Blend image1
and image2
using factor
.
tfa.image.blend(
image1: tfa.types.TensorLike
,
image2: tfa.types.TensorLike
,
factor: tfa.types.Number
) -> tf.Tensor
Factor can be above 0.0. A value of 0.0 means only image1
is used.
A value of 1.0 means only image2
is used. A value between 0.0 and
1.0 means we linearly interpolate the pixel values between the two
images. A value greater than 1.0 "extrapolates" the difference
between the two pixel values, and we clip the results to values
between 0 and 255.
Args |
image1
|
An image Tensor of shape
(num_rows, num_columns, num_channels) (HWC), or
(num_rows, num_columns) (HW), or
(num_channels, num_rows, num_columns) (CHW).
|
image2
|
An image Tensor of shape
(num_rows, num_columns, num_channels) (HWC), or
(num_rows, num_columns) (HW), or
(num_channels, num_rows, num_columns) .
|
factor
|
A floating point value or Tensor of type tf.float32 above 0.0.
|