tensorflow::ops::CropAndResize

#include <image_ops.h>

Extracts crops from the input image tensor and bilinearly resizes them (possibly.

Summary

with aspect ratio change) to a common output size specified by crop_size. This is more general than the crop_to_bounding_box op which extracts a fixed size slice from the input image and does not allow resizing or aspect ratio change.

Returns a tensor with crops from the input image at positions defined at the bounding box locations in boxes. The cropped boxes are all resized (with bilinear interpolation) to a fixed size = [crop_height, crop_width]. The result is a 4-D tensor [num_boxes, crop_height, crop_width, depth].

Arguments:

  • scope: A Scope object
  • 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.
  • box_ind: 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.
  • crop_size: A 1-D tensor of 2 elements, size = [crop_height, crop_width]. All cropped image patches are resized to this size. The aspect ratio of the image content is not preserved. Both crop_height and crop_width need to be positive.

Optional attributes (see Attrs):

  • method: A string specifying the interpolation method. Only 'bilinear' is supported for now.
  • extrapolation_value: Value used for extrapolation, when applicable.

Returns:

  • Output: A 4-D tensor of shape [num_boxes, crop_height, crop_width, depth].

Constructors and Destructors

CropAndResize(const ::tensorflow::Scope & scope, ::tensorflow::Input image, ::tensorflow::Input boxes, ::tensorflow::Input box_ind, ::tensorflow::Input crop_size)
CropAndResize(const ::tensorflow::Scope & scope, ::tensorflow::Input image, ::tensorflow::Input boxes, ::tensorflow::Input box_ind, ::tensorflow::Input crop_size, const CropAndResize::Attrs & attrs)

Public attributes

crops

Public functions

node() const
::tensorflow::Node *
operator::tensorflow::Input() const
operator::tensorflow::Output() const

Public static functions

ExtrapolationValue(float x)
Method(StringPiece x)

Structs

tensorflow::ops::CropAndResize::Attrs

Optional attribute setters for CropAndResize.

Public attributes

crops

::tensorflow::Output crops

Public functions

CropAndResize

 CropAndResize(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input image,
  ::tensorflow::Input boxes,
  ::tensorflow::Input box_ind,
  ::tensorflow::Input crop_size
)

CropAndResize

 CropAndResize(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input image,
  ::tensorflow::Input boxes,
  ::tensorflow::Input box_ind,
  ::tensorflow::Input crop_size,
  const CropAndResize::Attrs & attrs
)

node

::tensorflow::Node * node() const 

operator::tensorflow::Input

 operator::tensorflow::Input() const 

operator::tensorflow::Output

 operator::tensorflow::Output() const 

Public static functions

ExtrapolationValue

Attrs ExtrapolationValue(
  float x
)

Method

Attrs Method(
  StringPiece x
)