(self, img)
Convert a ``numpy.ndarray`` to tensor.

        Args:
            img (numpy.ndarray): Image to be converted to tensor.

        Returns:
            Tensor: Converted image.
Convert a ``numpy.ndarray`` to tensor.
Convert a numpy . ndarray to tensor .
def __call__(self, img):
        """Convert a ``numpy.ndarray`` to tensor.

        Args:
            img (numpy.ndarray): Image to be converted to tensor.

        Returns:
            Tensor: Converted image.
        """
        if not(_is_numpy_image(img)):
            raise TypeError('img should be ndarray. Got {}'.format(type(img)))

        if isinstance(img, np.ndarray):
            # handle numpy array
            if img.ndim == 3:
                img = torch.from_numpy(img.transpose((2, 0, 1)).copy())
            elif img.ndim == 2:
                img = torch.from_numpy(img.copy())
            else:
                raise RuntimeError('img should be ndarray with 2 or 3 dimensions. Got {}'.format(img.ndim))

            # backward compatibility
            # return img.float().div(255)
            return img.float()
def __call__ ( self , img ) : if not ( _is_numpy_image ( img ) ) : raise TypeError ( 'img should be ndarray. Got {}' . format ( type ( img ) ) ) if isinstance ( img , np . ndarray ) : # handle numpy array if img . ndim == 3 : img = torch . from_numpy ( img . transpose ( ( 2 , 0 , 1 ) ) . copy ( ) ) elif img . ndim == 2 : img = torch . from_numpy ( img . copy ( ) ) else : raise RuntimeError ( 'img should be ndarray with 2 or 3 dimensions. Got {}' . format ( img . ndim ) ) # backward compatibility # return img.float().div(255) return img . float ( )