Mercurial > ift6266

annotate transformations/add_background_image.py @ 41:fdb0e0870fb4

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Beaucoup de modifications à pipeline.py pour généraliser et un début de visualisation, et créé un wrapper (run_pipeline.py) pour appeler avec GIMP. - Modifications à pipeline.py - Wrappé la boucle du pipeline dans une classe - Isolé le problème de itérer sur les batches et les complexités dans des itérateurs - Permet d'avoir des ordres compliqués de batch (plusieurs sources), de complexités - Maintenant regenerate_parameters() est appelé pour chaque image. - Command line arguments avec getopt(). On pourra rajouter des options ainsi. - run_pipeline.py - Le but est de permettre de passer des arguments. Pas facile (pas trouvé comment de façon simple) avec la command line pour appeler GIMP en mode batch. C'est un hack ici. - Le but ultime est de permettre de lancer les jobs sur les clusters avec dbidispatch en précisant les options (diff. pour chaque job) sur la ligne de commande.
author fsavard
date Wed, 03 Feb 2010 17:08:27 -0500
parents 4d4248f7e2fb
children ab70fbca513c
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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7 Author: Guillaume Sicard
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8 '''
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10 import sys, os, random, fnmatch
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11 import Image, numpy
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13 class AddBackground():
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14 def __init__(self, threshold = 128):
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15 self.h = 32
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16 self.w = 32
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17 self.threshold = threshold;
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18 self.bg_image_dir = './images/'
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19 self.pattern = '*.jpg'
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21 # get threshold value
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22 def get_settings_names(self):
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23 return [str(self.threshold)]
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24
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25 # no need, except for testmod.py
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26 def regenerate_parameters(self, complexity):
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27 value = random.gauss(0, 0.5*complexity)
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28 return [value]
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30 # load an image
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31 def load_image(self,filename):
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32 image = Image.open(filename).convert('L')
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33 image = numpy.asarray(image)
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34 image = (image / 255.0).astype(numpy.float32)
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35 return image
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37 # save an image
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38 def save_image(self,array, filename):
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39 image = (array * 255.0).astype('int')
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40 image = Image.fromarray(image)
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41 if (filename != ''):
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42 image.save(filename)
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43 else:
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44 image.show()
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46 # make a random 32x32 crop of an image
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47 def rand_crop(self,image):
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48 i_w, i_h = image.shape
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49 x, y = random.randint(0, i_w - self.w), random.randint(0, i_h - self.h)
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50 return image[x:x + self.w, y:y + self.h]
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52 # select a random background image from "bg_image_dir" and crops it
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53 def rand_bg_image(self):
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54 files = os.listdir(self.bg_image_dir)
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55 image_files = fnmatch.filter(files, self.pattern)
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56 i = random.randint(0, len(image_files) - 1)
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58 image = self.load_image(self.bg_image_dir + image_files[i])
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59 self.bg_image = self.rand_crop(image)
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61 # set "bg_image" as background to "image", based on a pixels threshold
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62 def set_bg(self,image):
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63 b = (image < self.threshold / 255.0).astype(numpy.float32)
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64 return b * self.bg_image + ( 1 - b) * image
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66 # transform an image file and return an array
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67 def transform_image_from_file(self, filename):
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68 self.rand_bg_image()
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69 image = self.load_image(filename)
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70 image = self.set_bg(image)
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71 return image
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73 # standard array to array transform
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74 def transform_image(self, image):
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75 self.rand_bg_image()
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76 image = self.set_bg(image)
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77 return image
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79 # test method
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80 def test(self,filename):
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81 import time
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83 sys.stdout.write('Starting addBackground test : loading image')
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84 sys.stdout.flush()
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86 image = self.load_image(filename)
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88 t = 0
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89 n = 500
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90 for i in range(n):
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91 t0 = time.time()
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92 image2 = self.transform_image(image)
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93 t = ( i * t + (time.time() - t0) ) / (i + 1)
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94 sys.stdout.write('.')
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95 sys.stdout.flush()
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96
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97 print "Done!\nAverage time : " + str(1000 * t) + " ms"
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99 if __name__ == '__main__':
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101 myAddBackground = AddBackground()
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102 myAddBackground.test('./images/0-LiberationSans-Italic.ttf.jpg')