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
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]])

predict_recording_with(model)

sunflower_data,sunflower_result = get_word_pairs_data('sunflowers',15)
sunflower_result
model.predict([sunflower_data[:, 0], sunflower_data[:, 1]]) < 0.5