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#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.
Public attributes
Public functions
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2021-08-16 UTC.
[null,null,["Last updated 2021-08-16 UTC."],[],[],null,["# tensorflow::ops::ExtractImagePatches Class Reference\n\ntensorflow::\nops::\nExtractImagePatches\n======================================\n\n`\n#include \u003carray_ops.h\u003e\n`\n\n\nExtract\n`\npatches\n`\nfrom\n`\nimages\n`\nand put them in the \"depth\" output dimension.\n\nSummary\n-------\n\n\nArgs:\n\n- scope: A [Scope](/versions/r2.6/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- images: 4-D [Tensor](/versions/r2.6/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with shape `\n [batch, in_rows, in_cols, depth]\n ` .\n- ksizes: The size of the sliding window for each dimension of `\n images\n ` .\n- strides: How far the centers of two consecutive patches are in the images. Must be: `\n [1, stride_rows, stride_cols, 1]\n ` .\n- rates: Must be: `\n [1, rate_rows, rate_cols, 1]\n ` . This is the input stride, specifying how far two consecutive patch samples are in the input. Equivalent to extracting patches with `\n patch_sizes_eff = patch_sizes + (patch_sizes - 1) * (rates - 1)\n ` , followed by subsampling them spatially by a factor of `\n rates\n ` . This is equivalent to `\n rate\n ` in dilated (a.k.a. Atrous) convolutions.\n- padding: The type of padding algorithm to use.\n\n\u003cbr /\u003e\n\n\nReturns:\n\n- `\n `[Output](/versions/r2.6/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)`\n ` : 4-D [Tensor](/versions/r2.6/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with shape `\n [batch, out_rows, out_cols, ksize_rows * ksize_cols * depth]\n ` containing image patches with size `\n ksize_rows x ksize_cols x depth\n ` vectorized in the \"depth\" dimension. Note `\n out_rows\n ` and `\n out_cols\n ` are the dimensions of the output patches.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| ` `[ExtractImagePatches](#classtensorflow_1_1ops_1_1_extract_image_patches_1a48a27e59bf001d9d0599c4a4ad3abcf9)` (const :: `[tensorflow::Scope](/versions/r2.6/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, :: `[tensorflow::Input](/versions/r2.6/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` images, const gtl::ArraySlice\u003c int \u003e & ksizes, const gtl::ArraySlice\u003c int \u003e & strides, const gtl::ArraySlice\u003c int \u003e & rates, StringPiece padding) ` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|\n| ` `[operation](#classtensorflow_1_1ops_1_1_extract_image_patches_1a20f65de6816816f98d46af224137110d)` ` | ` `[Operation](/versions/r2.6/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)` ` |\n| ` `[patches](#classtensorflow_1_1ops_1_1_extract_image_patches_1a282b671f1a0d52422cd35c75d6819ee1)` ` | ` :: `[tensorflow::Output](/versions/r2.6/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)` ` |\n\n| ### Public functions ||\n|-------------------------------------------------------------------------------------------------------------------------------------|--------------------------|\n| ` `[node](#classtensorflow_1_1ops_1_1_extract_image_patches_1a812a245b3efe85c0003da911be95b891)` () const ` | ` ::tensorflow::Node * ` |\n| ` `[operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_extract_image_patches_1a3dbc12d46ac43f4e5cb6868030310880)` () const ` | ` ` |\n| ` `[operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_extract_image_patches_1a7a11be91c9fd8c6b3c5d48ae30630a18)` () const ` | ` ` |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### patches\n\n```text\n::tensorflow::Output patches\n``` \n\nPublic functions\n----------------\n\n### ExtractImagePatches\n\n```gdscript\n ExtractImagePatches(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input images,\n const gtl::ArraySlice\u003c int \u003e & ksizes,\n const gtl::ArraySlice\u003c int \u003e & strides,\n const gtl::ArraySlice\u003c int \u003e & rates,\n StringPiece padding\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n```"]]
