def run():
with h5py.File('HWDB1.1.hdf5', 'w') as f:
for name, size, dirpath in [('trn', TRN_SIZE, trn_dirpath), ('tst', TST_SIZE, tst_dirpath)]:
print('Converting \'%s\'...' % name)
grp = f.create_group(name)
dset_bitmap = grp.create_dataset('bitmap', (size, 64, 64, 1), dtype='uint8')
dset_tagcode = grp.create_dataset('tagcode', (size, 1), dtype='uint16')
sample_num = 0
for i, (bitmap, tagcode) in enumerate(utils.read_gnt_in_directory(dirpath)):
dset_bitmap[i] = utils.normalize_bitmap(bitmap)
dset_tagcode[i] = tagcode
sample_num += 1
print("Sample Number: {0}".format(sample_num))
#!/usr/bin/env python
# This script can be used to see how bitmaps will be preprocessed before
# subsetting the CASIA HWDB1.1 data set
import sys
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import numpy as np
import utils
if len(sys.argv) != 2:
print 'Usage: %s gnt_dirpath' % sys.argv[0]
exit()
gnt_dirpath = sys.argv[1]
for i, (bitmap,
tagcode) in enumerate(utils.read_gnt_in_directory(gnt_dirpath)):
print utils.tagcode_to_unicode(tagcode).encode(
'utf-8') # wrong terminal encoding = garbage
proc_bitmap = utils.normalize_bitmap(bitmap)
proc_bitmap = utils.preprocess_bitmap(proc_bitmap)
plt.subplot(121)
plt.imshow(bitmap, cmap=cm.Greys_r)
plt.subplot(122)
plt.imshow(np.squeeze(proc_bitmap, axis=0), cmap=cm.Greys_r)
plt.show()
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# This script counts the characters of the CASIA HWDB1.1 data set
import sys
from collections import Counter, defaultdict
import utils
if len(sys.argv) != 3:
print('Usage: %s trn_dirpath tst_dirpath' % sys.argv[0])
exit()
trn_dirpath = sys.argv[1]
tst_dirpath = sys.argv[2]
frequencies = defaultdict(Counter)
for bitmap, tagcode in utils.read_gnt_in_directory(trn_dirpath):
tagcode_unicode = utils.tagcode_to_unicode(tagcode)
frequencies[tagcode_unicode].update(trn=1)
for bitmap, tagcode in utils.read_gnt_in_directory(tst_dirpath):
tagcode_unicode = utils.tagcode_to_unicode(tagcode)
frequencies[tagcode_unicode].update(tst=1)
with open('frequencies.txt', 'w') as f:
for k, v in sorted(frequencies.items(),
key=lambda k_v: k_v[1]['trn'],
reverse=True):
f.write('%s: %d, %d\n' % (k.encode('utf-8'), v['trn'], v['tst']))
#!/usr/bin/env python2
# This script can be used to see how bitmaps will be preprocessed before
# subsetting the CASIA HWDB1.1 data set
import sys
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import numpy as np
import utils
if len(sys.argv) != 2:
print 'Usage: %s gnt_dirpath' % sys.argv[0]
exit()
gnt_dirpath = sys.argv[1]
for i, (bitmap, tagcode) in enumerate(utils.read_gnt_in_directory(gnt_dirpath)):
print utils.tagcode_to_unicode(tagcode).encode('utf-8') # wrong terminal encoding = garbage
proc_bitmap = utils.normalize_bitmap(bitmap)
proc_bitmap = utils.preprocess_bitmap(proc_bitmap)
plt.subplot(121)
plt.imshow(bitmap, cmap=cm.Greys_r)
plt.subplot(122)
plt.imshow(np.squeeze(proc_bitmap, axis=0), cmap=cm.Greys_r)
plt.show()
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import sys
import h5py
import utils
if len(sys.argv) != 3:
print('Usage: %s trn_dirpath tst_dirpath' % sys.argv[0])
sys.exit(1)
trn_dirpath = sys.argv[1]
tst_dirpath = sys.argv[2]
with h5py.File('HWDB1.1.hdf5', 'w') as f:
for name, size, dirpath in [('trn', 897758, trn_dirpath), ('tst', 223991, tst_dirpath)]:
print('Converting \'%s\'...' % name)
grp = f.create_group(name)
dset_bitmap = grp.create_dataset('bitmap', (size, 1, 64, 64), dtype='uint8')
dset_tagcode = grp.create_dataset('tagcode', (size, 1), dtype='uint16')
for i, (bitmap, tagcode) in enumerate(utils.read_gnt_in_directory(dirpath)):
dset_bitmap[i] = utils.normalize_bitmap(bitmap)
dset_tagcode[i] = tagcode
import sys
import h5py
import utils
if len(sys.argv) != 3:
print('Usage: %s trn_dirpath tst_dirpath' % sys.argv[0])
sys.exit(1)
trn_dirpath = sys.argv[1]
tst_dirpath = sys.argv[2]
with h5py.File('HWDB1.1.hdf5', 'w') as f:
for name, size, dirpath in [('trn', 897758, trn_dirpath),
('tst', 223991, tst_dirpath)]:
print('Converting \'%s\'...' % name)
grp = f.create_group(name)
dset_bitmap = grp.create_dataset('bitmap', (size, 1, 64, 64),
dtype='uint8')
dset_tagcode = grp.create_dataset('tagcode', (size, 1), dtype='uint16')
dset_writercode = grp.create_dataset('writercode', (size, 1),
dtype='uint16')
for i, (bitmap, tagcode,
writercode) in enumerate(utils.read_gnt_in_directory(dirpath)):
dset_bitmap[i] = utils.normalize_bitmap(bitmap)
dset_tagcode[i] = tagcode
dset_writercode[i] = writercode
#!/usr/bin/env python2
# This script counts the characters of the CASIA HWDB1.1 data set
import sys
from collections import Counter, defaultdict
import utils
if len(sys.argv) != 3:
print 'Usage: %s trn_dirpath tst_dirpath' % sys.argv[0]
exit()
trn_dirpath = sys.argv[1]
tst_dirpath = sys.argv[2]
frequencies = defaultdict(Counter)
for bitmap, tagcode in utils.read_gnt_in_directory(trn_dirpath):
tagcode_unicode = utils.tagcode_to_unicode(tagcode)
frequencies[tagcode_unicode].update(trn=1)
for bitmap, tagcode in utils.read_gnt_in_directory(tst_dirpath):
tagcode_unicode = utils.tagcode_to_unicode(tagcode)
frequencies[tagcode_unicode].update(tst=1)
with open('frequencies.txt', 'w') as f:
for k, v in sorted(frequencies.iteritems(), key=lambda (k, v): v['trn'], reverse=True):
f.write('%s: %d, %d\n' % (k.encode('utf-8'), v['trn'], v['tst']))
