diff --git a/python/paddle/vision/transforms/functional.py b/python/paddle/vision/transforms/functional.py index 1094e3fdb9572b6ad7f75af766ef6e0c340ac441..cde720e828383f35e34e2bfb3b9b045a1045cb64 100644 --- a/python/paddle/vision/transforms/functional.py +++ b/python/paddle/vision/transforms/functional.py @@ -104,7 +104,7 @@ def resize(img, size, interpolation='bilinear'): Resizes the image to given size Args: - input (PIL.Image|np.ndarray): Image to be resized. + input (PIL.Image|np.ndarray|paddle.Tensor): Image to be resized. size (int|list|tuple): Target size of input data, with (height, width) shape. interpolation (int|str, optional): Interpolation method. when use pil backend, support method are as following: @@ -122,7 +122,7 @@ def resize(img, size, interpolation='bilinear'): - "lanczos": cv2.INTER_LANCZOS4 Returns: - PIL.Image or np.array: Resized image. + PIL.Image|np.array|paddle.Tensor: Resized image. Examples: .. code-block:: python @@ -162,10 +162,10 @@ def resize(img, size, interpolation='bilinear'): def pad(img, padding, fill=0, padding_mode='constant'): """ - Pads the given PIL.Image or numpy.array on all sides with specified padding mode and fill value. + Pads the given PIL.Image or numpy.array or paddle.Tensor on all sides with specified padding mode and fill value. Args: - img (PIL.Image|np.array): Image to be padded. + img (PIL.Image|np.array|paddle.Tensor): Image to be padded. padding (int|list|tuple): Padding on each border. If a single int is provided this is used to pad all borders. If list/tuple of length 2 is provided this is the padding on left/right and top/bottom respectively. If a list/tuple of length 4 is provided @@ -191,7 +191,7 @@ def pad(img, padding, fill=0, padding_mode='constant'): will result in [2, 1, 1, 2, 3, 4, 4, 3] Returns: - PIL.Image or np.array: Padded image. + PIL.Image|np.array|paddle.Tensor: Padded image. Examples: .. code-block:: python @@ -231,7 +231,7 @@ def crop(img, top, left, height, width): """Crops the given Image. Args: - img (PIL.Image|np.array): Image to be cropped. (0,0) denotes the top left + img (PIL.Image|np.array|paddle.Tensor): Image to be cropped. (0,0) denotes the top left corner of the image. top (int): Vertical component of the top left corner of the crop box. left (int): Horizontal component of the top left corner of the crop box. @@ -239,7 +239,7 @@ def crop(img, top, left, height, width): width (int): Width of the crop box. Returns: - PIL.Image or np.array: Cropped image. + PIL.Image|np.array|paddle.Tensor: Cropped image. Examples: .. code-block:: python @@ -277,12 +277,12 @@ def center_crop(img, output_size): """Crops the given Image and resize it to desired size. Args: - img (PIL.Image|np.array): Image to be cropped. (0,0) denotes the top left corner of the image. + img (PIL.Image|np.array|paddle.Tensor): Image to be cropped. (0,0) denotes the top left corner of the image. output_size (sequence or int): (height, width) of the crop box. If int, it is used for both directions Returns: - PIL.Image or np.array: Cropped image. + PIL.Image|np.array|paddle.Tensor: Cropped image. Examples: .. code-block:: python @@ -316,13 +316,13 @@ def center_crop(img, output_size): def hflip(img): - """Horizontally flips the given Image or np.array. + """Horizontally flips the given Image or np.array or paddle.Tensor. Args: - img (PIL.Image|np.array): Image to be flipped. + img (PIL.Image|np.array|Tensor): Image to be flipped. Returns: - PIL.Image or np.array: Horizontall flipped image. + PIL.Image|np.array|paddle.Tensor: Horizontall flipped image. Examples: .. code-block:: python @@ -357,13 +357,13 @@ def hflip(img): def vflip(img): - """Vertically flips the given Image or np.array. + """Vertically flips the given Image or np.array or paddle.Tensor. Args: - img (PIL.Image|np.array): Image to be flipped. + img (PIL.Image|np.array|paddle.Tensor): Image to be flipped. Returns: - PIL.Image or np.array: Vertically flipped image. + PIL.Image|np.array|paddle.Tensor: Vertically flipped image. Examples: .. code-block:: python @@ -760,7 +760,7 @@ def rotate( Args: - img (PIL.Image|np.array): Image to be rotated. + img (PIL.Image|np.array|paddle.Tensor): Image to be rotated. angle (float or int): In degrees degrees counter clockwise order. interpolation (str, optional): Interpolation method. If omitted, or if the image has only one channel, it is set to PIL.Image.NEAREST or cv2.INTER_NEAREST @@ -784,7 +784,7 @@ def rotate( Returns: - PIL.Image or np.array: Rotated image. + PIL.Image|np.array|paddle.Tensor: Rotated image. Examples: .. code-block:: python @@ -934,11 +934,11 @@ def to_grayscale(img, num_output_channels=1): """Converts image to grayscale version of image. Args: - img (PIL.Image|np.array): Image to be converted to grayscale. + img (PIL.Image|np.array|paddle.Tensor): Image to be converted to grayscale. num_output_channels (int, optional): The number of channels for the output image. Single channel. Default: 1. Returns: - PIL.Image or np.array: Grayscale version of the image. + PIL.Image|np.array|paddle.Tensor: Grayscale version of the image. if num_output_channels = 1 : returned image is single channel if num_output_channels = 3 : returned image is 3 channel with r = g = b @@ -988,7 +988,7 @@ def normalize(img, mean, std, data_format='CHW', to_rgb=False): this option will be igored. Default: False. Returns: - np.ndarray or Tensor: Normalized mage. Data format is same as input img. + PIL.Image|np.array|paddle.Tensor: Normalized mage. Data format is same as input img. Examples: .. code-block:: python