Mercurial > ift6266

annotate data_generation/transformations/add_background_image.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
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1 #!/usr/bin/python
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2 # -*- coding: iso-8859-1 -*-
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4 '''
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5 Implementation of random background adding to a specific image
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6
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7 Author: Guillaume Sicard
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8 '''
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10 import sys, os, random
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11 import cPickle
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12 import Image, numpy
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14 class AddBackground():
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15 def __init__(self, threshold = 128, complexity = 1):
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16 self.h = 32
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17 self.w = 32
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18 self.threshold = 1;
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19 try: #in order to load locally if it is available
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20 self.bg_image_file = '/Tmp/image_net/'
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21 f=open(self.bg_image_file+'filelist.pkl')
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22 except:
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23 self.bg_image_file = '/data/lisa/data/ift6266h10/image_net/'
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24 f=open(self.bg_image_file+'filelist.pkl')
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25 self.image_files = cPickle.load(f)
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26 f.close()
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27 self.regenerate_parameters(complexity)
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29 def get_current_parameters(self):
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30 return [self.contrast]
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31 # get threshold value
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32 def get_settings_names(self):
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33 return ['contrast']
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34
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35 # no need, except for testmod.py
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36 def regenerate_parameters(self, complexity):
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37 self.contrast = 1-numpy.random.rand()*complexity
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38 return [self.contrast]
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40 # load an image
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41 def load_image(self,filename):
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42 image = Image.open(filename).convert('L')
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43 image = numpy.asarray(image)
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44 image = (image / 255.0).astype(numpy.float32)
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45 return image
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47 # save an image
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48 def save_image(self,array, filename):
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49 image = (array * 255.0).astype('int')
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50 image = Image.fromarray(image)
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51 if (filename != ''):
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52 image.save(filename)
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53 else:
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54 image.show()
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56 # make a random 32x32 crop of an image
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57 def rand_crop(self,image):
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58 i_w, i_h = image.shape
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59 x, y = random.randint(0, i_w - self.w), random.randint(0, i_h - self.h)
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60 return image[x:x + self.w, y:y + self.h]
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62 # select a random background image from "bg_image_file" and crops it
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63 def rand_bg_image(self,maximage):
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64 i = random.randint(0, len(self.image_files) - 1)
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66 image = self.load_image(self.bg_image_file + self.image_files[i])
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67 self.bg_image = self.rand_crop(image)
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68 maxbg = self.bg_image.max()
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69 self.bg_image = self.bg_image / maxbg * ( max(maximage - self.contrast,0.0) )
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71 # set "bg_image" as background to "image", based on a pixels threshold
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72 def set_bg(self,image):
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73 tensor = numpy.asarray([self.bg_image,image],dtype='float32')
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74 return tensor.max(0)
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75
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76 # transform an image file and return an array
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77 def transform_image_from_file(self, filename):
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78 self.rand_bg_image()
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79 image = self.load_image(filename)
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80 image = self.set_bg(image)
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81 return image
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83 # standard array to array transform
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84 def transform_image(self, image):
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85 self.rand_bg_image(image.max())
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86 image = self.set_bg(image)
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87 return image
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89 # test method
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90 def test(self,filename):
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91 import time
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93 sys.stdout.write('Starting addBackground test : loading image')
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94 sys.stdout.flush()
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95
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96 image = self.load_image(filename)
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98 t = 0
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99 n = 500
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100 for i in range(n):
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101 t0 = time.time()
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102 image2 = self.transform_image(image)
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103 t = ( i * t + (time.time() - t0) ) / (i + 1)
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104 sys.stdout.write('.')
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105 sys.stdout.flush()
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106
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107 print "Done!\nAverage time : " + str(1000 * t) + " ms"
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108
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109 if __name__ == '__main__':
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110
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111 myAddBackground = AddBackground()
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112 myAddBackground.test('./images/0-LiberationSans-Italic.ttf.jpg')