Mercurial > ift6266
annotate data_generation/transformations/add_background_image.py @ 552:35c611363291
added the real picture
author | Frederic Bastien <nouiz@nouiz.org> |
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date | Wed, 02 Jun 2010 17:28:43 -0400 |
parents | 1f5937e9e530 |
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1 #!/usr/bin/python |
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2 # -*- coding: iso-8859-1 -*- |
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3 |
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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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9 |
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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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13 |
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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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28 |
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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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39 |
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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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46 |
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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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55 |
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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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61 |
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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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65 |
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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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70 |
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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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82 |
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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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88 |
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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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92 |
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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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97 |
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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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changeset
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112 myAddBackground.test('./images/0-LiberationSans-Italic.ttf.jpg') |