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annotate pylearn/dataset_ops/image_patches.py @ 1510:07b48bd449cd

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Make a dataset ops use the new path system.
author Frederic Bastien <nouiz@nouiz.org>
date Mon, 12 Sep 2011 11:47:00 -0400
parents 976539956475
children 9ffe5d6faee3
rev   line source
963
06f21a964bd8 datasets - added olshausen_field data loaders, and an image_patches
James Bergstra <bergstrj@iro.umontreal.ca>
parents:
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1 import os, numpy
06f21a964bd8 datasets - added olshausen_field data loaders, and an image_patches
James Bergstra <bergstrj@iro.umontreal.ca>
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2 import theano
06f21a964bd8 datasets - added olshausen_field data loaders, and an image_patches
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3
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4 from pylearn.datasets.image_patches import (
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5 olshausen_field_1996_whitened_images,
06f21a964bd8 datasets - added olshausen_field data loaders, and an image_patches
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6 extract_random_patches)
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7
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8 from .protocol import TensorFnDataset # protocol.py __init__.py
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9 from .memo import memo
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10
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11 import scipy.io
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12 from pylearn.io import image_tiling
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13 from pylearn.datasets.config import get_filepath_in_roots
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14
963
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15 @memo
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16 def get_dataset(N,R,C,dtype,center,unitvar):
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17 seed=98234
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18 rng = numpy.random.RandomState(seed)
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19 img_stack = olshausen_field_1996_whitened_images()
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20 patch_stack = extract_random_patches(img_stack, N,R,C,rng)
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21 rval = patch_stack.astype(dtype).reshape((N,(R*C)))
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22
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23 if center:
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24 rval -= rval.mean(axis=0)
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25 if unitvar:
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26 rval /= numpy.max(rval.std(axis=0),1e-8)
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27
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28 return rval
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29
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30 def image_patches(s_idx, dims,
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31 split='train', dtype=theano.config.floatX, rasterized=False,
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32 center=True,
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33 unitvar=True,
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34 fn=get_dataset):
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35 N,R,C=dims
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36
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37 if split != 'train':
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38 raise NotImplementedError('train/test/valid splits for randomly sampled image patches?')
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39
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40 if not rasterized:
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41 raise NotImplementedError()
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42
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43 op = TensorFnDataset(dtype, bcast=(False,), fn=(fn, (N,R,C,dtype,center,unitvar)), single_shape=(R*C,))
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44 x = op(s_idx%N)
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45 if x.ndim == 1:
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46 if not rasterized:
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47 x = x.reshape((20,20))
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48 elif x.ndim == 2:
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49 if not rasterized:
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50 x = x.reshape((x.shape[0], 20,20))
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51 else:
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52 assert False, 'what happened?'
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53
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54 return x
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55
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 971
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56
8ba8b08e0442 added the image_patches dataset used in RanzatoHinton2010
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 971
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57
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 971
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58 @memo
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59 def ranzato_hinton_2010(path=None):
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60 if path is None:
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61 path = get_filepath_in_roots(os.path.join('image_patches', 'mcRBM',
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62 'training_colorpatches_16x16_demo.mat'))
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63 dct = scipy.io.loadmat(path)
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64 return dct
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65 def ranzato_hinton_2010_whitened_patches(path=None):
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66 """Return the pca of the data, which is 10240 x 105
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67 """
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68 dct = ranzato_hinton_2010(path)
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69 return dct['whitendata'].astype('float32')
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70
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71 def undo_pca_filters_of_ranzato_hinton_2010(X, path=None):
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72 """Return tuple (R,G,B,None) of matrices for matrix `X` of filters (one per row)
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73
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74 Return value can be passed to `image_tiling.tile_raster_images`.
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75 """
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76 dct = ranzato_hinton_2010(path)
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77 X = numpy.dot(X, dct['invpcatransf'].T)
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78 return (X[:,:256], X[:,256:512], X[:,512:], None)
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79
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80 def save_filters_of_ranzato_hinton_2010(X, fname, min_dynamic_range=1e-3, data_path=None):
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81 _img = image_tiling.tile_raster_images(
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82 undo_pca_filters_of_ranzato_hinton_2010(X, path=data_path),
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83 img_shape=(16,16),
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84 min_dynamic_range=min_dynamic_range)
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85 image_tiling.save_tiled_raster_images(_img, fname)
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86
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87 def ranzato_hinton_2010_op(s_idx,
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88 split='train',
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89 dtype=theano.config.floatX, rasterized=True,
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90 center=True,
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91 unitvar=True,
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92 fn=ranzato_hinton_2010_whitened_patches):
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93 N = 10240
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94
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95 if split != 'train':
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96 raise NotImplementedError('train/test/valid splits for randomly sampled image patches?')
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97
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98 if not rasterized:
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99 # the data is provided as PCA-sphered, so rasterizing does not make sense
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100 # TODO: add a param to enable/disable 'PCA', and if disabled, then consider
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101 # rasterizing or not
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102 raise NotImplementedError('only pca data is provided')
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parents: 971
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103
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104 if dtype != 'float32':
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105 raise NotImplementedError('dtype not float32')
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106
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107 op = TensorFnDataset(dtype,
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108 bcast=(False,),
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109 fn=fn,
998
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110 single_shape=(105,))
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111 x = op(s_idx%N)
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112 return x
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113