1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
#!/usr/bin/python
# The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
#
#
# You need to compile the dlib python interface before you can use this
# file. To do this, run compile_dlib_python_module.bat. You also need to
# have the boost-python library installed. On Ubuntu, this can be done easily by running
# the command: sudo apt-get install libboost-python-dev
# asfd
import dlib
use_sparse_vects = False
if use_sparse_vects:
samples = dlib.sparse_vectorss()
else:
samples = dlib.vectorss()
segments = dlib.rangess()
if use_sparse_vects:
inside = dlib.sparse_vector()
outside = dlib.sparse_vector()
inside.append(dlib.pair(0,1))
outside.append(dlib.pair(1,1))
else:
inside = dlib.vector([0, 1])
outside = dlib.vector([1, 0])
samples.resize(2)
segments.resize(2)
samples[0].append(outside)
samples[0].append(outside)
samples[0].append(inside)
samples[0].append(inside)
samples[0].append(inside)
samples[0].append(outside)
samples[0].append(outside)
samples[0].append(outside)
segments[0].append(dlib.range(2,5))
samples[1].append(outside)
samples[1].append(outside)
samples[1].append(inside)
samples[1].append(inside)
samples[1].append(inside)
samples[1].append(inside)
samples[1].append(outside)
samples[1].append(outside)
segments[1].append(dlib.range(2,6))
params = dlib.segmenter_params()
#params.be_verbose = True
params.window_size = 1
params.use_high_order_features = False
params.C = 1
print "params:", params
df = dlib.train_sequence_segmenter(samples, segments, params)
print len(df.segment_sequence(samples[0]))
print df.segment_sequence(samples[0])[0]
print df.weights
#res = dlib.test_sequence_segmenter(df, samples, segments)
res = dlib.cross_validate_sequence_segmenter(samples, segments, 2, params)
print res