Mercurial > ift6266

comparison data_generation/transformations/add_background_image.py @ 167:1f5937e9e530

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More moves - transformations into data_generation, added "deep" folder
author Dumitru Erhan <dumitru.erhan@gmail.com>
date Fri, 26 Feb 2010 14:15:38 -0500
parents transformations/add_background_image.py@8aadb0f59a64
children
comparison
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166:17ae5a1a4dd1 167:1f5937e9e530
1 #!/usr/bin/python
2 # -*- coding: iso-8859-1 -*-
3
4 '''
5 Implementation of random background adding to a specific image
6
7 Author: Guillaume Sicard
8 '''
9
10 import sys, os, random
11 import cPickle
12 import Image, numpy
13
14 class AddBackground():
15 def __init__(self, threshold = 128, complexity = 1):
16 self.h = 32
17 self.w = 32
18 self.threshold = 1;
19 try: #in order to load locally if it is available
20 self.bg_image_file = '/Tmp/image_net/'
21 f=open(self.bg_image_file+'filelist.pkl')
22 except:
23 self.bg_image_file = '/data/lisa/data/ift6266h10/image_net/'
24 f=open(self.bg_image_file+'filelist.pkl')
25 self.image_files = cPickle.load(f)
26 f.close()
27 self.regenerate_parameters(complexity)
28
29 def get_current_parameters(self):
30 return [self.contrast]
31 # get threshold value
32 def get_settings_names(self):
33 return ['contrast']
34
35 # no need, except for testmod.py
36 def regenerate_parameters(self, complexity):
37 self.contrast = 1-numpy.random.rand()*complexity
38 return [self.contrast]
39
40 # load an image
41 def load_image(self,filename):
42 image = Image.open(filename).convert('L')
43 image = numpy.asarray(image)
44 image = (image / 255.0).astype(numpy.float32)
45 return image
46
47 # save an image
48 def save_image(self,array, filename):
49 image = (array * 255.0).astype('int')
50 image = Image.fromarray(image)
51 if (filename != ''):
52 image.save(filename)
53 else:
54 image.show()
55
56 # make a random 32x32 crop of an image
57 def rand_crop(self,image):
58 i_w, i_h = image.shape
59 x, y = random.randint(0, i_w - self.w), random.randint(0, i_h - self.h)
60 return image[x:x + self.w, y:y + self.h]
61
62 # select a random background image from "bg_image_file" and crops it
63 def rand_bg_image(self,maximage):
64 i = random.randint(0, len(self.image_files) - 1)
65
66 image = self.load_image(self.bg_image_file + self.image_files[i])
67 self.bg_image = self.rand_crop(image)
68 maxbg = self.bg_image.max()
69 self.bg_image = self.bg_image / maxbg * ( max(maximage - self.contrast,0.0) )
70
71 # set "bg_image" as background to "image", based on a pixels threshold
72 def set_bg(self,image):
73 tensor = numpy.asarray([self.bg_image,image],dtype='float32')
74 return tensor.max(0)
75
76 # transform an image file and return an array
77 def transform_image_from_file(self, filename):
78 self.rand_bg_image()
79 image = self.load_image(filename)
80 image = self.set_bg(image)
81 return image
82
83 # standard array to array transform
84 def transform_image(self, image):
85 self.rand_bg_image(image.max())
86 image = self.set_bg(image)
87 return image
88
89 # test method
90 def test(self,filename):
91 import time
92
93 sys.stdout.write('Starting addBackground test : loading image')
94 sys.stdout.flush()
95
96 image = self.load_image(filename)
97
98 t = 0
99 n = 500
100 for i in range(n):
101 t0 = time.time()
102 image2 = self.transform_image(image)
103 t = ( i * t + (time.time() - t0) ) / (i + 1)
104 sys.stdout.write('.')
105 sys.stdout.flush()
106
107 print "Done!\nAverage time : " + str(1000 * t) + " ms"
108
109 if __name__ == '__main__':
110
111 myAddBackground = AddBackground()
112 myAddBackground.test('./images/0-LiberationSans-Italic.ttf.jpg')