Mercurial > ift6266
changeset 45:f8a92292b299
merge de 4 fevrier
| author | SylvainPL <sylvain.pannetier.lebeuf@umontreal.ca> |
|---|---|
| date | Thu, 04 Feb 2010 10:27:58 -0500 |
| parents | 5deccb161307 (diff) 05145f4fb609 (current diff) |
| children | 48a21d19b8eb |
| files | |
| diffstat | 1 files changed, 158 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/transformations/Occlusion.py Thu Feb 04 10:27:58 2010 -0500 @@ -0,0 +1,158 @@ +#!/usr/bin/python +# coding: utf-8 + +''' +Ajout de bruit d'occlusion dans l'image originale. Le bruit d'occlusion vient +d'une seconde image passee en parametre dans la methode ???? + +Le bruit provient d'un echantillon pris dans la seconde image puis rajoutee a +gauche ou a droite de l'image originale. De plus, il se peut aussi que le +bruit soit rajoute sur l'image originale, mais en plus pâle. + +Sylvain Pannetier Lebeuf dans le cadre de IFT6266, hiver 2010 + +''' + + +import numpy +#import random +import scipy +import pylab +#from scipy import ndimage + +class Occlusion(): + + def __init__(self): + #Ces 4 variables representent la taille du "crop" sur l'image2 + #Ce "crop" est pris a partie de image1[15,15], le milieu de l'image1 + self.haut=2 + self.bas=2 + self.gauche=2 + self.droite=2 + + #Ces deux variables representent le deplacement en x et y par rapport + #au milieu du bord gauche ou droit + self.x_arrivee=0 + self.y_arrivee=0 + + #Cette variable =1 si l'image est mise a gauche et -1 si a droite + #et =0 si au centre, mais plus pale + self.endroit=-1 + + #Cette variable determine l'opacite de l'ajout dans le cas ou on est au milieu + + self.opacite=0.5 + + + ##La douzaine d'image sera stoquee ici et non dans un autre fichier + ##Afin de ne pas devoir charger un autre 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0, 0, 0, 0, 2, 10, 34, 80, 136, 160, 148, 98, 55, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 10, 26, 34, 31, 16, 6, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) + self.d=(w/255).astype('float') + + + def get_settings_names(self): + return ['haut','bas','gauche','droite','x_arrivee','y_arrivee','endroit','rajout'] + + def regenerate_parameters(self, complexity): + self.haut=min(15,int(numpy.abs(numpy.random.normal(int(7*complexity),2)))) + self.bas=min(15,int(numpy.abs(numpy.random.normal(int(7*complexity),2)))) + self.gauche=min(15,int(numpy.abs(numpy.random.normal(int(7*complexity),2)))) + self.droite=min(15,int(numpy.abs(numpy.random.normal(int(7*complexity),2)))) + if self.haut+self.bas+self.gauche+self.droite==0: #Tres improbable + self.haut=1 + self.bas=1 + self.gauche=1 + self.droite=1 + + #Ces deux valeurs seront controlees afin d'etre certain de ne pas depasser + self.x_arrivee=int(numpy.abs(numpy.random.normal(0,2))) #Complexity n'entre pas en jeu, pas besoin + self.y_arrivee=int(numpy.random.normal(0,3)) + + self.rajout=numpy.random.randint(0,12) #les bouts de quelle lettre + + self.endroit=numpy.random.randint(-1,2) + #####Revoir si ces trois dernieres variables sont determinees ici ! + return self._get_current_parameters() + + def _get_current_parameters(self): + return [self.haut,self.bas,self.gauche,self.droite,self.x_arrivee,self.y_arrivee,self.endroit,self.rajout] + + + def transform_image(self, image): + #Attrapper le bruit d'occlusion + bruit=self.d[self.rajout].reshape((32,32))[15-self.haut:15+self.bas+1,15-self.gauche:15+self.droite+1] + + if self.x_arrivee+self.gauche+self.droite>32: + self.endroit*=-1 #On change de bord et on colle sur le cote + self.x_arrivee=0 + if self.y_arrivee-self.haut <-16: + self.y_arrivee=self.haut-16#On colle le morceau en haut + if self.y_arrivee+self.bas > 15: + self.y_arrivee=15-self.bas #On colle le morceau en bas + + if self.endroit==-1: #a gauche + image[(16+self.y_arrivee-self.haut):(16+self.y_arrivee+self.bas+1),(self.x_arrivee):(self.x_arrivee+self.gauche+self.droite+1)]=image[(16+self.y_arrivee-self.haut):(16+self.y_arrivee+self.bas+1),(self.x_arrivee):(self.x_arrivee+self.gauche+self.droite+1)]+bruit + + elif self.endroit==1: #a droite + image[(16+self.y_arrivee-self.haut):(16+self.y_arrivee+self.bas+1),(31-self.x_arrivee-self.gauche-self.droite):(31-self.x_arrivee+1)]=image[(16+self.y_arrivee-self.haut):(16+self.y_arrivee+self.bas+1),(31-self.x_arrivee-self.gauche-self.droite):(31-self.x_arrivee+1)]+bruit + + elif self.endroit==0: #au milieu + image[(16-self.haut):(16+self.bas+1),(16-self.gauche):(16+self.droite+1)]=image[(16-self.haut):(16+self.bas+1),(16-self.gauche):(16+self.droite+1)]+(bruit*self.opacite) + + #renormaliser le tout. Toutes les entrees doivent etre entre 0 et 1 + for ii in xrange(0,32): + for jj in xrange(0,32): + image[ii,jj]=min(1,image[ii,jj]) + + return image + +#---TESTS--- + +def _load_image(): + f = open('/home/sylvain/Dropbox/Msc/IFT6266/donnees/lower_test_data.ft') #Le jeu de donnees est en local. + d = ft.read(f) + w=numpy.asarray(d[numpy.random.randint(0,50)]) + return (w/255.0).astype('float') + +def _test(complexite): + img=_load_image() + transfo = Occlusion() + pylab.imshow(img.reshape((32,32))) + pylab.show() + print transfo.get_settings_names() + print transfo.regenerate_parameters(complexite) + + img_trans=transfo.transform_image(img.reshape((32,32))) + + pylab.imshow(img_trans.reshape((32,32))) + pylab.show() + + +if __name__ == '__main__': + from pylearn.io import filetensor as ft + import pylab + _test(0.5) \ No newline at end of file