Mercurial > ift6266
annotate data_generation/transformations/contrast.py @ 204:e1f5f66dd7dd
Changé le coût de reconstruction pour stabilité numérique, en ajoutant une petite constante dans le log.
author | fsavard |
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date | Thu, 04 Mar 2010 08:18:42 -0500 |
parents | 1f5937e9e530 |
children |
rev | line source |
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27
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Added a contrast.py script difining the Contrast transformation class
Xavier Glorot <glorotxa@iro.umontreal.ca>
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1 #!/usr/bin/python |
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2 # coding: utf-8 |
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3 |
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4 ''' |
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5 Simple implementation of random contrast. This always switch half the time the polarity. |
31
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6 then it decides of a random contrast dependant of the complexity, the mean of the maximum and minimum |
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7 pixel value stays 0 (to avoid import bias change between exemples). |
27
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8 |
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9 Author: Xavier Glorot |
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10 ''' |
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11 |
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12 import numpy as N |
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13 import copy |
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14 |
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15 |
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16 class Contrast(): |
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17 def __init__(self,complexity = 1): |
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18 #---------- private attributes |
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19 self.__nx__ = 32 #xdim of the images |
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20 self.__ny__ = 32 #ydim of the images |
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21 self.__Pinvert__ = 0.5 #probability to switch polarity |
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22 self.__mincontrast__ = 0.15 |
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23 self.__resolution__ = 256 |
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24 self.__rangecontrastres__ = self.__resolution__ - N.int(self.__mincontrast__*self.__resolution__) |
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25 #------------------------------------------------ |
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26 |
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27 #---------- generation parameters |
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28 self.regenerate_parameters(complexity) |
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29 #------------------------------------------------ |
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30 |
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31 def _get_current_parameters(self): |
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32 return [self.invert,self.contrast] |
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33 |
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34 def get_settings_names(self): |
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35 return ['invert','contrast'] |
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36 |
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37 def regenerate_parameters(self, complexity): |
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38 self.invert = (N.random.uniform() < self.__Pinvert__) |
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39 self.contrast = self.__resolution__ - N.random.randint(1 + self.__rangecontrastres__ * complexity) |
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40 return self._get_current_parameters() |
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41 |
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42 def transform_1_image(self,image): #the real transformation method |
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43 maxi = image.max() |
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44 mini = image.min() |
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45 if self.invert: |
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46 newimage = 1 - (self.__resolution__- self.contrast) / (2 * float(self.__resolution__)) -\ |
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47 (image - mini) / float(maxi - mini) * self.contrast / float(self.__resolution__) |
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48 else: |
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49 newimage = (self.__resolution__- self.contrast) / (2 * float(self.__resolution__)) +\ |
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50 (image - mini) / float(maxi - mini) * self.contrast / float(self.__resolution__) |
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51 if image.dtype == 'uint8': |
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52 return N.asarray(newimage*255,dtype='uint8') |
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53 else: |
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54 return N.asarray(newimage,dtype=image.dtype) |
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55 |
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56 def transform_image(self,image): #handling different format |
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57 if image.shape == (self.__nx__,self.__ny__): |
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58 return self.transform_1_image(image) |
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59 if image.ndim == 3: |
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60 newimage = copy.copy(image) |
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61 for i in range(image.shape[0]): |
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62 newimage[i,:,:] = self.transform_1_image(image[i,:,:]) |
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63 return newimage |
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64 if image.ndim == 2 and image.shape != (self.__nx__,self.__ny__): |
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65 newimage = N.reshape(image,(image.shape[0],self.__nx__,self.__ny__)) |
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66 for i in range(image.shape[0]): |
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67 newimage[i,:,:] = self.transform_1_image(newimage[i,:,:]) |
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68 return N.reshape(newimage,image.shape) |
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69 if image.ndim == 1: |
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70 newimage = N.reshape(image,(self.__nx__,self.__ny__)) |
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71 newimage = self.transform_1_image(newimage) |
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72 return N.reshape(newimage,image.shape) |
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73 assert False #should never go there |
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74 |
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75 |
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76 |
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77 |
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78 #test on NIST (you need pylearn and access to NIST to do that) |
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79 |
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80 if __name__ == '__main__': |
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81 |
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82 from pylearn.io import filetensor as ft |
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83 import copy |
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84 import pygame |
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85 import time |
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86 datapath = '/data/lisa/data/nist/by_class/' |
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87 f = open(datapath+'digits/digits_train_data.ft') |
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88 d = ft.read(f) |
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89 |
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90 pygame.surfarray.use_arraytype('numpy') |
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91 |
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92 pygame.display.init() |
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93 screen = pygame.display.set_mode((8*2*32,8*32),0,8) |
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94 anglcolorpalette=[(x,x,x) for x in xrange(0,256)] |
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95 screen.set_palette(anglcolorpalette) |
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96 |
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97 MyContrast = Contrast() |
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98 |
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99 debut=time.time() |
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100 MyContrast.transform_image(d) |
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101 fin=time.time() |
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102 print '------------------------------------------------' |
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103 print d.shape[0],' images transformed in :', fin-debut, ' seconds' |
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104 print '------------------------------------------------' |
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105 print (fin-debut)/d.shape[0]*1000000,' microseconds per image' |
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106 print '------------------------------------------------' |
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107 print MyContrast.get_settings_names() |
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108 print MyContrast._get_current_parameters() |
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109 print MyContrast.regenerate_parameters(0) |
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110 print MyContrast.regenerate_parameters(0.5) |
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111 print MyContrast.regenerate_parameters(1) |
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112 for i in range(10000): |
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113 a=d[i,:] |
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114 b=N.asarray(N.reshape(a,(32,32))).T |
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115 |
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116 new=pygame.surfarray.make_surface(b) |
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117 new=pygame.transform.scale2x(new) |
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118 new=pygame.transform.scale2x(new) |
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119 new=pygame.transform.scale2x(new) |
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120 new.set_palette(anglcolorpalette) |
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121 screen.blit(new,(0,0)) |
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122 |
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123 print MyContrast.get_settings_names(), MyContrast.regenerate_parameters(1) |
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124 c=MyContrast.transform_image(a) |
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125 b=N.asarray(N.reshape(c,(32,32))).T |
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126 |
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127 new=pygame.surfarray.make_surface(b) |
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128 new=pygame.transform.scale2x(new) |
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129 new=pygame.transform.scale2x(new) |
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130 new=pygame.transform.scale2x(new) |
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131 new.set_palette(anglcolorpalette) |
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132 screen.blit(new,(8*32,0)) |
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133 |
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134 pygame.display.update() |
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135 raw_input('Press Enter') |
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136 |
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137 pygame.display.quit() |