Image warping using per-pixel flow vectors.
@tf.function
tfa.image.dense_image_warp( image:
tfa.types.TensorLike
, flow:tfa.types.TensorLike
, name: Optional[str] = None ) -> tf.Tensor
Used in the notebooks
Used in the tutorials |
---|
Apply a non-linear warp to the image, where the warp is specified by a
dense flow field of offset vectors that define the correspondences of
pixel values in the output image back to locations in the source image.
Specifically, the pixel value at output[b, j, i, c]
is
images[b, j - flow[b, j, i, 0], i - flow[b, j, i, 1], c]
.
The locations specified by this formula do not necessarily map to an int
index. Therefore, the pixel value is obtained by bilinear
interpolation of the 4 nearest pixels around
(b, j - flow[b, j, i, 0], i - flow[b, j, i, 1])
. For locations outside
of the image, we use the nearest pixel values at the image boundary.
Args | |
---|---|
image
|
4-D float Tensor with shape [batch, height, width, channels] .
|
flow
|
A 4-D float Tensor with shape [batch, height, width, 2] .
|
name
|
A name for the operation (optional).
Note that image and flow can be of type |
Returns | |
---|---|
A 4-D float Tensor with shape[batch, height, width, channels]
and same type as input image.
|