perspective¶

paddle.vision.transforms. perspective ( img, startpoints, endpoints, interpolation='nearest', fill=0 ) [source]

Perform perspective transform of the given image.

Parameters

• img (PIL.Image|np.array|paddle.Tensor) – Image to be transformed.

• startpoints (list of list of ints) – List containing four lists of two integers corresponding to four corners [top-left, top-right, bottom-right, bottom-left] of the original image.

• endpoints (list of list of ints) – List containing four lists of two integers corresponding to four corners [top-left, top-right, bottom-right, bottom-left] of the transformed image.

• 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 according the backend. When use pil backend, support method are as following: - “nearest”: Image.NEAREST, - “bilinear”: Image.BILINEAR, - “bicubic”: Image.BICUBIC When use cv2 backend, support method are as following: - “nearest”: cv2.INTER_NEAREST, - “bilinear”: cv2.INTER_LINEAR, - “bicubic”: cv2.INTER_CUBIC

• fill (int|list|tuple, optional) – Pixel fill value for the area outside the transformed image. If given a number, the value is used for all bands respectively.

Returns

transformed Image.

Return type

PIL.Image|np.array|paddle.Tensor

Examples

>>> import paddle
>>> from paddle.vision.transforms import functional as F
>>> fake_img = paddle.randn((3, 256, 300)).astype(paddle.float32)
>>> startpoints = [[0, 0], [33, 0], [33, 25], [0, 25]]
>>> endpoints = [[3, 2], [32, 3], [30, 24], [2, 25]]
>>> perspectived_img = F.perspective(fake_img, startpoints, endpoints)
>>> print(perspectived_img.shape)
[3, 256, 300]