Computes the grayscale dilation of 4-D input
and 3-D filters
tensors.
tf.compat.v2.nn.dilation2d( input, filters, strides, padding, data_format, dilations, name=None )
The input
tensor has shape [batch, in_height, in_width, depth]
and the filters
tensor has shape [filter_height, filter_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 dilation is the max-sum correlation (for consistency with conv2d
, we use unmirrored filters):
output[b, y, x, c] = max_{dy, dx} input[b, strides[1] * y + rates[1] * dy, strides[2] * x + rates[2] * dx, c] + filters[dy, dx, c]
Max-pooling is a special case when the filter has size equal to the pooling kernel size and contains all zeros.
Note on duality: The dilation of input
by the filters
is equal to the negation of the erosion of -input
by the reflected filters
.
Args | |
---|---|
input | A Tensor . Must be one of the following types: float32 , float64 , int32 , uint8 , int16 , int8 , int64 , bfloat16 , uint16 , half , uint32 , uint64 . 4-D with shape [batch, in_height, in_width, depth] . |
filters | A Tensor . Must have the same type as input . 3-D with shape [filter_height, filter_width, depth] . |
strides | A list of ints that has length >= 4 . The stride of the sliding window for each dimension of the input tensor. Must be: [1, stride_height, stride_width, 1] . |
padding | A string from: "SAME", "VALID" . The type of padding algorithm to use. |
data_format | A string , only "NHWC" is currently supported. |
dilations | A list of ints that has length >= 4 . The input stride for atrous morphological dilation. Must be: [1, rate_height, rate_width, 1] . |
name | A name for the operation (optional). |
Returns | |
---|---|
A Tensor . Has the same type as input . |
© 2020 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/versions/r1.15/api_docs/python/tf/compat/v2/nn/dilation2d