# # 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. # import functools import operator import re from . import ExifTags, Image, ImagePalette # # 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 isinstance(color, str): from . 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 msg = "mode P support coming soon" raise NotImplementedError(msg) elif image.mode in ("L", "RGB"): if image.mode == "RGB" and len(lut) == 256: lut = lut + lut + lut return image.point(lut) else: msg = f"not supported for mode {image.mode}" raise OSError(msg) # # actions def autocontrast(image, cutoff=0, ignore=None, mask=None, preserve_tone=False): """ Maximize (normalize) image contrast. This function calculates a histogram of the input image (or mask region), 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: The percent to cut off from the histogram on the low and high ends. Either a tuple of (low, high), or a single number for both. :param ignore: The background pixel value (use None for no background). :param mask: Histogram used in contrast operation is computed using pixels within the mask. If no mask is given the entire image is used for histogram computation. :param preserve_tone: Preserve image tone in Photoshop-like style autocontrast. .. versionadded:: 8.2.0 :return: An image. """ if preserve_tone: histogram = image.convert("L").histogram(mask) else: histogram = image.histogram(mask) 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 if not isinstance(cutoff, tuple): cutoff = (cutoff, cutoff) # 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[0] // 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: