#
# 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.
#
class Filter:
pass
##
# Convolution filter kernel.
class Kernel(Filter):
##
# Create a convolution kernel. The current version only
# supports 3x3 and 5x5 integer and floating point kernels.
# <p>
# In the current version, kernels can only be applied to
# "L" and "RGB" images.
#
# @def __init__(size, kernel, **options)
# @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 **options Optional keyword arguments.
# @keyparam scale Scale factor. If given, the result for each
# pixel is divided by this value. The default is the sum
# of the kernel weights.
# @keyparam 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 = 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 apply(image.filter, self.filterargs)
class BuiltinFilter(Kernel):
def __init__(self):
pass
##
# Rank filter.
class RankFilter(Filter):
name = "Rank"
##
# 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.
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)
##
# Median filter. Picks the median pixel value in a window with the
# given size.
class MedianFilter(RankFilter):
name = "Median"
##
# Create a median filter.
#
# @param size The kernel size, in pixels.
def __init__(self, size=3):
self.size = size
self.rank = size*size/2
##
# Min filter. Picks the lowest pixel value in a window with the given
# size.
class MinFilter(RankFilter):
name = "Min"
##
# Create a min filter.
#
# @param size The kernel size, in pixels.
def __init__(self, size=3):
self.size = size
self.rank = 0
##
# Max filter. Picks the largest pixel value in a window with the
# given size.
class MaxFilter(RankFilter):
name = "Max"
##
# Create a max filter.
#
# @param size The kernel size, in pixels.
def __init__(self, size=3):
self.size = size
self.rank = size*size-1
##
# 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.
class ModeFilter(Filter):
name = "Mode"
##
# Create a mode filter.
#
# @param size The kernel size, in pixels.
def __init__(self, size=3):
self.size = size
def filter(self, image):
return image.modefilter(self.size)
##
# Gaussian blur filter.
class GaussianBlur(Filter):
name = "GaussianBlur"
def __init__(self, radius=2):
self.radius = 2
def filter(self, image):
return image.gaussian_blur(self.radius)
##
# Unsharp mask filter.
class UnsharpMask(Filter):
name = "UnsharpMask"
def __init__(self, radius=2, percent=150, threshold=3):
self.radius = 2
self.percent = percent
self.threshold = threshold
def filter(self, image):
return image.unsharp_mask(self.radius, self.percent, self.threshold)
##
# Simple blur filter.
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
)
##
# Simple contour filter.
class CONTOUR(BuiltinFilter):
name = "Contour"
filterargs = (3, 3), 1, 255, (
-1, -1, -1,
-1, 8, -1,
-1, -1, -1
)
##
# Simple detail filter.
class DETAIL(BuiltinFilter):
name = "Detail"
filterargs = (3, 3), 6, 0, (
0, -1, 0,
-1, 10, -1,
0, -1, 0
)
##
# Simple edge enhancement filter.
class EDGE_ENHANCE(BuiltinFilter):
name = "Edge-enhance"
filterargs = (3, 3), 2, 0, (
-1, -1, -1,
-1, 10, -1,
-1, -1, -1
)
##
# Simple stronger edge enhancement filter.
class EDGE_ENHANCE_MORE(BuiltinFilter):
name = "Edge-enhance More"
filterargs = (3, 3), 1, 0, (
-1, -1, -1,
-1, 9, -1,
-1, -1, -1
)
##
# Simple embossing filter.
class EMBOSS(BuiltinFilter):
name = "Emboss"
filterargs = (3, 3), 1, 128, (
-1, 0, 0,
0, 1, 0,
0, 0, 0
)
##
# Simple edge-finding filter.
class FIND_EDGES(BuiltinFilter):
name = "Find Edges"
filterargs = (3, 3), 1, 0, (
-1, -1, -1,
-1, 8, -1,
-1, -1, -1
)
##
# Simple smoothing filter.
class SMOOTH(BuiltinFilter):
name = "Smooth"
filterargs = (3, 3), 13, 0, (
1, 1, 1,
1, 5, 1,
1, 1, 1
)
##
# Simple stronger smoothing filter.
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
)
##
# Simple sharpening filter.
class SHARPEN(BuiltinFilter):
name = "Sharpen"
filterargs = (3, 3), 16, 0, (
-2, -2, -2,
-2, 32, -2,
-2, -2, -2
)
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