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bob
bob.bio.vein
Commits
3a3d8eb3
Commit
3a3d8eb3
authored
Jun 27, 2017
by
André Anjos
💬
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b92fd827
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bob/bio/vein/utils.py
bob/bio/vein/utils.py
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bob/bio/vein/utils.py
View file @
3a3d8eb3
...
@@ -3,7 +3,6 @@
...
@@ -3,7 +3,6 @@
import
numpy
import
numpy
import
scipy.signal
import
scipy.signal
import
bob.ip.base
import
bob.sp
import
bob.sp
import
bob.core
import
bob.core
...
@@ -11,22 +10,27 @@ import bob.core
...
@@ -11,22 +10,27 @@ import bob.core
def
imfilter
(
a
,
b
):
def
imfilter
(
a
,
b
):
"""Applies a 2D filtering between images
"""Applies a 2D filtering between images
This implementation was created to work similarly like the Matlab one.
This implementation was created to work similarly like the Matlab one when
``boundary = replicate``. It filters the image ``a`` with the filter ``b`` by
applying it over an extended version of ``a``, expanded of ``b.shape`` on the
right and bottom, by repeating the values on ``a``'s borders.
The filter is then applied to the image considering only the ``valid`` range
with :py:func:`scipy.signal.convolve2d`.
Parameters:
Parameters:
a (numpy.ndarray): A 2-dimensional :py:class:`numpy.ndarray` which
a (numpy.ndarray): A 2-dimensional :py:class:`numpy.ndarray` which
represents the image to be filtered. The dtype of the array is supposed
represents the image to be filtered. The dtype of the array is supposed
to be 64-floats. You can also pass an 8-bit unsigned integer array,
to be 64-
bit
floats. You can also pass an 8-bit unsigned integer array,
loaded from a file (for example). In this case it will be scaled as
loaded from a file (for example). In this case it will be scaled as
with
with
:py:func:`bob.core.convert` and the range reset to ``[0.0, 1.0]``.
:py:func:`bob.core.convert` and the range reset to ``[0.0, 1.0]``.
b (numpy.ndarray): A 64-bit float 2-dimensional :py:class:`numpy.ndarray`
b (numpy.ndarray): A 64-bit float 2-dimensional :py:class:`numpy.ndarray`
which represents the filter to be applied to the image. The input filter
which represents the filter to be applied to the image. The input filter
has to be rotated by 180 degrees as we use
has to be rotated by 180 degrees as we use
:py:func:`scipy.signal.convolve2d` to apply it. You can rotate your
:py:func:`scipy.signal.convolve2d` to apply it.
filter ``b`` with the help of :py:func:`bob.ip.base.rotate`.
"""
"""
...
...
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