CropAndResizeGradBoxes

public final class CropAndResizeGradBoxes

Computes the gradient of the crop_and_resize op wrt the input boxes tensor.

Nested Classes

class CropAndResizeGradBoxes.Options Optional attributes for CropAndResizeGradBoxes  

Constants

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

Public Methods

Output<TFloat32>
asOutput()
Returns the symbolic handle of the tensor.
static CropAndResizeGradBoxes
create(Scope scope, Operand<TFloat32> grads, Operand<? extends TNumber> image, Operand<TFloat32> boxes, Operand<TInt32> boxInd, Options... options)
Factory method to create a class wrapping a new CropAndResizeGradBoxes operation.
static CropAndResizeGradBoxes.Options
method(String method)
Output<TFloat32>
output()
A 2-D tensor of shape `[num_boxes, 4]`.

Inherited Methods

Constants

public static final String OP_NAME

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

Constant Value: "CropAndResizeGradBoxes"

Public Methods

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 CropAndResizeGradBoxes create (Scope scope, Operand<TFloat32> grads, Operand<? extends TNumber> image, Operand<TFloat32> boxes, Operand<TInt32> boxInd, Options... options)

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

Parameters
scope current scope
grads A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.
image A 4-D tensor of shape `[batch, image_height, image_width, depth]`. Both `image_height` and `image_width` need to be positive.
boxes A 2-D tensor of shape `[num_boxes, 4]`. The `i`-th row of the tensor specifies the coordinates of a box in the `box_ind[i]` image and is specified in normalized coordinates `[y1, x1, y2, x2]`. A normalized coordinate value of `y` is mapped to the image coordinate at `y * (image_height - 1)`, so as the `[0, 1]` interval of normalized image height is mapped to `[0, image_height - 1] in image height coordinates. We do allow y1 > y2, in which case the sampled crop is an up-down flipped version of the original image. The width dimension is treated similarly. Normalized coordinates outside the `[0, 1]` range are allowed, in which case we use `extrapolation_value` to extrapolate the input image values.
boxInd A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`. The value of `box_ind[i]` specifies the image that the `i`-th box refers to.
options carries optional attributes values
Returns
  • a new instance of CropAndResizeGradBoxes

public static CropAndResizeGradBoxes.Options method (String method)

Parameters
method A string specifying the interpolation method. Only 'bilinear' is supported for now.

public Output<TFloat32> output ()

A 2-D tensor of shape `[num_boxes, 4]`.