|View source on GitHub|
Applies the given transform(s) to the image(s).
tf.contrib.image.transform( images, transforms, interpolation='NEAREST', output_shape=None, name=None )
images: A tensor of shape (num_images, num_rows, num_columns, num_channels) (NHWC), (num_rows, num_columns, num_channels) (HWC), or (num_rows, num_columns) (HW). The rank must be statically known (the shape is not
transforms: Projective transform matrix/matrices. A vector of length 8 or tensor of size N x 8. If one row of transforms is [a0, a1, a2, b0, b1, b2, c0, c1], then it maps the output point
(x, y)to a transformed input point
(x', y') = ((a0 x + a1 y + a2) / k, (b0 x + b1 y + b2) / k), where
k = c0 x + c1 y + 1. The transforms are inverted compared to the transform mapping input points to output points. Note that gradients are not backpropagated into transformation parameters.
interpolation: Interpolation mode. Supported values: "NEAREST", "BILINEAR".
output_shape: Output dimesion after the transform, [height, width]. If None, output is the same size as input image.
name: The name of the op.
Image(s) with the same type and shape as
images, with the given
transform(s) applied. Transformed coordinates outside of the input image
will be filled with zeros.
imageis an invalid type.
ValueError: If output shape is not 1-D int32 Tensor.