/usr/lib/python3/dist-packages/PIL/ImageStat.py is in python3-pil 2.6.1-2+deb8u3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 | #
# 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.
#
import math
import operator
from functools import reduce
class Stat:
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 += 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 += (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
|