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comparison transformations/DistorsionGauss.py @ 47:3bc75139654a

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Ajout d'un petit bruit gaussien sur chaque pixel de l'image.
author SylvainPL <sylvain.pannetier.lebeuf@umontreal.ca>
date Thu, 04 Feb 2010 10:32:07 -0500
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children aee278ebc827
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46:48a21d19b8eb 47:3bc75139654a
1 #!/usr/bin/python
2 # coding: utf-8
3
4 '''
5 Ajout d'une composante aleatoire dans chaque pixel de l'image.
6 C'est une distorsion gaussienne de moyenne 0 et d'écart type complexity/10
7
8 Sylvain Pannetier Lebeuf dans le cadre de IFT6266, hiver 2010
9
10 '''
11
12 import numpy
13 import random
14
15 class DistorsionGauss():
16
17 def __init__(self):
18 self.ecart_type=0.1 #L'ecart type de la gaussienne
19
20 def get_settings_names(self):
21 return ['ecart_type']
22
23 def regenerate_parameters(self, complexity):
24 self.ecart_type=float(complexity)/10
25 return self._get_current_parameters()
26
27 def _get_current_parameters(self):
28 return []
29
30 def get_parameters_determined_by_complexity(self, complexity):
31 return [float(complexity)/10]
32
33 def transform_image(self, image):
34 image=image.reshape(1024,1)
35 aleatoire=numpy.zeros((1024,1)).astype('float32')
36 for i in xrange(0,1024):
37 aleatoire[i]=float(random.gauss(0,self.ecart_type))
38 image=image+aleatoire
39
40 #Ramener tout entre 0 et 1
41 if numpy.min(image) < 0:
42 image-=numpy.min(image)
43 if numpy.max(image) > 1:
44 image/=numpy.max(image)
45
46 return image.reshape(32,32)
47
48
49 #---TESTS---
50
51 def _load_image():
52 f = open('/home/sylvain/Dropbox/Msc/IFT6266/donnees/lower_test_data.ft') #Le jeu de donnees est en local.
53 d = ft.read(f)
54 w=numpy.asarray(d[random.randint(0,100)])
55 return (w/255.0).astype('float')
56
57 def _test(complexite):
58 img=_load_image()
59 transfo = DistorsionGauss()
60 pylab.imshow(img.reshape((32,32)))
61 pylab.show()
62 print transfo.get_settings_names()
63 print transfo.regenerate_parameters(complexite)
64
65 img_trans=transfo.transform_image(img)
66
67 pylab.imshow(img_trans.reshape((32,32)))
68 pylab.show()
69
70
71 if __name__ == '__main__':
72 from pylearn.io import filetensor as ft
73 import pylab
74 for i in xrange(0,5):
75 _test(1)
76
77