tf.contrib.image.transform

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

Defined in tensorflow/contrib/image/python/ops/image_ops.py.

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

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.