Source code for PIL.ImageStat

#
# The Python Imaging Library.
# $Id$
#
# global image statistics
#
# History:
# 1996-04-05 fl   Created
# 1997-05-21 fl   Added mask; added rms, var, stddev attributes
# 1997-08-05 fl   Added median
# 1998-07-05 hk   Fixed integer overflow error
#
# Notes:
# This class shows how to implement delayed evaluation of attributes.
# To get a certain value, simply access the corresponding attribute.
# The __getattr__ dispatcher takes care of the rest.
#
# Copyright (c) Secret Labs AB 1997.
# Copyright (c) Fredrik Lundh 1996-97.
#
# See the README file for information on usage and redistribution.
#

from PIL import Image
import operator, math
from functools import reduce

##
# The <b>ImageStat</b> module calculates global statistics for an
# image, or a region of an image.
##

##
# Calculate statistics for the given image.  If a mask is included,
# only the regions covered by that mask are included in the
# statistics.

[docs]class Stat: "Get image or feature statistics" ## # Create a statistics object. # # @def __init__(image, mask=None) # @param image A PIL image, or a precalculate histogram. # @param mask An optional mask. def __init__(self, image_or_list, mask = None): try: if mask: self.h = image_or_list.histogram(mask) else: self.h = image_or_list.histogram() except AttributeError: self.h = image_or_list # assume it to be a histogram list if not isinstance(self.h, list): raise TypeError("first argument must be image or list") self.bands = list(range(len(self.h) // 256)) def __getattr__(self, id): "Calculate missing attribute" if id[:4] == "_get": raise AttributeError(id) # calculate missing attribute v = getattr(self, "_get" + id)() setattr(self, id, v) return v def _getextrema(self): "Get min/max values for each band in the image" def minmax(histogram): n = 255 x = 0 for i in range(256): if histogram[i]: n = min(n, i) x = max(x, i) return n, x # returns (255, 0) if there's no data in the histogram v = [] for i in range(0, len(self.h), 256): v.append(minmax(self.h[i:])) return v def _getcount(self): "Get total number of pixels in each layer" v = [] for i in range(0, len(self.h), 256): v.append(reduce(operator.add, self.h[i:i+256])) return v def _getsum(self): "Get sum of all pixels in each layer" v = [] for i in range(0, len(self.h), 256): sum = 0.0 for j in range(256): sum = sum + j * self.h[i+j] v.append(sum) return v def _getsum2(self): "Get squared sum of all pixels in each layer" v = [] for i in range(0, len(self.h), 256): sum2 = 0.0 for j in range(256): sum2 = sum2 + (j ** 2) * float(self.h[i+j]) v.append(sum2) return v def _getmean(self): "Get average pixel level for each layer" v = [] for i in self.bands: v.append(self.sum[i] / self.count[i]) return v def _getmedian(self): "Get median pixel level for each layer" v = [] for i in self.bands: s = 0 l = self.count[i]//2 b = i * 256 for j in range(256): s = s + self.h[b+j] if s > l: break v.append(j) return v def _getrms(self): "Get RMS for each layer" v = [] for i in self.bands: v.append(math.sqrt(self.sum2[i] / self.count[i])) return v def _getvar(self): "Get variance for each layer" v = [] for i in self.bands: n = self.count[i] v.append((self.sum2[i]-(self.sum[i]**2.0)/n)/n) return v def _getstddev(self): "Get standard deviation for each layer" v = [] for i in self.bands: v.append(math.sqrt(self.var[i])) return v
Global = Stat # compatibility