perspective¶
- torchvision.transforms.functional.perspective(img: Tensor, startpoints: List[List[int]], endpoints: List[List[int]], interpolation: InterpolationMode = InterpolationMode.BILINEAR, fill: Optional[List[float]] = None) Tensor [source]¶
Perform perspective transform of the given image. If the image is torch Tensor, it is expected to have […, H, W] shape, where … means an arbitrary number of leading dimensions.
- Parameters:
img (PIL Image or Tensor) – Image to be transformed.
startpoints (list of list of python: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 python: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 (InterpolationMode) – Desired interpolation enum defined by
torchvision.transforms.InterpolationMode
. Default isInterpolationMode.BILINEAR
. If input is Tensor, onlyInterpolationMode.NEAREST
,InterpolationMode.BILINEAR
are supported. The corresponding Pillow integer constants, e.g.PIL.Image.BILINEAR
are accepted as well.fill (sequence or number, optional) –
Pixel fill value for the area outside the transformed image. If given a number, the value is used for all bands respectively.
Note
In torchscript mode single int/float value is not supported, please use a sequence of length 1:
[value, ]
.
- Returns:
transformed Image.
- Return type:
PIL Image or Tensor
Examples using
perspective
:Illustration of transforms