--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/data_generation/transformations/add_background_image.py	Fri Feb 26 14:15:38 2010 -0500
@@ -0,0 +1,112 @@
+#!/usr/bin/python                                                                                 
+# -*- coding: iso-8859-1 -*-                                                                      
+
+'''
+    Implementation of random background adding to a specific image
+
+    Author: Guillaume Sicard
+'''
+
+import sys, os, random
+import cPickle
+import Image, numpy           
+
+class AddBackground():
+    def __init__(self, threshold = 128, complexity = 1):
+        self.h = 32
+        self.w = 32
+        self.threshold = 1;
+        try: #in order to load locally if it is available
+            self.bg_image_file = '/Tmp/image_net/'
+            f=open(self.bg_image_file+'filelist.pkl')
+        except:
+            self.bg_image_file = '/data/lisa/data/ift6266h10/image_net/'
+            f=open(self.bg_image_file+'filelist.pkl')
+        self.image_files = cPickle.load(f)
+        f.close()
+        self.regenerate_parameters(complexity)
+    
+    def get_current_parameters(self):
+        return [self.contrast]
+    # get threshold value
+    def get_settings_names(self):
+        return ['contrast']
+    
+    # no need, except for testmod.py
+    def regenerate_parameters(self, complexity):
+        self.contrast = 1-numpy.random.rand()*complexity
+        return [self.contrast]
+
+    # load an image
+    def load_image(self,filename):
+        image = Image.open(filename).convert('L')
+        image = numpy.asarray(image)
+        image = (image / 255.0).astype(numpy.float32)
+        return image
+
+    # save an image
+    def save_image(self,array, filename):
+        image = (array * 255.0).astype('int')
+        image = Image.fromarray(image)
+        if (filename != ''):
+            image.save(filename)
+        else:
+            image.show()
+
+    # make a random 32x32 crop of an image
+    def rand_crop(self,image):
+        i_w, i_h = image.shape
+        x, y = random.randint(0, i_w - self.w), random.randint(0, i_h - self.h)
+        return image[x:x + self.w, y:y + self.h]
+
+    # select a random background image from "bg_image_file" and crops it
+    def rand_bg_image(self,maximage):
+        i = random.randint(0, len(self.image_files) - 1)
+
+        image = self.load_image(self.bg_image_file + self.image_files[i])
+        self.bg_image = self.rand_crop(image)
+        maxbg = self.bg_image.max()
+        self.bg_image = self.bg_image / maxbg * ( max(maximage - self.contrast,0.0) ) 
+
+    # set "bg_image" as background to "image", based on a pixels threshold
+    def set_bg(self,image):
+        tensor = numpy.asarray([self.bg_image,image],dtype='float32')
+        return tensor.max(0)
+
+    # transform an image file and return an array
+    def transform_image_from_file(self, filename):
+        self.rand_bg_image()
+        image = self.load_image(filename)
+        image = self.set_bg(image)
+        return image
+
+    # standard array to array transform
+    def transform_image(self, image):
+        self.rand_bg_image(image.max())
+        image = self.set_bg(image)
+        return image
+
+    # test method
+    def test(self,filename):
+        import time
+
+        sys.stdout.write('Starting addBackground test : loading image')
+        sys.stdout.flush()
+
+        image = self.load_image(filename)
+
+        t = 0
+        n = 500
+        for i in range(n):
+            t0 =  time.time()
+            image2 = self.transform_image(image)
+            t = ( i * t + (time.time() - t0) ) / (i + 1)
+            sys.stdout.write('.')
+            sys.stdout.flush()
+            
+        print "Done!\nAverage time : " + str(1000 * t) + " ms"
+
+if __name__ == '__main__':
+
+    myAddBackground = AddBackground()
+    myAddBackground.test('./images/0-LiberationSans-Italic.ttf.jpg')