inference_chunked.py

from keras.models import model_from_json
import keras
import librosa
import numpy as np
from tensorflow.keras import optimizers
import os
import pandas as pd
import librosa
import glob
from pydub import AudioSegment
from pydub.utils import make_chunks

json_file = open('model.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
loaded_model = model_from_json(loaded_model_json)

# load weights into new model
loaded_model.load_weights("saved_models/Emotion_Voice_Detection_Model.h5")
print("Loaded model from disk")

#open a longer file, this one has 20s and was made with AudioRecorder_long.py
audio_path = 'Input5.wav'
myaudio = AudioSegment.from_wav(audio_path)
chunk_length_ms = 4000  # pydub calculates in millisec
chunks = make_chunks(myaudio, chunk_length_ms)  # Make chunks of 4 sec
for i, chunk in enumerate(chunks):
	chunk.export('temporar.wav', format="wav")
	(X, sample_rate) = librosa.load('temporar.wav', res_type='kaiser_fast', duration=2.5, sr=22050*2, offset=0.5, mono=True)
	#X, sample_rate = librosa.load(audio_path, res_type='kaiser_fast',duration=2.5,sr=22050*2,offset=0.5)
	sample_rate = np.array(sample_rate)
	mfccs = np.mean(librosa.feature.mfcc(y=X, sr=sample_rate, n_mfcc=13),axis=0)
	featurelive = mfccs
	livedf2 = featurelive
	#import pandas as pd
	livedf2= pd.DataFrame(data=livedf2)
	livedf2 = livedf2.stack().to_frame().T
	twodim= np.expand_dims(livedf2, axis=2)
	livepreds = loaded_model.predict(twodim, batch_size=32, verbose=1)
	livepreds1=livepreds.argmax(axis=1)
	liveabc = livepreds1.astype(int).flatten()
	#Print chunks
	m, s = divmod(i * 4, 60)
	h, m = divmod(m, 60)
	print(f'At time: {h:d}:{m:02d}:{s:02d}')
  #Labels assigned as per README of main repo.
	if liveabc == 0:
		print("Female_angry")
	elif liveabc == 1:
		print("Female Calm")
	elif liveabc == 2:
		print("Female Fearful")
	elif liveabc == 3:
		print("Female Happy")
	elif liveabc == 4:
		print("Female Sad")
	elif liveabc == 5:
		print("Male Angry")
	elif liveabc == 6:
		print("Male calm")
	elif liveabc == 7:
		print("Male Fearful")
	elif liveabc == 8:
		print("Male Happy")
	elif liveabc == 9:
		print("Male sad")