tensorflow::ops::ExtractImagePatches

#include <array_ops.h>

Extract patches from images and put them in the "depth" output dimension.

Summary

Args:

  • scope: A Scope object
  • images: 4-D Tensor with shape [batch, in_rows, in_cols, depth].
  • ksizes: The size of the sliding window for each dimension of images.
  • strides: How far the centers of two consecutive patches are in the images. Must be: [1, stride_rows, stride_cols, 1].
  • rates: Must be: [1, rate_rows, rate_cols, 1]. This is the input stride, specifying how far two consecutive patch samples are in the input. Equivalent to extracting patches with patch_sizes_eff = patch_sizes + (patch_sizes - 1) * (rates - 1), followed by subsampling them spatially by a factor of rates. This is equivalent to rate in dilated (a.k.a. Atrous) convolutions.
  • padding: The type of padding algorithm to use.

Returns:

  • Output: 4-D Tensor with shape [batch, out_rows, out_cols, ksize_rows * ksize_cols * depth] containing image patches with size ksize_rows x ksize_cols x depth vectorized in the "depth" dimension. Note out_rows and out_cols are the dimensions of the output patches.

Constructors and Destructors
ExtractImagePatches(const ::tensorflow::Scope & scope, ::tensorflow::Input images, const gtl::ArraySlice< int > & ksizes, const gtl::ArraySlice< int > & strides, const gtl::ArraySlice< int > & rates, StringPiece padding)

Public attributes
operation
patches

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

Public attributes

operation

Operation operation

patches

::tensorflow::Output patches

Public functions

ExtractImagePatches

 ExtractImagePatches(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input images,
  const gtl::ArraySlice< int > & ksizes,
  const gtl::ArraySlice< int > & strides,
  const gtl::ArraySlice< int > & rates,
  StringPiece padding
)

node

::tensorflow::Node * node() const

operator::tensorflow::Input

 operator::tensorflow::Input() const

operator::tensorflow::Output

 operator::tensorflow::Output() const