Mercurial > ift6266
comparison transformations/pipeline.py @ 10:faacc76d21c2
Basic new pipeline script for the images tranforms
(includes bonus patched filetensor module from pylearn.io)
| author | Arnaud Bergeron <abergeron@gmail.com> |
|---|---|
| date | Wed, 27 Jan 2010 17:35:37 -0500 |
| parents | |
| children | f6b6c74bb82f |
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| 9:64dac4aabc04 | 10:faacc76d21c2 |
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| 1 from __future__ import with_statement | |
| 2 | |
| 3 import sys, os | |
| 4 import numpy | |
| 5 import filetensor as ft | |
| 6 import random | |
| 7 | |
| 8 BATCH_SIZE = 100 | |
| 9 | |
| 10 #import <modules> and stuff them in mods below | |
| 11 | |
| 12 mods = [] | |
| 13 | |
| 14 # DANGER: HIGH VOLTAGE -- DO NOT EDIT BELOW THIS LINE | |
| 15 # ----------------------------------------------------------- | |
| 16 | |
| 17 train_data = open('/data/lisa/data/nist/by_class/all/all_train_data.ft', 'rb') | |
| 18 | |
| 19 dim = tuple(ft._read_header(train_data)[3]) | |
| 20 | |
| 21 res_data = numpy.empty(dim) | |
| 22 | |
| 23 all_settings = ['complexity'] | |
| 24 | |
| 25 for mod in mods: | |
| 26 all_settings += mod.get_settings_names() | |
| 27 | |
| 28 params = numpy.empty(((dim[0]/BATCH_SIZE)+1, len(all_settings))) | |
| 29 | |
| 30 for i in xrange(0, dim[0], BATCH_SIZE): | |
| 31 train_data.seek(0) | |
| 32 imgs = ft.read(train_data, slice(i, i+BATCH_SIZE)) | |
| 33 | |
| 34 complexity = random.random() | |
| 35 p = i/BATCH_SIZE | |
| 36 j = 1 | |
| 37 for mod in mods: | |
| 38 par = mod.regenerate_parameters(complexity) | |
| 39 params[p, j:j+len(par)] = par | |
| 40 j += len(par) | |
| 41 | |
| 42 for k in range(imgs.shape[0]): | |
| 43 c = imgs[k] | |
| 44 for mod in mods: | |
| 45 c = mod.transform_image(c) | |
| 46 res_data[i+k] = c | |
| 47 | |
| 48 with open(sys.argv[1], 'wb') as f: | |
| 49 ft.write(f, res_data) | |
| 50 | |
| 51 numpy.save(sys.argv[2], params) |