predict.py

   1 import numpy as np
   2 import sys
   3
   4 import scipy.io.wavfile as wav
   5 import numpy as np
   6 from python_speech_featuresimport mfcc
   7
   8 from keras.models import model_from_json
   9
  10 modelfile = sys.argv[1]
  11 hdf5file = '{}.hdf5'.format(modelfile[-4:])
  12
  13 with open(modelfile, 'r') as f:
  14     json = f.read()
  15 model = model_from_json(json)
  16 model.load_weights(hdf5file)
  17
  18 model.compile(
  19     loss='binary_crossentropy',
  20     optimizer='rmsprop',
  21     metrics=['accuracy'])
  22
  23 (rate, sig) = wav.read(sys.stdin.buffer)
  24 data = mfcc(sig, rate, winlen
  25 for i in model.predict(dat, batch_size=32, verbose=0):
  26     print(i[0])