Mercurial > ift6266
changeset 53:60b093f963d8
Ajout de chargement d'un fichier d'image afin d'avoir une plus grande variete de fragments possible. Ce fichier est sur Assembla dans <files>.
| author | SylvainPL <sylvain.pannetier.lebeuf@umontreal.ca> |
|---|---|
| date | Fri, 05 Feb 2010 11:07:20 -0500 |
| parents | c89defea1e65 |
| children | 12bc019acd4e |
| files | transformations/Occlusion.py |
| diffstat | 1 files changed, 24 insertions(+), 43 deletions(-) [+] |
line wrap: on
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--- a/transformations/Occlusion.py Thu Feb 04 16:53:50 2010 -0500 +++ b/transformations/Occlusion.py Fri Feb 05 11:07:20 2010 -0500 @@ -2,23 +2,24 @@ # 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 ???? +Ajout de bruit d'occlusion dans l'image originale. 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. +Il faut s'assurer d'avoir le fichier echantillon_occlusion.ft (voir "files" sur assembla) +dans le repertoire ou est effectuee l'execution de Occlusion.py. Sinon, +simplement changer le "path" sur la ligne 46 + Sylvain Pannetier Lebeuf dans le cadre de IFT6266, hiver 2010 ''' import numpy -#import random import scipy import pylab -#from scipy import ndimage class Occlusion(): @@ -40,37 +41,15 @@ self.endroit=-1 #Cette variable determine l'opacite de l'ajout dans le cas ou on est au milieu - self.opacite=0.5 + f3 = open('echantillon_occlusion.ft') #Arranger pour y mettre le bon path !! + #Presentement, on prend en compte que le fichier est ou on execute + + w=ft.read(f3) + f3.close() - ##La douzaine d'image sera stoquee ici et non dans un autre fichier - ##Afin de ne pas devoir charger un autre fichier a chaque appel. - w=numpy.zeros((12,1024)) - #a - w[0]=numpy.asarray([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, 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, 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, 2, 7, 18, 28, 18, 7, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 31, 73, 115, 144, 115, 70, 23, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 12, 44, 124, 192, 219, 231, 223, 188, 100, 23, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 45, 93, 146, 198, 197, 171, 172, 211, 237, 187, 67, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 47, 146, 210, 212, 156, 83, 44, 48, 122, 221, 216, 92, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 20, 111, 216, 225, 153, 58, 12, 3, 6, 59, 184, 224, 125, 26, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 62, 177, 230, 162, 58, 10, 1, 0, 2, 37, 165, 239, 189, 68, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 25, 130, 227, 222, 103, 15, 1, 0, 0, 2, 37, 165, 245, 217, 89, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 34, 161, 243, 212, 84, 8, 0, 0, 0, 4, 56, 184, 247, 220, 91, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 35, 164, 240, 184, 56, 4, 0, 0, 0, 9, 86, 213, 251, 219, 91, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 35, 164, 237, 165, 37, 2, 0, 0, 0, 18, 117, 229, 252, 212, 84, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 35, 164, 237, 165, 37, 2, 0, 0, 1, 34, 155, 243, 249, 186, 57, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 34, 161, 239, 184, 56, 4, 0, 0, 5, 58, 184, 249, 249, 186, 58, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 26, 136, 232, 212, 87, 9, 0, 3, 28, 118, 222, 251, 251, 215, 96, 14, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 78, 192, 222, 126, 29, 6, 26, 102, 199, 239, 222, 228, 235, 161, 59, 15, 6, 2, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 26, 123, 221, 198, 101, 51, 105, 198, 238, 200, 126, 152, 223, 225, 161, 102, 72, 43, 35, 26, 9, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 70, 188, 234, 194, 165, 208, 238, 210, 115, 35, 56, 137, 205, 230, 220, 198, 170, 159, 129, 63, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 23, 104, 204, 239, 240, 241, 206, 117, 39, 5, 8, 35, 104, 187, 216, 216, 211, 202, 161, 88, 18, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 34, 122, 200, 215, 180, 116, 35, 5, 0, 0, 3, 23, 67, 89, 91, 91, 84, 54, 24, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 33, 86, 98, 56, 25, 5, 0, 0, 0, 0, 2, 6, 9, 9, 9, 8, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 12, 13, 5, 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, 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]) - 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#z - w[10]=numpy.asarray([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, 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, 3, 8, 9, 9, 9, 8, 7, 7, 4, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 35, 80, 91, 91, 91, 86, 75, 78, 55, 36, 26, 10, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 102, 197, 218, 219, 219, 214, 203, 206, 183, 163, 136, 80, 31, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 21, 115, 207, 227, 236, 244, 244, 243, 243, 241, 241, 234, 198, 121, 33, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 45, 99, 117, 140, 161, 164, 164, 164, 171, 201, 230, 243, 204, 98, 18, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 14, 18, 27, 34, 35, 35, 36, 44, 83, 160, 236, 242, 171, 51, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 2, 12, 64, 167, 241, 250, 201, 75, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 10, 57, 153, 229, 251, 231, 150, 45, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 16, 63, 154, 229, 252, 243, 175, 64, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 20, 80, 170, 231, 251, 245, 197, 95, 18, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 27, 96, 181, 237, 252, 240, 192, 101, 26, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 38, 114, 199, 243, 253, 243, 182, 86, 24, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 28, 114, 210, 247, 254, 245, 197, 96, 20, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 26, 102, 200, 247, 252, 237, 191, 101, 26, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 23, 101, 198, 245, 252, 229, 160, 80, 24, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 70, 188, 245, 254, 237, 160, 59, 12, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 26, 123, 228, 254, 249, 198, 84, 16, 8, 9, 9, 8, 4, 2, 3, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 68, 189, 247, 254, 243, 176, 81, 59, 84, 91, 91, 84, 56, 39, 48, 47, 28, 17, 9, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 87, 215, 253, 255, 251, 227, 188, 186, 212, 219, 219, 212, 184, 167, 176, 173, 141, 104, 49, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 67, 186, 241, 251, 253, 252, 248, 248, 251, 252, 252, 251, 245, 239, 239, 238, 224, 178, 73, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 23, 93, 159, 199, 218, 220, 220, 220, 220, 220, 220, 218, 199, 171, 164, 163, 153, 104, 35, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 16, 39, 71, 90, 91, 91, 91, 91, 91, 91, 90, 71, 43, 36, 35, 32, 17, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 6, 9, 9, 9, 9, 9, 9, 9, 9, 6, 2, 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]) - #o - w[11]=numpy.asarray([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, 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, 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, 3, 11, 13, 16, 22, 12, 8, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 24, 69, 77, 88, 122, 101, 84, 51, 15, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 69, 149, 136, 152, 218, 222, 211, 166, 79, 20, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 48, 145, 177, 127, 171, 218, 236, 246, 236, 180, 88, 16, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 22, 110, 206, 173, 110, 128, 115, 141, 192, 239, 238, 162, 49, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 13, 73, 166, 229, 202, 96, 44, 22, 31, 89, 192, 242, 217, 125, 31, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 38, 136, 171, 204, 184, 68, 9, 1, 2, 24, 105, 210, 245, 195, 70, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 71, 188, 208, 203, 122, 26, 2, 0, 0, 4, 45, 170, 245, 218, 90, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 97, 219, 246, 209, 86, 9, 0, 0, 0, 1, 29, 145, 238, 220, 94, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 112, 226, 236, 166, 51, 4, 0, 0, 0, 1, 20, 122, 230, 228, 117, 18, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 99, 217, 193, 84, 16, 1, 0, 0, 0, 0, 12, 99, 222, 241, 154, 32, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 92, 212, 173, 48, 4, 0, 0, 0, 0, 0, 9, 92, 220, 245, 163, 35, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 91, 216, 199, 74, 7, 0, 0, 0, 0, 0, 13, 102, 223, 245, 163, 35, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 90, 217, 226, 118, 21, 1, 0, 0, 0, 3, 36, 146, 237, 240, 152, 31, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 70, 196, 240, 178, 71, 21, 9, 5, 6, 27, 105, 207, 244, 204, 96, 16, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 32, 134, 218, 228, 178, 119, 87, 62, 64, 112, 198, 237, 205, 122, 33, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 48, 132, 218, 240, 228, 213, 190, 190, 216, 243, 210, 109, 34, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 48, 134, 200, 235, 248, 249, 250, 251, 244, 171, 46, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 33, 81, 144, 201, 235, 245, 237, 206, 136, 30, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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.longueur=len(w) self.d=(w/255).astype('float') @@ -92,7 +71,7 @@ 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.rajout=numpy.random.randint(0,self.longueur) #les bouts de quelle lettre self.endroit=numpy.random.randint(-1,2) #####Revoir si ces trois dernieres variables sont determinees ici ! @@ -139,17 +118,19 @@ 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() + for i in xrange(0,20): + img = _load_image() + 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__':