tf.contrib.image.transform

Applies the given transform(s) to the image(s).

tf.contrib.image.transform(
    images, transforms, interpolation='NEAREST', output_shape=None, name=None
)

Args
`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 `TensorShape(None)`.
`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.

Returns
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.

Raises
`TypeError`	If `image` is an invalid type.
`ValueError`	If output shape is not 1-D int32 Tensor.

Args