from speech_siamese import siamese_model
from record_mic_speech import record_spectrogram
from importlib import reload
# import speech_data
# reload(speech_data)
from speech_data import create_test_pair,get_word_pairs_data,speech_data
import numpy as np

model = siamese_model((15, 1654))
model.load_weights('./models/siamese_speech_model-final.h5')

def predict_recording_with(m,sample_size=15):
    spec1 = record_spectrogram(n_sec=1.4)
    spec2 = record_spectrogram(n_sec=1.4)
    inp = create_test_pair(spec1,spec2,sample_size)
    return m.predict([inp[:, 0], inp[:, 1]])

# while(True):
#     print(predict_recording_with(model))


def test_with(audio_group):
    X,Y = speech_data(audio_group)
    print(np.argmax(model.predict([X[:, 0], X[:, 1]]),axis=1))
    print(Y.astype(np.int8))

test_with('rand_edu')
# sunflower_data,sunflower_result = get_word_pairs_data('sweater',15)
# print(np.argmax(model.predict([sunflower_data[:, 0], sunflower_data[:, 1]]),axis=1))
# print(sunflower_result)