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.
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static <T extends TType> ExtractImagePatches<T> | |
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
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.