Mercurial > ift6266

annotate transformations/contrast.py @ 41:fdb0e0870fb4

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Beaucoup de modifications à pipeline.py pour généraliser et un début de visualisation, et créé un wrapper (run_pipeline.py) pour appeler avec GIMP. - Modifications à pipeline.py - Wrappé la boucle du pipeline dans une classe - Isolé le problème de itérer sur les batches et les complexités dans des itérateurs - Permet d'avoir des ordres compliqués de batch (plusieurs sources), de complexités - Maintenant regenerate_parameters() est appelé pour chaque image. - Command line arguments avec getopt(). On pourra rajouter des options ainsi. - run_pipeline.py - Le but est de permettre de passer des arguments. Pas facile (pas trouvé comment de façon simple) avec la command line pour appeler GIMP en mode batch. C'est un hack ici. - Le but ultime est de permettre de lancer les jobs sur les clusters avec dbidispatch en précisant les options (diff. pour chaque job) sur la ligne de commande.
author fsavard
date Wed, 03 Feb 2010 17:08:27 -0500
parents 7ef8aac2cdb5
children
rev   line source
27
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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
7ef8aac2cdb5 comment change and useless import removed for contrast.py
Xavier Glorot <glorotxa@iro.umontreal.ca>
parents: 27
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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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parents:
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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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parents:
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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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parents:
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126
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127 new=pygame.surfarray.make_surface(b)
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parents:
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128 new=pygame.transform.scale2x(new)
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parents:
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129 new=pygame.transform.scale2x(new)
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parents:
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130 new=pygame.transform.scale2x(new)
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parents:
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131 new.set_palette(anglcolorpalette)
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parents:
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132 screen.blit(new,(8*32,0))
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parents:
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133
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parents:
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134 pygame.display.update()
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Xavier Glorot <glorotxa@iro.umontreal.ca>
parents:
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135 raw_input('Press Enter')
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parents:
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136
0b9350998dbe Added a contrast.py script difining the Contrast transformation class
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parents:
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137 pygame.display.quit()