Mercurial > ift6266

annotate data_generation/transformations/slant.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: utf-8
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4 '''
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5 Author: Youssouf
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6
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7 this module add a slant effect to the image.
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8
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9 To obtain the slant effect, each row of the array is shifted proportionately by a step controlled by the complexity.
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11 '''
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12
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13 import numpy
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16 class Slant():
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17 def __init__(self, complexity=1):
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18 #---------- private attributes
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19 self.direction = 1
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20 self.angle = 0
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21
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22 #---------- generation parameters
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23 self.regenerate_parameters(complexity)
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24 #------------------------------------------------
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25
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26 def _get_current_parameters(self):
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27 return [self.angle, self.direction]
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28
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29 def get_settings_names(self):
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30 return ['angle', 'direction']
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32 def regenerate_parameters(self, complexity):
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33 self.angle = numpy.random.uniform(0.0, complexity)
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34 P = numpy.random.uniform()
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35 self.direction = 1;
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36 if P < 0.5:
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37 self.direction = -1;
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38 return self._get_current_parameters()
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41 def transform_image(self,image):
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42 if self.angle == 0:
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43 return image
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44
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45 ysize, xsize = image.shape
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46 slant = self.direction*self.angle
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47
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48 output = image.copy()
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49
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50 # shift all the rows
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51 for i in range(ysize):
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52 line = image[i]
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53 delta = round((i*slant)) % xsize
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54 line1 = line[:xsize-delta]
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55 line2 = line[xsize-delta:xsize]
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57 output[i][delta:xsize] = line1
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58 output[i][0:delta] = line2
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61 #correction to center the image
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62 correction = (self.direction)*round(self.angle*ysize/2)
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63 correction = (xsize - correction) % xsize
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65 # center the region
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66 line1 = output[0:ysize,0:xsize-correction].copy()
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67 line2 = output[0:ysize,xsize-correction:xsize].copy()
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68 output[0:ysize,correction:xsize] = line1
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69 output[0:ysize,0:correction] = line2
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72 return output
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74
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75 # Test function
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76 # Load an image in local and create several samples of the effect on the
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77 # original image with different parameter. All the samples are saved in a single image, the 1st image being the original.
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78
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79 def test_slant():
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80 import scipy
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81 img_name = "test_img/mnist_0.png"
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82 dest_img_name = "test_img/slanted.png"
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83 nb_samples = 10
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84 im = Image.open(img_name)
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85 im = im.convert("L")
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86 image = numpy.asarray(im)
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87
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88 image_final = image
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89 slant = Slant()
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90 for i in range(nb_samples):
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91 slant.regenerate_parameters(1)
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92 image_slant = slant.transform_image(image)
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93 image_final = scipy.hstack((image_final,image_slant))
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94
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95 im = Image.fromarray(image_final.astype('uint8'), "L")
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96 im.save(dest_img_name)
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97
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98 # Test
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99 if __name__ == '__main__':
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100 import sys, os, fnmatch
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101 import Image
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102
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103 test_slant()
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104