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]. The resizing is corner aligned. In particular, if boxes = [[0, 0, 1, 1]], the method will give identical results to using tf.image.resize_bilinear() with align_corners=True.

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].

Public attributes

::tensorflow::Output crops

Public functions

 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
)

::tensorflow::Node * node() const 

operator::tensorflow::Input() const 

operator::tensorflow::Output() const 

Public static functions

Attrs ExtrapolationValue(
  float x
)

Attrs Method(
  StringPiece x
)