# # 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. # from functools import reduce 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. #

# 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 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 = radius 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 = radius 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 )