def __init__(self, model_path):
self.identifer = libtrate.DoubleIdentifer()
self.identifer.Load(model_path + '/identifer.bin')
self.predictor = Predictor()
self.predictor.load(model_path)
self.normalizer = libnormalizer.NormalizerFactory().Load(model_path + '/normalizer.bin')
from libcalibrator import CalibratorFactory
self.calibrator = CalibratorFactory.Load(model_path + '/calibrator.bin')
Segmentor.Init()
def __init__(self, model_path, predictor_path):
self.identifer = libtrate.DoubleIdentifer()
self.identifer.Load(model_path + '/identifer.bin')
#self.predictor = libtrate.LinearPredictor()
#self.predictor.Load(predictor_path)
self.predictor = libtrate.PredictorFactory.LoadPredictor(
predictor_path)
self.dnn_predictor = DnnPredictor()
self.dnn_predictor.load(model_path)
self.normalizer = None
if self.predictor == None:
self.normalizer = libnormalizer.NormalizerFactory().Load(
'./normalizer.bin')
else:
self.normalizer = self.predictor.GetNormalizer()
from libcalibrator import CalibratorFactory
self.calibrator = CalibratorFactory.Load(model_path +
'/calibrator.bin')
Segmentor.Init()
#pid = 82069969465
pid = 82069968445
pid = 82073369485
pid = 82154598133
info = libtieba.get_post_info(pid)
print info.title, ' ', info.content
import libtrate
identifer = libtrate.DoubleIdentifer()
#identifer.Load('./data/ltrate.thread.model/identifer.bin')
identifer.Load('./ltrate.thread.model/identifer.bin')
print identifer.size()
print identifer.id('工程')
#normalizer = libtrate.NormalizerFactory.CreateNormalizer('minmax', './data/ltrate.thread.model/normalizer.bin')
#normalizer = libnormalizer.NormalizerFactory.Load('./data/ltrate.thread.model/normalizer.bin')
normalizer = libnormalizer.NormalizerFactory.Load('./ltrate.thread.model/normalizer.bin')
#lpredictor = libtrate.PredictorFactory.LoadPredictor('./data/ltrate.thread.model/')
lpredictor = libtrate.PredictorFactory.LoadPredictor('./ltrate.thread.model/')
from libcalibrator import CalibratorFactory
calibrator = CalibratorFactory.Load('./model/calibrator.bin')