tfa.image.resampler

Resamples input data at user defined coordinates.

@tf.function
tfa.image.resampler(
    data: tfa.types.TensorLike,
    warp: tfa.types.TensorLike,
    name: Optional[str] = None
) -> tf.Tensor

The resampler currently only supports bilinear interpolation of 2D data.

data Tensor of shape [batch_size, data_height, data_width, data_num_channels] containing 2D data that will be resampled.
warp Tensor of minimum rank 2 containing the coordinates at which resampling will be performed. Since only bilinear interpolation is currently supported, the last dimension of the warp tensor must be 2, representing the (x, y) coordinate where x is the index for width and y is the index for height.
name Optional name of the op.

Tensor of resampled values from data. The output tensor shape is determined by the shape of the warp tensor. For example, if data is of shape [batch_size, data_height, data_width, data_num_channels] and warp of shape [batch_size, dim_0, ... , dim_n, 2] the output will be of shape [batch_size, dim_0, ... , dim_n, data_num_channels].

ImportError if the wrapper generated during compilation is not present when the function is called.