ResizeArea

public final class ResizeArea

Resize `images` to `size` using area interpolation.

Input images can be of different types but output images are always float.

The range of pixel values for the output image might be slightly different from the range for the input image because of limited numerical precision. To guarantee an output range, for example `[0.0, 1.0]`, apply tf.clip_by_value to the output.

Each output pixel is computed by first transforming the pixel's footprint into the input tensor and then averaging the pixels that intersect the footprint. An input pixel's contribution to the average is weighted by the fraction of its area that intersects the footprint. This is the same as OpenCV's INTER_AREA.

Nested Classes

class ResizeArea.Options Optional attributes for ResizeArea

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

static ResizeArea.Options	alignCorners(Boolean alignCorners)
Output<TFloat32>	asOutput() Returns the symbolic handle of the tensor.
static ResizeArea	create(Scope scope, Operand<? extends TNumber> images, Operand<TInt32> size, Options... options) Factory method to create a class wrapping a new ResizeArea operation.
Output<TFloat32>	resizedImages() 4-D with shape `[batch, new_height, new_width, channels]`.

Inherited Methods

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single `Operation`.
final String	toString()

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single `Operation`.

From interface org.tensorflow.Operand

abstract Output<TFloat32>	asOutput() Returns the symbolic handle of the tensor.
abstract TFloat32	asTensor() Returns the tensor at this operand.
abstract Shape	shape() Returns the (possibly partially known) shape of the tensor referred to by the `Output` of this operand.
abstract Class<TFloat32>	type() Returns the tensor type of this operand

From interface org.tensorflow.ndarray.Shaped

abstract int	rank()
abstract Shape	shape()
abstract long	size() Computes and returns the total size of this container, in number of values.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "ResizeArea"

Public Methods

public static ResizeArea.Options alignCorners (Boolean alignCorners)

Parameters

alignCorners	If true, the centers of the 4 corner pixels of the input and output tensors are aligned, preserving the values at the corner pixels. Defaults to false.

public Output<TFloat32> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static ResizeArea create (Scope scope, Operand<? extends TNumber> images, Operand<TInt32> size, Options... options)

Factory method to create a class wrapping a new ResizeArea operation.

Parameters

scope	current scope
images	4-D with shape `[batch, height, width, channels]`.
size	= A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The new size for the images.
options	carries optional attributes values

Returns

a new instance of ResizeArea

public Output<TFloat32> resizedImages ()

4-D with shape `[batch, new_height, new_width, channels]`.