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