tf.nn.erosion2d
tf.nn.erosion2d
tf.nn.erosion2d
erosion2d( value, kernel, strides, rates, padding, name=None )
Defined in tensorflow/python/ops/nn_ops.py
.
See the guide: Neural Network > Morphological filtering
Computes the grayscale erosion of 4-D value
and 3-D kernel
tensors.
The value
tensor has shape [batch, in_height, in_width, depth]
and the kernel
tensor has shape [kernel_height, kernel_width, depth]
, i.e., each input channel is processed independently of the others with its own structuring function. The output
tensor has shape [batch, out_height, out_width, depth]
. The spatial dimensions of the output tensor depend on the padding
algorithm. We currently only support the default "NHWC" data_format
.
In detail, the grayscale morphological 2-D erosion is given by:
output[b, y, x, c] = min_{dy, dx} value[b, strides[1] * y - rates[1] * dy, strides[2] * x - rates[2] * dx, c] - kernel[dy, dx, c]
Duality: The erosion of value
by the kernel
is equal to the negation of the dilation of -value
by the reflected kernel
.
Args:
-
value
: ATensor
. 4-D with shape[batch, in_height, in_width, depth]
. -
kernel
: ATensor
. Must have the same type asvalue
. 3-D with shape[kernel_height, kernel_width, depth]
. -
strides
: A list ofints
that has length>= 4
. 1-D of length 4. The stride of the sliding window for each dimension of the input tensor. Must be:[1, stride_height, stride_width, 1]
. -
rates
: A list ofints
that has length>= 4
. 1-D of length 4. The input stride for atrous morphological dilation. Must be:[1, rate_height, rate_width, 1]
. -
padding
: Astring
from:"SAME", "VALID"
. The type of padding algorithm to use. -
name
: A name for the operation (optional). If not specified "erosion2d" is used.
Returns:
A Tensor
. Has the same type as value
. 4-D with shape [batch, out_height, out_width, depth]
.
Raises:
-
ValueError
: If thevalue
depth does not matchkernel
' shape, or if padding is other than'VALID'
or'SAME'
.
© 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/nn/erosion2d