Mercurial > ift6266

annotate scripts/ocr_divide.py @ 570:f4b95749ffba

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nips_reviews.txt added
author Yoshua Bengio <bengioy@iro.umontreal.ca>
date Wed, 04 Aug 2010 15:04:46 -0400
parents 2b6a28e4cadc
children
rev   line source
137
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
parents:
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1 #!/usr/bin/env python
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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2
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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3 '''
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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4 creation des ensembles train, valid et test OCR
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2b6a28e4cadc J'ai reséparé NIST/OCR purs pour avoir des ensembles de test et de validation de 80000 plutôt que 20000, comme on a discuté au cours
boulanni <nicolas_boulanger@hotmail.com>
parents: 137
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5 ensemble valid est trainorig[:80000]
2b6a28e4cadc J'ai reséparé NIST/OCR purs pour avoir des ensembles de test et de validation de 80000 plutôt que 20000, comme on a discuté au cours
boulanni <nicolas_boulanger@hotmail.com>
parents: 137
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6 ensemble test est trainorig[80000:160000]
2b6a28e4cadc J'ai reséparé NIST/OCR purs pour avoir des ensembles de test et de validation de 80000 plutôt que 20000, comme on a discuté au cours
boulanni <nicolas_boulanger@hotmail.com>
parents: 137
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7 ensemble train est trainorig[160000:]
137
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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8 trainorig est deja shuffled
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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9 '''
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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10
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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11 from pylearn.io import filetensor as ft
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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12 import numpy, os
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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13
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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14 dir1 = '/data/lisa/data/ocr_breuel/filetensor/'
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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15 dir2 = "/data/lisa/data/ift6266h10/"
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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16
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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17 f = open(dir1 + 'unlv-corrected-2010-02-01-shuffled.ft')
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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18 d = ft.read(f)
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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19 f = open(dir2 + "ocr_valid_data.ft", 'wb')
182
2b6a28e4cadc J'ai reséparé NIST/OCR purs pour avoir des ensembles de test et de validation de 80000 plutôt que 20000, comme on a discuté au cours
boulanni <nicolas_boulanger@hotmail.com>
parents: 137
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20 ft.write(f, d[:80000])
137
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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21 f = open(dir2 + "ocr_test_data.ft", 'wb')
182
2b6a28e4cadc J'ai reséparé NIST/OCR purs pour avoir des ensembles de test et de validation de 80000 plutôt que 20000, comme on a discuté au cours
boulanni <nicolas_boulanger@hotmail.com>
parents: 137
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22 ft.write(f, d[80000:160000])
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728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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23 f = open(dir2 + "ocr_train_data.ft", 'wb')
182
2b6a28e4cadc J'ai reséparé NIST/OCR purs pour avoir des ensembles de test et de validation de 80000 plutôt que 20000, comme on a discuté au cours
boulanni <nicolas_boulanger@hotmail.com>
parents: 137
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24 ft.write(f, d[160000:])
137
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
parents:
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25
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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26 f = open(dir1 + 'unlv-corrected-2010-02-01-labels-shuffled.ft')
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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27 d = ft.read(f)
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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28 f = open(dir2 + "ocr_valid_labels.ft", 'wb')
182
2b6a28e4cadc J'ai reséparé NIST/OCR purs pour avoir des ensembles de test et de validation de 80000 plutôt que 20000, comme on a discuté au cours
boulanni <nicolas_boulanger@hotmail.com>
parents: 137
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29 ft.write(f, d[:80000])
137
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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30 f = open(dir2 + "ocr_test_labels.ft", 'wb')
182
2b6a28e4cadc J'ai reséparé NIST/OCR purs pour avoir des ensembles de test et de validation de 80000 plutôt que 20000, comme on a discuté au cours
boulanni <nicolas_boulanger@hotmail.com>
parents: 137
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31 ft.write(f, d[80000:160000])
137
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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32 f = open(dir2 + "ocr_train_labels.ft", 'wb')
182
2b6a28e4cadc J'ai reséparé NIST/OCR purs pour avoir des ensembles de test et de validation de 80000 plutôt que 20000, comme on a discuté au cours
boulanni <nicolas_boulanger@hotmail.com>
parents: 137
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33 ft.write(f, d[160000:])
137
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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34
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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35 for i in ["train", "valid", "test"]:
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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36 os.chmod(dir2 + "ocr_" + i + "_data.ft", 0744)
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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37 os.chmod(dir2 + "ocr_" + i + "_labels.ft", 0744)
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
parents:
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38
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
boulanni <nicolas_boulanger@hotmail.com>
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39
728e232eaf45 Added script to separate OCR data in train, validation and test sets (raw data)
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