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annotate data_generation/transformations/thick.py @ 266:1e4e60ddadb1

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Merge. Ah, et dans le dernier commit, j'avais oublié de mentionner que j'ai ajouté du code pour gérer l'isolation de différents clones pour rouler des expériences et modifier le code en même temps.
author fsavard
date Fri, 19 Mar 2010 10:56:16 -0400
parents 1f5937e9e530
children
rev   line source
11
dbc806d025a2 Added a thick.py script defining a Thick class transforming randomly the thickness of the characters
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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 thickness deformation using morphological
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6 operation of scipy.
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7 Only one morphological operation applied (dilation or erosion), the kernel is random
14
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8 out of a list of 12 symmetric kernels. (only 5 to be chosen for erosion because it can
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9 hurt the recognizability of the charater and 12 for dilation).
11
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10
dbc806d025a2 Added a thick.py script defining a Thick class transforming randomly the thickness of the characters
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11 Author: Xavier Glorot
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12
dbc806d025a2 Added a thick.py script defining a Thick class transforming randomly the thickness of the characters
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13 '''
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14
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15 import scipy.ndimage.morphology
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16 import numpy as N
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17
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18
dbc806d025a2 Added a thick.py script defining a Thick class transforming randomly the thickness of the characters
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19 class Thick():
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20 def __init__(self,complexity = 1):
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21 #---------- private attributes
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22 self.__nx__ = 32 #xdim of the images
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23 self.__ny__ = 32 #ydim of the images
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24 self.__erodemax__ = 5 #nb of index max of erode structuring elements
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25 self.__dilatemax__ = 9 #nb of index max of dilation structuring elements
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26 self.__structuring_elements__ = [N.asarray([[1,1]]),N.asarray([[1],[1]]),\
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27 N.asarray([[1,1],[1,1]]),N.asarray([[0,1,0],[1,1,1],[0,1,0]]),\
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28 N.asarray([[1,1,1],[1,1,1]]),N.asarray([[1,1],[1,1],[1,1]]),\
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29 N.asarray([[1,1,1],[1,1,1],[1,1,1]]),\
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30 N.asarray([[1,1,1,1],[1,1,1,1],[1,1,1,1]]),\
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31 N.asarray([[1,1,1],[1,1,1],[1,1,1],[1,1,1]]),\
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32 N.asarray([[0,0,1,0,0],[0,1,1,1,0],[1,1,1,1,1],[0,1,1,1,0],[0,0,1,0,0]]),\
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33 N.asarray([[1,1,1,1],[1,1,1,1]]),N.asarray([[1,1],[1,1],[1,1],[1,1]])]
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34 #------------------------------------------------
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35
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36 #---------- generation parameters
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37 self.regenerate_parameters(complexity)
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38 #------------------------------------------------
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39
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40 def _get_current_parameters(self):
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41 return [self.thick_param]
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42
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43 def get_settings_names(self):
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44 return ['thick_param']
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45
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46 def regenerate_parameters(self, complexity):
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47 self.erodenb = N.ceil(complexity * self.__erodemax__)
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48 self.dilatenb = N.ceil(complexity * self.__dilatemax__)
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49 self.Perode = self.erodenb / (self.dilatenb + self.erodenb + 1.0)
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50 self.Pdilate = self.dilatenb / (self.dilatenb + self.erodenb + 1.0)
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51 assert (self.Perode + self.Pdilate <= 1) & (self.Perode + self.Pdilate >= 0)
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52 assert (complexity >= 0) & (complexity <= 1)
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53 P = N.random.uniform()
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54 if P>1-(self.Pdilate+self.Perode):
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55 if P>1-(self.Pdilate+self.Perode)+self.Perode:
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56 self.meth = 1
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57 self.nb=N.random.randint(self.dilatenb)
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58 else:
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59 self.meth = -1
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60 self.nb=N.random.randint(self.erodenb)
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61 else:
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62 self.meth = 0
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63 self.nb = -1
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64 self.thick_param = self.meth*self.nb
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65 return self._get_current_parameters()
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66
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67 def transform_1_image(self,image): #the real transformation method
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68 if self.meth!=0:
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69 maxi = float(N.max(image))
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70 mini = float(N.min(image))
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71
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72 imagenorm=image/maxi
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73
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74 if self.meth==1:
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75 trans=scipy.ndimage.morphology.grey_dilation\
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76 (imagenorm,size=self.__structuring_elements__[self.nb].shape,structure=self.__structuring_elements__[self.nb])
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77 else:
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78 trans=scipy.ndimage.morphology.grey_erosion\
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79 (imagenorm,size=self.__structuring_elements__[self.nb].shape,structure=self.__structuring_elements__[self.nb])
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80
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81 #------renormalizing
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82 maxit = N.max(trans)
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83 minit = N.min(trans)
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84 trans= N.asarray((trans - (minit+mini)) / (maxit - (minit+mini)) * maxi,dtype=image.dtype)
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85 #--------
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86 return trans
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87 else:
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88 return image
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89
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90 def transform_image(self,image): #handling different format
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91 if image.shape == (self.__nx__,self.__ny__):
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92 return self.transform_1_image(image)
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93 if image.ndim == 3:
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94 newimage = copy.copy(image)
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95 for i in range(image.shape[0]):
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96 newimage[i,:,:] = self.transform_1_image(image[i,:,:])
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97 return newimage
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98 if image.ndim == 2 and image.shape != (self.__nx__,self.__ny__):
11
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99 newimage = N.reshape(image,(image.shape[0],self.__nx__,self.__ny__))
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100 for i in range(image.shape[0]):
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101 newimage[i,:,:] = self.transform_1_image(newimage[i,:,:])
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102 return N.reshape(newimage,image.shape)
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103 if image.ndim == 1:
11
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104 newimage = N.reshape(image,(self.__nx__,self.__ny__))
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105 newimage = self.transform_1_image(newimage)
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106 return N.reshape(newimage,image.shape)
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107 assert False #should never go there
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108
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109
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110
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111
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112 #test on NIST (you need pylearn and access to NIST to do that)
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113
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114 if __name__ == '__main__':
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115
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116 from pylearn.io import filetensor as ft
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117 import copy
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118 import pygame
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119 import time
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120 datapath = '/data/lisa/data/nist/by_class/'
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121 f = open(datapath+'digits/digits_train_data.ft')
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122 d = ft.read(f)
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123
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124 pygame.surfarray.use_arraytype('numpy')
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125
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126 pygame.display.init()
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127 screen = pygame.display.set_mode((8*4*32,8*32),0,8)
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128 anglcolorpalette=[(x,x,x) for x in xrange(0,256)]
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129 screen.set_palette(anglcolorpalette)
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130
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131 MyThick = Thick()
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132
23
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133 #debut=time.time()
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134 #MyThick.transform_image(d)
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135 #fin=time.time()
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136 #print '------------------------------------------------'
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137 #print d.shape[0],' images transformed in :', fin-debut, ' seconds'
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138 #print '------------------------------------------------'
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139 #print (fin-debut)/d.shape[0]*1000000,' microseconds per image'
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140 #print '------------------------------------------------'
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141 #print MyThick.get_settings_names()
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142 #print MyThick._get_current_parameters()
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143 #print MyThick.regenerate_parameters(0)
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144 #print MyThick.regenerate_parameters(0.5)
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145 #print MyThick.regenerate_parameters(1)
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146 for i in range(10000):
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147 a=d[i,:]
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148 b=N.asarray(N.reshape(a,(32,32))).T
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149
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150 new=pygame.surfarray.make_surface(b)
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151 new=pygame.transform.scale2x(new)
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152 new=pygame.transform.scale2x(new)
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153 new=pygame.transform.scale2x(new)
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154 new.set_palette(anglcolorpalette)
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155 screen.blit(new,(0,0))
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156
23
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157 #max dilation
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158 MyThick.meth=1
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159 MyThick.nb=MyThick.__dilatemax__
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160 c=MyThick.transform_image(a)
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161 b=N.asarray(N.reshape(c,(32,32))).T
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162
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163 new=pygame.surfarray.make_surface(b)
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164 new=pygame.transform.scale2x(new)
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165 new=pygame.transform.scale2x(new)
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166 new=pygame.transform.scale2x(new)
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167 new.set_palette(anglcolorpalette)
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168 screen.blit(new,(8*32,0))
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169
23
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170 #max erosion
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171 MyThick.meth=-1
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172 MyThick.nb=MyThick.__erodemax__
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173 c=MyThick.transform_image(a)
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174 b=N.asarray(N.reshape(c,(32,32))).T
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175
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176 new=pygame.surfarray.make_surface(b)
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177 new=pygame.transform.scale2x(new)
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178 new=pygame.transform.scale2x(new)
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179 new=pygame.transform.scale2x(new)
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180 new.set_palette(anglcolorpalette)
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181 screen.blit(new,(8*2*32,0))
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182
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183 #random
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184 print MyThick.get_settings_names(), MyThick.regenerate_parameters(1)
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185 c=MyThick.transform_image(a)
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186 b=N.asarray(N.reshape(c,(32,32))).T
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187
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188 new=pygame.surfarray.make_surface(b)
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189 new=pygame.transform.scale2x(new)
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190 new=pygame.transform.scale2x(new)
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191 new=pygame.transform.scale2x(new)
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192 new.set_palette(anglcolorpalette)
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193 screen.blit(new,(8*3*32,0))
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194
11
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195 pygame.display.update()
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196 raw_input('Press Enter')
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197
17
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198 pygame.display.quit()