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Diffstat (limited to 'lib/Python/Lib/PIL/ImageOps.py')
| -rw-r--r-- | lib/Python/Lib/PIL/ImageOps.py | 462 |
1 files changed, 462 insertions, 0 deletions
diff --git a/lib/Python/Lib/PIL/ImageOps.py b/lib/Python/Lib/PIL/ImageOps.py new file mode 100644 index 000000000..a1706875d --- /dev/null +++ b/lib/Python/Lib/PIL/ImageOps.py @@ -0,0 +1,462 @@ +# +# The Python Imaging Library. +# $Id$ +# +# standard image operations +# +# History: +# 2001-10-20 fl Created +# 2001-10-23 fl Added autocontrast operator +# 2001-12-18 fl Added Kevin's fit operator +# 2004-03-14 fl Fixed potential division by zero in equalize +# 2005-05-05 fl Fixed equalize for low number of values +# +# Copyright (c) 2001-2004 by Secret Labs AB +# Copyright (c) 2001-2004 by Fredrik Lundh +# +# See the README file for information on usage and redistribution. +# + +from PIL import Image +from PIL._util import isStringType +import operator +from functools import reduce + + +# +# helpers + +def _border(border): + if isinstance(border, tuple): + if len(border) == 2: + left, top = right, bottom = border + elif len(border) == 4: + left, top, right, bottom = border + else: + left = top = right = bottom = border + return left, top, right, bottom + + +def _color(color, mode): + if isStringType(color): + from PIL import ImageColor + color = ImageColor.getcolor(color, mode) + return color + + +def _lut(image, lut): + if image.mode == "P": + # FIXME: apply to lookup table, not image data + raise NotImplementedError("mode P support coming soon") + elif image.mode in ("L", "RGB"): + if image.mode == "RGB" and len(lut) == 256: + lut = lut + lut + lut + return image.point(lut) + else: + raise IOError("not supported for this image mode") + +# +# actions + + +def autocontrast(image, cutoff=0, ignore=None): + """ + Maximize (normalize) image contrast. This function calculates a + histogram of the input image, removes **cutoff** percent of the + lightest and darkest pixels from the histogram, and remaps the image + so that the darkest pixel becomes black (0), and the lightest + becomes white (255). + + :param image: The image to process. + :param cutoff: How many percent to cut off from the histogram. + :param ignore: The background pixel value (use None for no background). + :return: An image. + """ + histogram = image.histogram() + lut = [] + for layer in range(0, len(histogram), 256): + h = histogram[layer:layer+256] + if ignore is not None: + # get rid of outliers + try: + h[ignore] = 0 + except TypeError: + # assume sequence + for ix in ignore: + h[ix] = 0 + if cutoff: + # cut off pixels from both ends of the histogram + # get number of pixels + n = 0 + for ix in range(256): + n = n + h[ix] + # remove cutoff% pixels from the low end + cut = n * cutoff // 100 + for lo in range(256): + if cut > h[lo]: + cut = cut - h[lo] + h[lo] = 0 + else: + h[lo] -= cut + cut = 0 + if cut <= 0: + break + # remove cutoff% samples from the hi end + cut = n * cutoff // 100 + for hi in range(255, -1, -1): + if cut > h[hi]: + cut = cut - h[hi] + h[hi] = 0 + else: + h[hi] -= cut + cut = 0 + if cut <= 0: + break + # find lowest/highest samples after preprocessing + for lo in range(256): + if h[lo]: + break + for hi in range(255, -1, -1): + if h[hi]: + break + if hi <= lo: + # don't bother + lut.extend(list(range(256))) + else: + scale = 255.0 / (hi - lo) + offset = -lo * scale + for ix in range(256): + ix = int(ix * scale + offset) + if ix < 0: + ix = 0 + elif ix > 255: + ix = 255 + lut.append(ix) + return _lut(image, lut) + + +def colorize(image, black, white): + """ + Colorize grayscale image. The **black** and **white** + arguments should be RGB tuples; this function calculates a color + wedge mapping all black pixels in the source image to the first + color, and all white pixels to the second color. + + :param image: The image to colorize. + :param black: The color to use for black input pixels. + :param white: The color to use for white input pixels. + :return: An image. + """ + assert image.mode == "L" + black = _color(black, "RGB") + white = _color(white, "RGB") + red = [] + green = [] + blue = [] + for i in range(256): + red.append(black[0]+i*(white[0]-black[0])//255) + green.append(black[1]+i*(white[1]-black[1])//255) + blue.append(black[2]+i*(white[2]-black[2])//255) + image = image.convert("RGB") + return _lut(image, red + green + blue) + + +def crop(image, border=0): + """ + Remove border from image. The same amount of pixels are removed + from all four sides. This function works on all image modes. + + .. seealso:: :py:meth:`~PIL.Image.Image.crop` + + :param image: The image to crop. + :param border: The number of pixels to remove. + :return: An image. + """ + left, top, right, bottom = _border(border) + return image.crop( + (left, top, image.size[0]-right, image.size[1]-bottom) + ) + + +def deform(image, deformer, resample=Image.BILINEAR): + """ + Deform the image. + + :param image: The image to deform. + :param deformer: A deformer object. Any object that implements a + **getmesh** method can be used. + :param resample: What resampling filter to use. + :return: An image. + """ + return image.transform( + image.size, Image.MESH, deformer.getmesh(image), resample + ) + + +def equalize(image, mask=None): + """ + Equalize the image histogram. This function applies a non-linear + mapping to the input image, in order to create a uniform + distribution of grayscale values in the output image. + + :param image: The image to equalize. + :param mask: An optional mask. If given, only the pixels selected by + the mask are included in the analysis. + :return: An image. + """ + if image.mode == "P": + image = image.convert("RGB") + h = image.histogram(mask) + lut = [] + for b in range(0, len(h), 256): + histo = [_f for _f in h[b:b+256] if _f] + if len(histo) <= 1: + lut.extend(list(range(256))) + else: + step = (reduce(operator.add, histo) - histo[-1]) // 255 + if not step: + lut.extend(list(range(256))) + else: + n = step // 2 + for i in range(256): + lut.append(n // step) + n = n + h[i+b] + return _lut(image, lut) + + +def expand(image, border=0, fill=0): + """ + Add border to the image + + :param image: The image to expand. + :param border: Border width, in pixels. + :param fill: Pixel fill value (a color value). Default is 0 (black). + :return: An image. + """ + "Add border to image" + left, top, right, bottom = _border(border) + width = left + image.size[0] + right + height = top + image.size[1] + bottom + out = Image.new(image.mode, (width, height), _color(fill, image.mode)) + out.paste(image, (left, top)) + return out + + +def fit(image, size, method=Image.NEAREST, bleed=0.0, centering=(0.5, 0.5)): + """ + Returns a sized and cropped version of the image, cropped to the + requested aspect ratio and size. + + This function was contributed by Kevin Cazabon. + + :param size: The requested output size in pixels, given as a + (width, height) tuple. + :param method: What resampling method to use. Default is + :py:attr:`PIL.Image.NEAREST`. + :param bleed: Remove a border around the outside of the image (from all + four edges. The value is a decimal percentage (use 0.01 for + one percent). The default value is 0 (no border). + :param centering: Control the cropping position. Use (0.5, 0.5) for + center cropping (e.g. if cropping the width, take 50% off + of the left side, and therefore 50% off the right side). + (0.0, 0.0) will crop from the top left corner (i.e. if + cropping the width, take all of the crop off of the right + side, and if cropping the height, take all of it off the + bottom). (1.0, 0.0) will crop from the bottom left + corner, etc. (i.e. if cropping the width, take all of the + crop off the left side, and if cropping the height take + none from the top, and therefore all off the bottom). + :return: An image. + """ + + # by Kevin Cazabon, Feb 17/2000 + # kevin@cazabon.com + # http://www.cazabon.com + + # ensure inputs are valid + if not isinstance(centering, list): + centering = [centering[0], centering[1]] + + if centering[0] > 1.0 or centering[0] < 0.0: + centering[0] = 0.50 + if centering[1] > 1.0 or centering[1] < 0.0: + centering[1] = 0.50 + + if bleed > 0.49999 or bleed < 0.0: + bleed = 0.0 + + # calculate the area to use for resizing and cropping, subtracting + # the 'bleed' around the edges + + # number of pixels to trim off on Top and Bottom, Left and Right + bleedPixels = ( + int((float(bleed) * float(image.size[0])) + 0.5), + int((float(bleed) * float(image.size[1])) + 0.5) + ) + + liveArea = (0, 0, image.size[0], image.size[1]) + if bleed > 0.0: + liveArea = ( + bleedPixels[0], bleedPixels[1], image.size[0] - bleedPixels[0] - 1, + image.size[1] - bleedPixels[1] - 1 + ) + + liveSize = (liveArea[2] - liveArea[0], liveArea[3] - liveArea[1]) + + # calculate the aspect ratio of the liveArea + liveAreaAspectRatio = float(liveSize[0])/float(liveSize[1]) + + # calculate the aspect ratio of the output image + aspectRatio = float(size[0]) / float(size[1]) + + # figure out if the sides or top/bottom will be cropped off + if liveAreaAspectRatio >= aspectRatio: + # liveArea is wider than what's needed, crop the sides + cropWidth = int((aspectRatio * float(liveSize[1])) + 0.5) + cropHeight = liveSize[1] + else: + # liveArea is taller than what's needed, crop the top and bottom + cropWidth = liveSize[0] + cropHeight = int((float(liveSize[0])/aspectRatio) + 0.5) + + # make the crop + leftSide = int(liveArea[0] + (float(liveSize[0]-cropWidth) * centering[0])) + if leftSide < 0: + leftSide = 0 + topSide = int(liveArea[1] + (float(liveSize[1]-cropHeight) * centering[1])) + if topSide < 0: + topSide = 0 + + out = image.crop( + (leftSide, topSide, leftSide + cropWidth, topSide + cropHeight) + ) + + # resize the image and return it + return out.resize(size, method) + + +def flip(image): + """ + Flip the image vertically (top to bottom). + + :param image: The image to flip. + :return: An image. + """ + return image.transpose(Image.FLIP_TOP_BOTTOM) + + +def grayscale(image): + """ + Convert the image to grayscale. + + :param image: The image to convert. + :return: An image. + """ + return image.convert("L") + + +def invert(image): + """ + Invert (negate) the image. + + :param image: The image to invert. + :return: An image. + """ + lut = [] + for i in range(256): + lut.append(255-i) + return _lut(image, lut) + + +def mirror(image): + """ + Flip image horizontally (left to right). + + :param image: The image to mirror. + :return: An image. + """ + return image.transpose(Image.FLIP_LEFT_RIGHT) + + +def posterize(image, bits): + """ + Reduce the number of bits for each color channel. + + :param image: The image to posterize. + :param bits: The number of bits to keep for each channel (1-8). + :return: An image. + """ + lut = [] + mask = ~(2**(8-bits)-1) + for i in range(256): + lut.append(i & mask) + return _lut(image, lut) + + +def solarize(image, threshold=128): + """ + Invert all pixel values above a threshold. + + :param image: The image to solarize. + :param threshold: All pixels above this greyscale level are inverted. + :return: An image. + """ + lut = [] + for i in range(256): + if i < threshold: + lut.append(i) + else: + lut.append(255-i) + return _lut(image, lut) + + +# -------------------------------------------------------------------- +# PIL USM components, from Kevin Cazabon. + +def gaussian_blur(im, radius=None): + """ PIL_usm.gblur(im, [radius])""" + + if radius is None: + radius = 5.0 + + im.load() + + return im.im.gaussian_blur(radius) + +gblur = gaussian_blur + + +def unsharp_mask(im, radius=None, percent=None, threshold=None): + """ PIL_usm.usm(im, [radius, percent, threshold])""" + + if radius is None: + radius = 5.0 + if percent is None: + percent = 150 + if threshold is None: + threshold = 3 + + im.load() + + return im.im.unsharp_mask(radius, percent, threshold) + +usm = unsharp_mask + + +def box_blur(image, radius): + """ + Blur 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 image: The image to blur. + :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. + :return: An image. + """ + image.load() + + return image._new(image.im.box_blur(radius)) |