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#
# The Python Imaging Library.
# $Id$
#
# standard filters
#
# History:
# 1995-11-27 fl Created
# 2002-06-08 fl Added rank and mode filters
# 2003-09-15 fl Fixed rank calculation in rank filter; added expand call
#
# Copyright (c) 1997-2003 by Secret Labs AB.
# Copyright (c) 1995-2002 by Fredrik Lundh.
#
# See the README file for information on usage and redistribution.
#
import functools
class Filter(object):
pass
class MultibandFilter(Filter):
pass
class Kernel(MultibandFilter):
"""
Create a convolution kernel. The current version only
supports 3x3 and 5x5 integer and floating point kernels.
In the current version, kernels can only be applied to
"L" and "RGB" images.
:param size: Kernel size, given as (width, height). In the current
version, this must be (3,3) or (5,5).
:param kernel: A sequence containing kernel weights.
:param scale: Scale factor. If given, the result for each pixel is
divided by this value. the default is the sum of the
kernel weights.
:param offset: Offset. If given, this value is added to the result,
after it has been divided by the scale factor.
"""
def __init__(self, size, kernel, scale=None, offset=0):
if scale is None:
# default scale is sum of kernel
scale = functools.reduce(lambda a, b: a+b, kernel)
if size[0] * size[1] != len(kernel):
raise ValueError("not enough coefficients in kernel")
self.filterargs = size, scale, offset, kernel
def filter(self, image):
if image.mode == "P":
raise ValueError("cannot filter palette images")
return image.filter(*self.filterargs)
class BuiltinFilter(Kernel):
def __init__(self):
pass
class RankFilter(Filter):
"""
Create a rank filter. The rank filter sorts all pixels in
a window of the given size, and returns the **rank**'th value.
:param size: The kernel size, in pixels.
:param rank: What pixel value to pick. Use 0 for a min filter,
``size * size / 2`` for a median filter, ``size * size - 1``
for a max filter, etc.
"""
name = "Rank"
def __init__(self, size, rank):
self.size = size
self.rank = rank
def filter(self, image):
if image.mode == "P":
raise ValueError("cannot filter palette images")
image = image.expand(self.size//2, self.size//2)
return image.rankfilter(self.size, self.rank)
class MedianFilter(RankFilter):
"""
Create a median filter. Picks the median pixel value in a window with the
given size.
:param size: The kernel size, in pixels.
"""
name = "Median"
def __init__(self, size=3):
self.size = size
self.rank = size*size//2
class MinFilter(RankFilter):
"""
Create a min filter. Picks the lowest pixel value in a window with the
given size.
:param size: The kernel size, in pixels.
"""
name = "Min"
def __init__(self, size=3):
self.size = size
self.rank = 0
class MaxFilter(RankFilter):
"""
Create a max filter. Picks the largest pixel value in a window with the
given size.
:param size: The kernel size, in pixels.
"""
name = "Max"
def __init__(self, size=3):
self.size = size
self.rank = size*size-1
class ModeFilter(Filter):
"""
Create a mode filter. Picks the most frequent pixel value in a box with the
given size. Pixel values that occur only once or twice are ignored; if no
pixel value occurs more than twice, the original pixel value is preserved.
:param size: The kernel size, in pixels.
"""
name = "Mode"
def __init__(self, size=3):
self.size = size
def filter(self, image):
return image.modefilter(self.size)
class GaussianBlur(MultibandFilter):
"""Gaussian blur filter.
:param radius: Blur radius.
"""
name = "GaussianBlur"
def __init__(self, radius=2):
self.radius = radius
def filter(self, image):
return image.gaussian_blur(self.radius)
class BoxBlur(MultibandFilter):
"""Blurs the image by setting each pixel to the average value of the pixels
in a square box extending radius pixels in each direction.
Supports float radius of arbitrary size. Uses an optimized implementation
which runs in linear time relative to the size of the image
for any radius value.
:param radius: Size of the box in one direction. Radius 0 does not blur,
returns an identical image. Radius 1 takes 1 pixel
in each direction, i.e. 9 pixels in total.
"""
name = "BoxBlur"
def __init__(self, radius):
self.radius = radius
def filter(self, image):
return image.box_blur(self.radius)
class UnsharpMask(MultibandFilter):
"""Unsharp mask filter.
See Wikipedia's entry on `digital unsharp masking`_ for an explanation of
the parameters.
:param radius: Blur Radius
:param percent: Unsharp strength, in percent
:param threshold: Threshold controls the minimum brightness change that
will be sharpened
.. _digital unsharp masking: https://en.wikipedia.org/wiki/Unsharp_masking#Digital_unsharp_masking
"""
name = "UnsharpMask"
def __init__(self, radius=2, percent=150, threshold=3):
self.radius = radius
self.percent = percent
self.threshold = threshold
def filter(self, image):
return image.unsharp_mask(self.radius, self.percent, self.threshold)
class BLUR(BuiltinFilter):
name = "Blur"
filterargs = (5, 5), 16, 0, (
1, 1, 1, 1, 1,
1, 0, 0, 0, 1,
1, 0, 0, 0, 1,
1, 0, 0, 0, 1,
1, 1, 1, 1, 1
)
class CONTOUR(BuiltinFilter):
name = "Contour"
filterargs = (3, 3), 1, 255, (
-1, -1, -1,
-1, 8, -1,
-1, -1, -1
)
class DETAIL(BuiltinFilter):
name = "Detail"
filterargs = (3, 3), 6, 0, (
0, -1, 0,
-1, 10, -1,
0, -1, 0
)
class EDGE_ENHANCE(BuiltinFilter):
name = "Edge-enhance"
filterargs = (3, 3), 2, 0, (
-1, -1, -1,
-1, 10, -1,
-1, -1, -1
)
class EDGE_ENHANCE_MORE(BuiltinFilter):
name = "Edge-enhance More"
filterargs = (3, 3), 1, 0, (
-1, -1, -1,
-1, 9, -1,
-1, -1, -1
)
class EMBOSS(BuiltinFilter):
name = "Emboss"
filterargs = (3, 3), 1, 128, (
-1, 0, 0,
0, 1, 0,
0, 0, 0
)
class FIND_EDGES(BuiltinFilter):
name = "Find Edges"
filterargs = (3, 3), 1, 0, (
-1, -1, -1,
-1, 8, -1,
-1, -1, -1
)
class SHARPEN(BuiltinFilter):
name = "Sharpen"
filterargs = (3, 3), 16, 0, (
-2, -2, -2,
-2, 32, -2,
-2, -2, -2
)
class SMOOTH(BuiltinFilter):
name = "Smooth"
filterargs = (3, 3), 13, 0, (
1, 1, 1,
1, 5, 1,
1, 1, 1
)
class SMOOTH_MORE(BuiltinFilter):
name = "Smooth More"
filterargs = (5, 5), 100, 0, (
1, 1, 1, 1, 1,
1, 5, 5, 5, 1,
1, 5, 44, 5, 1,
1, 5, 5, 5, 1,
1, 1, 1, 1, 1
)
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