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ExtractImagePatches

public final class ExtractImagePatches

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

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output <T>
asOutput ()
Returns the symbolic handle of the tensor.
static <T extends TType > ExtractImagePatches <T>
create ( Scope scope, Operand <T> images, List<Long> ksizes, List<Long> strides, List<Long> rates, String padding)
Factory method to create a class wrapping a new ExtractImagePatches operation.
Output <T>
patches ()
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.

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "ExtractImagePatches"

Public Methods

public Output <T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static ExtractImagePatches <T> create ( Scope scope, Operand <T> images, List<Long> ksizes, List<Long> strides, List<Long> rates, String padding)

Factory method to create a class wrapping a new ExtractImagePatches operation.

Parameters
scope current scope
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
  • a new instance of ExtractImagePatches

public Output <T> patches ()

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.