tf.extract_image_patches
tf.extract_image_patches
tf.extract_image_patches
extract_image_patches( images, ksizes, strides, rates, padding, name=None )
Defined in tensorflow/python/ops/gen_array_ops.py
.
See the guide: Tensor Transformations > Slicing and Joining
Extract patches
from images
and put them in the "depth" output dimension.
Args:
-
images
: ATensor
. Must be one of the following types:float32
,float64
,int32
,int64
,uint8
,int16
,int8
,uint16
,half
. 4-D Tensor with shape[batch, in_rows, in_cols, depth]
. -
ksizes
: A list ofints
that has length>= 4
. The size of the sliding window for each dimension ofimages
. -
strides
: A list ofints
that has length>= 4
. 1-D of length 4. How far the centers of two consecutive patches are in the images. Must be:[1, stride_rows, stride_cols, 1]
. -
rates
: A list ofints
that has length>= 4
. 1-D of length 4. 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 withpatch_sizes_eff = patch_sizes + (patch_sizes - 1) * (rates - 1)
, followed by subsampling them spatially by a factor ofrates
. -
padding
: Astring
from:"SAME", "VALID"
. The type of padding algorithm to use.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]
*name
: A name for the operation (optional).
Returns:
A Tensor
. Has the same type as images
. 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.
© 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/python/tf/extract_image_patches