encodesound.py

import glob, os
import soundfile as sf
from math import sqrt
from scipy.io.wavfile import read as wavread
import matplotlib.pyplot as plt
from scipy import signal
import pandas as pd


from scipy.signal import butter, lfilter, freqz

FILE_FORMAT = "wav"
def extract_audio():
    for video in glob.glob("videos/P*/*/*.avi"):
        f = video[:-3] + FILE_FORMAT
        # print(f)
        os.system("ffmpeg -v 0 -y -i "+video+" -f "+FILE_FORMAT+" -ar 10000 -vn "+f)

def read_audio():
    l = []
    for audio in glob.glob("videos/P*/*/*."+FILE_FORMAT):
        data, samplerate = sf.read(audio)

        # First, design the Buterworth filter
        N  = 3    # Filter order
        Wn = 0.1 # Cutoff frequency
        B, A = signal.butter(N, Wn, output='ba')
        smooth_data = signal.filtfilt(B,A, data)

        smooth_data = pd.rolling_mean(data, 10)
        plt.plot(data, 'b')

        plt.plot(smooth_data, 'r')
        # print(audio[:-4]+"_smooth.wav")
        # sf.write(audio[:-4]+"_smooth.wav", smooth_data, samplerate)
        # plt.savefig(audio[:-3]+"png")
        plt.show()
        # plt.clf()
        l.append(data.shape[0])

    av = sum(l)/len(l)
    s = 0

    for x in l:
        s += sqrt((x - av)**2)

    print(max(l), min(l), av, s/len(l))

# extract_audio()
read_audio()