#include <array_ops.h>
Extract patches
from images
and put them in the "depth" output dimension.
Arguments:
[batch, in_rows, in_cols, depth]
.images
.[1, stride_rows, stride_cols, 1]
.[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.We specify the size-related attributes as:
```python ksizes = [1, ksize_rows, ksize_cols, 1] strides = [1, strides_rows, strides_cols, 1] rates = [1, rates_rows, rates_cols, 1] ```
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 | |
---|---|
patches |
Public functions | |
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node() const | ::tensorflow::Node * |
operator::tensorflow::Input() const | |
operator::tensorflow::Output() const |
::tensorflow::Output patches
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 )
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output() const
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/cc/class/tensorflow/ops/extract-image-patches.html