def decode_image_with_pil(encoded_image: torch.Tensor) -> torch.Tensor:
image = torch.as_tensor(
np.array(PIL.Image.open(ReadOnlyTensorBuffer(encoded_image)),
copy=True))
if image.ndim == 2:
image = image.unsqueeze(2)
return image.permute(2, 0, 1)
def decode_video_with_av(
encoded_video: torch.Tensor
) -> Tuple[torch.Tensor, torch.Tensor, Dict[str, Any]]:
with unittest.mock.patch("torchvision.io.video.os.path.exists",
return_value=True):
return read_video(
ReadOnlyTensorBuffer(encoded_video)) # type: ignore[arg-type]
def image_size(self) -> Tuple[int, int]:
if not hasattr(self, "_image_size"):
with PIL.Image.open(ReadOnlyTensorBuffer(self)) as image:
self._image_size = image.height, image.width
return self._image_size