Mercurial > ift6266

comparison transformations/DistorsionGauss.py @ 77:aee278ebc827

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Mise a niveau specifications parametres deterministes et nouvelle normalisation des images
author SylvainPL <sylvain.pannetier.lebeuf@umontreal.ca>
date Wed, 10 Feb 2010 14:42:40 -0500
parents 3bc75139654a
children e352a98fcc0a
comparison
equal deleted inserted replaced
76:42e3e2f67626 77:aee278ebc827
16 16
17 def __init__(self): 17 def __init__(self):
18 self.ecart_type=0.1 #L'ecart type de la gaussienne 18 self.ecart_type=0.1 #L'ecart type de la gaussienne
19 19
20 def get_settings_names(self): 20 def get_settings_names(self):
21 return []
22
23 def get_settings_name_determined_by_complexity(self):
21 return ['ecart_type'] 24 return ['ecart_type']
22 25
23 def regenerate_parameters(self, complexity): 26 def regenerate_parameters(self, complexity):
24 self.ecart_type=float(complexity)/10 27 self.ecart_type=float(complexity)/10
25 return self._get_current_parameters() 28 return self._get_current_parameters()
35 aleatoire=numpy.zeros((1024,1)).astype('float32') 38 aleatoire=numpy.zeros((1024,1)).astype('float32')
36 for i in xrange(0,1024): 39 for i in xrange(0,1024):
37 aleatoire[i]=float(random.gauss(0,self.ecart_type)) 40 aleatoire[i]=float(random.gauss(0,self.ecart_type))
38 image=image+aleatoire 41 image=image+aleatoire
39 42
40 #Ramener tout entre 0 et 1 43
41 if numpy.min(image) < 0: 44 #Ramener tout entre 0 et 1. Ancienne facon de normaliser.
42 image-=numpy.min(image) 45 #Resultats moins interessant je trouve.
43 if numpy.max(image) > 1: 46 ## if numpy.min(image) < 0:
44 image/=numpy.max(image) 47 ## image-=numpy.min(image)
48 ## if numpy.max(image) > 1:
49 ## image/=numpy.max(image)
50
51 for i in xrange(0,1024):
52 image[i]=min(1,max(0,image[i]))
45 53
46 return image.reshape(32,32) 54 return image.reshape(32,32)
47 55
48 56
49 #---TESTS--- 57 #---TESTS---
70 78
71 if __name__ == '__main__': 79 if __name__ == '__main__':
72 from pylearn.io import filetensor as ft 80 from pylearn.io import filetensor as ft
73 import pylab 81 import pylab
74 for i in xrange(0,5): 82 for i in xrange(0,5):
75 _test(1) 83 _test(0.5)
76 84
77 85