crop the given Image Tensor into four corners and the central crop plus the
flipped version of these (horizontal flipping is used by default).
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
.. warning::
This method is deprecated and will be removed in future releases.
......@@ -488,7 +549,12 @@ def _pad_symmetric(img: Tensor, padding: List[int]) -> Tensor:
def pad(img: Tensor, padding: List[int], fill: int = 0, padding_mode: str = "constant") -> Tensor:
r"""Pad the given Tensor Image on all sides with specified padding mode and fill value.
r"""PRIVATE METHOD. Pad the given Tensor Image on all sides with specified padding mode and fill value.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (Tensor): Image to be padded.
......@@ -593,7 +659,12 @@ def pad(img: Tensor, padding: List[int], fill: int = 0, padding_mode: str = "con
def resize(img: Tensor, size: List[int], interpolation: int = 2) -> Tensor:
r"""Resize the input Tensor to the given size.
r"""PRIVATE METHOD. Resize the input Tensor to the given size.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (Tensor): Image to be resized.
......@@ -757,7 +828,12 @@ def _gen_affine_grid(
def affine(
img: Tensor, matrix: List[float], resample: int = 0, fillcolor: Optional[int] = None
) -> Tensor:
"""Apply affine transformation on the Tensor image keeping image center invariant.
"""PRIVATE METHOD. Apply affine transformation on the Tensor image keeping image center invariant.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (Tensor): image to be rotated.
......@@ -814,7 +890,12 @@ def _compute_output_size(matrix: List[float], w: int, h: int) -> Tuple[int, int]
def rotate(
img: Tensor, matrix: List[float], resample: int = 0, expand: bool = False, fill: Optional[int] = None
) -> Tensor:
"""Rotate the Tensor image by angle.
"""PRIVATE METHOD. Rotate the Tensor image by angle.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (Tensor): image to be rotated.
......@@ -886,7 +967,12 @@ def _perspective_grid(coeffs: List[float], ow: int, oh: int, dtype: torch.dtype,
def perspective(
img: Tensor, perspective_coeffs: List[float], interpolation: int = 2, fill: Optional[int] = None
) -> Tensor:
"""Perform perspective transform of the given Tensor image.
"""PRIVATE METHOD. Perform perspective transform of the given Tensor image.
.. warning::
Module ``transforms.functional_tensor`` is private and should not be used in user application.
Please, consider instead using methods from `transforms.functional` module.
Args:
img (Tensor): Image to be transformed.
......
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