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#
# 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: