mirror of
				https://github.com/python-pillow/Pillow.git
				synced 2025-10-31 16:07:30 +03:00 
			
		
		
		
	
		
			
				
	
	
		
			148 lines
		
	
	
		
			3.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			148 lines
		
	
	
		
			3.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| #
 | |
| # 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
 | |
| import functools
 | |
| 
 | |
| 
 | |
| class Stat(object):
 | |
| 
 | |
|     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(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):
 | |
|             layerSum = 0.0
 | |
|             for j in range(256):
 | |
|                 layerSum += j * self.h[i + j]
 | |
|             v.append(layerSum)
 | |
|         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
 |