Extract patches
from images
and put them in the "depth" output dimension.
tf.compat.v1.extract_image_patches(
images,
ksizes=None,
strides=None,
rates=None,
padding=None,
name=None,
sizes=None
)
Args |
images
|
A Tensor . Must be one of the following types: bfloat16 , half , float32 , float64 , int8 , int16 , int32 , int64 , uint8 , uint16 , uint32 , uint64 , complex64 , complex128 , bool .
4-D Tensor with shape [batch, in_rows, in_cols, depth] .
|
ksizes
|
A list of ints that has length >= 4 .
The size of the sliding window for each dimension of images .
|
strides
|
A list of ints that has 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 of ints that has 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 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
|
A string from: "SAME", "VALID" .
The type of padding algorithm to use.
|
name
|
A name for the operation (optional).
|
Returns |
A Tensor . Has the same type as images .
|