tensorflow::ops::ResizeArea

#include <image_ops.h>

Resize images to size using area interpolation.

Summary

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

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.

Arguments:

• scope: A Scope object
• 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.

Optional attributes (see Attrs):

• align_corners: If true, rescale input by (new_height - 1) / (height - 1), which exactly aligns the 4 corners of images and resized images. If false, rescale by new_height / height. Treat similarly the width dimension.

Returns:

• Output: 4-D with shape [batch, new_height, new_width, channels].

Public attributes

::tensorflow::Output resized_images

Public functions

 ResizeArea(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input images,
  ::tensorflow::Input size
)

 ResizeArea(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input images,
  ::tensorflow::Input size,
  const ResizeArea::Attrs & attrs
)

::tensorflow::Node * node() const 

operator::tensorflow::Input() const 

operator::tensorflow::Output() const 

Public static functions

Attrs AlignCorners(
  bool x
)