1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
|
# coding: utf-8
# /*##########################################################################
# Copyright (C) 2017-2018 European Synchrotron Radiation Facility
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
# ############################################################################*/
"""
This module provides :func:`medfilt2d`, a 2D median filter function
with the choice between 2 implementations: 'cpp' and 'opencl'.
"""
__authors__ = ["H. Payno"]
__license__ = "MIT"
__date__ = "04/05/2017"
import logging
from silx.math import medianfilter as medianfilter_cpp
from silx.opencl import ocl as _ocl
if _ocl is not None:
from silx.opencl import medfilt as medfilt_opencl
else: # No OpenCL device or pyopencl not installed
medfilt_opencl = None
_logger = logging.getLogger(__name__)
MEDFILT_ENGINES = ['cpp', 'opencl']
def medfilt2d(image, kernel_size=3, engine='cpp'):
"""Apply a median filter on an image.
This median filter is using a 'nearest' padding for values
past the array edges. If you want more padding options or
functionalities for the median filter (conditional filter
for example) please have a look at
:mod:`silx.math.medianfilter`.
:param numpy.ndarray image: the 2D array for which we want to apply
the median filter.
:param kernel_size: the dimension of the kernel.
Kernel size must be odd.
If a scalar is given, then it is used as the size in both dimension.
Default: (3, 3)
:type kernel_size: A int or a list of 2 int (kernel_height, kernel_width)
:param engine: the type of implementation to use.
Valid values are: 'cpp' (default) and 'opencl'
:returns: the array with the median value for each pixel.
.. note:: if the opencl implementation is requested but
is not present or fails, the cpp implementation is called.
"""
if engine not in MEDFILT_ENGINES:
err = 'silx doesn\'t have an implementation for the requested engine: '
err += '%s' % engine
raise ValueError(err)
if len(image.shape) is not 2:
raise ValueError('medfilt2d deals with arrays of dimension 2 only')
if engine == 'cpp':
return medianfilter_cpp.medfilt(data=image,
kernel_size=kernel_size,
conditional=False)
elif engine == 'opencl':
if medfilt_opencl is None:
wrn = 'opencl median filter not available. '
wrn += 'Launching cpp implementation.'
_logger.warning(wrn)
# instead call the cpp implementation
return medianfilter_cpp.medfilt(data=image,
kernel_size=kernel_size,
conditional=False)
else:
try:
medianfilter = medfilt_opencl.MedianFilter2D(image.shape,
devicetype="gpu")
res = medianfilter.medfilt2d(image, kernel_size)
except(RuntimeError, MemoryError, ImportError):
wrn = 'Exception occured in opencl median filter. '
wrn += 'To get more information see debug log.'
wrn += 'Launching cpp implementation.'
_logger.warning(wrn)
_logger.debug("median filter - openCL implementation issue.",
exc_info=True)
# instead call the cpp implementation
res = medianfilter_cpp.medfilt(data=image,
kernel_size=kernel_size,
conditional=False)
return res
|
