common/img.py

   1 #!/usr/bin/env python
   2 # -*- coding: UTF8 -*-
   3 #
   4 #   Copyright (C) 2006-2007 Antonio Ingargiola <tritemio@gmail.com>
   5 #
   6 #   This file is part of Image Analyzer.
   7 #
   8 #   Image Analyzer is free software; you can redistribute it and/or modify
   9 #   it under the terms of the GNU General Public License as published by
  10 #   the Free Software Foundation; either version 2 of the License, or
  11 #   (at your option) any later version.
  12
  13 import sys
  14 from PIL import Image
  15 from numpy import fromstring, resize, array, around, arange, zeros
  16
  17 class WrongImageFormat(Exception):
  18     """ Exception for image format not known. """
  19     def __init__(self, value):
  20         self.value = value
  21     def __str__(self):
  22         return repr(self.value)
  23
  24 def image2array(image):
  25     """ Converts an image object (PIL) to an array (NumPy). """
  26     if image.mode == "RGB":
  27         dimensions = (image.size[1], image.size[0], 3)
  28         type = 'uint8'
  29     elif image.mode == "RGBA":
  30         dimensions = (image.size[1], image.size[0], 4)
  31         type = 'uint8'
  32     elif image.mode == "L":
  33         dimensions = (image.size[1], image.size[0])
  34         type = 'uint8'
  35     elif image.mode == "I;16":
  36         dimensions = (image.size[1], image.size[0])
  37         type = 'uint16'
  38     else:
  39         raise WrongImageFormat, "Image type "+image.mode+" unknown."
  40
  41     image_string = image.tostring()
  42     image_array = fromstring(image_string, type)
  43     return resize(image_array, dimensions)
  44
  45 def image2array2(image):
  46     """Converts an image object (PIL) into an array (NumPy).
  47     Seems slightly slower than image2array()."""
  48     if image.mode == "RGB":
  49         dimensions = (image.size[1], image.size[0], 3)
  50         type = 'UInt8'
  51     elif image.mode == "RGBA":
  52         dimensions = (image.size[1], image.size[0], 4)
  53         type = 'UInt8'
  54     elif image.mode == "L":
  55         dimensions = (image.size[1], image.size[0])
  56         type = 'UInt8'
  57     elif image.mode == "I;16":
  58         dimensions = (image.size[1], image.size[0])
  59         type = 'UInt16'
  60     else:
  61         raise WrongImageFormat, "Image type "+image.mode+" unknown."
  62
  63     image_array = array(image.getdata(), dtype='UInt16')
  64     return resize(image_array, dimensions)
  65
  66 def histogram3(image, nbit):
  67     """
  68     It is used instead of image.histogram() because the latter does not work
  69     with high dynamic images (for example 14 bit).
  70
  71     Takes as parameters a PIL image and the number of bit and returns an array
  72     2**nbit length containing the image histogram.
  73
  74     This function has been written by Fredrik Lundh, in the article:
  75
  76         http://effbot.org/zone/image-histogram-optimization.htm
  77
  78     This code snipped is public domain as stated at:
  79
  80         http://effbot.org/zone/copyright.htm
  81     """
  82
  83     # wait, use a list, but get rid of that getpixel call
  84     result = [0] * 2**nbit
  85     for v in image.getdata():
  86         result[v] = result[v] + 1
  87     return result
  88
  89 def histogramfloat(farray, nbit=10, rescale=True):
  90     """
  91     Calculates (quite) efficiently the histogram of a float array.
  92
  93     Returns two arrays of the same length:
  94      - an equally spaced array of (quantized) values
  95      - the occurrence of each value
  96
  97     The optional 'nbit' parameter set the quantization number of bit.
  98     The optional 'rescale' flag can inhibit data rescaling. This is useful if
  99     your data comes from a source with a known number of bit (for example an
 100     image converted to array). In this case you must set the correct 'nbit'
 101     and assure that the 'farray' data is contained in the range 0..(2^nbit)-1
 102     (extreme included).
 103     """
 104
 105     if rescale:
 106         m = farray.max()
 107     else:
 108         m = (2.**nbit) - 1
 109
 110     rarray = around(farray*((2.**nbit)-1)/m).astype(int)
 111     values = arange(2**nbit)*m/(2.**nbit-1)
 112
 113     hist_data = zeros(2**nbit)
 114     for v in rarray.ravel():
 115         hist_data[v] += 1
 116     return values, hist_data
 117
 118 def speed_test():
 119     files = sys.argv[1:]
 120     if len(files) < 1:
 121         files = ['test-img.tif']
 122
 123     for file_name in files:
 124         try:
 125             image = Image.open(file_name)
 126         except IOError:
 127             print "\n File '"+file_name+"' cannot be opened.\n"
 128             sys.exit()
 129
 130         profile.run('ia = image2array(image)', 'ia')
 131         profile.run('ia2 = image2array2(image)', 'ia2')
 132
 133 if __name__ == "__main__":
 134     from pylab import *
 135     from scipy import lena
 136     import profile
 137
 138     a = lena()
 139     v, h = histogramfloat(a, nbit=8, rescale=False)
 140     step = 1
 141     print v[0], v[-1]
 142     print v[20:30]
 143     print h[20:30]
 144
 145     plot(v, h, 'ro')
 146     bar(v,h, width=step, bottom=0.01, edgecolor='blue')
 147     grid(True)
 148     show()
 149
 150
 151