# # 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 )