Returns:
A tensor of shape `[B, H, W, 1]` containing the mattes.
Raises:
ValueError: If `image`, `coeff_mul`, or `coeff_add` are not of rank 4. If
the last dimension of `coeff_add` is not 1. If the batch dimensions of
`image`, `coeff_mul`, and `coeff_add` do not match.
"""
with tf.compat.v1.name_scope(name, "matting_reconstruct",
[image, coeff_mul, coeff_add]):
image = tf.convert_to_tensor(value=image)
coeff_mul = tf.convert_to_tensor(value=coeff_mul)
coeff_add = tf.convert_to_tensor(value=coeff_add)
shape.check_static(image, has_rank=4)
shape.check_static(coeff_mul, has_rank=4)
shape.check_static(coeff_add, has_rank=4, has_dim_equals=(-1, 1))
shape.compare_batch_dimensions(tensors=(image, coeff_mul),
last_axes=-1,
broadcast_compatible=False)
shape.compare_batch_dimensions(tensors=(image, coeff_add),
last_axes=-2,
broadcast_compatible=False)
return tfg_vector.dot(coeff_mul, image) + coeff_add
# API contains all public functions and classes.
__all__ = export_api.get_functions_and_classes()
def test_get_functions_and_classes(self):
"""Tests that get_functions_and_classes does not raise an exception."""
try:
export_api.get_functions_and_classes()
except Exception as e: # pylint: disable=broad-except
self.fail("Exception raised: %s" % str(e))
