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| # | |
| # 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 functools | |
| import math | |
| import operator | |
| 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): | |
| msg = "first argument must be image or list" | |
| raise TypeError(msg) | |
| 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(functools.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): | |
| layer_sum = 0.0 | |
| for j in range(256): | |
| layer_sum += j * self.h[i + j] | |
| v.append(layer_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 | |
| half = self.count[i] // 2 | |
| b = i * 256 | |
| for j in range(256): | |
| s = s + self.h[b + j] | |
| if s > half: | |
| 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 | |