def test_file(model_path, test_file_path):
"""Test model
test file format
今 B
晚 E
月 B
色 E
真 S
美 S
。 S
<MUST SEPERATE BY SPACE LINE>
我 S
output file format
今 B preTag
晚 E preTag
"""
if not os.path.isfile(model_path) or not os.path.isfile(test_file_path):
print("File don't exist!")
model = LinearCRF()
model.load(model_path)
f = codecs.open(test_file_path, 'r', encoding='utf-8')
lines = f.readlines()
f.close()
sentences = []
labels = []
sentence = []
label = []
for line in lines:
if len(line) < 2:
# sentence end
sentences.append(sentence)
labels.append(label)
sentence = []
label = []
else:
char, tag = line.split()
sentence.append(char)
label.append(tag)
pre_tags = [model.inference_viterbi(sen) for sen in sentences]
with open('test_result.txt', 'w+') as f:
for sen, sen_tag, sen_pre in zip(sentences, labels, pre_tags):
for i in range(len(sen)):
f.write('{}\t{}\t{}\n'.format(sen[i], sen_tag[i], sen_pre[i]))
f.write('\n')
print('Test finished!')
class Segmentation(object):
def __init__(self, model_path='model/linear_crf.model'):
self.model = LinearCRF()
self.model.load(model_path)
def seg(self, sentence):
sentence.strip()
tags = self.model.inference_viterbi(sentence)
str_seg = ""
for word, tag in zip(sentence, tags):
str_seg += word
if tag == 'S' or tag == 'E':
str_seg += ' '
result = str_seg.split()
return result