audiospec.py

import matplotlib.pyplot as plt
import librosa.display
import os
import glob
import numpy as np
#import pandas as pd
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
import librosa
import sys

def save_spectrogram(filename, sample_length):
    """
    filename of wav file
    sample_length in seconds
    """
    y, sr = librosa.load(filename)    
    slen = int(sr * sample_length)
    #if slen < len(y): # requested sample length is larger then the file
    window_size = 1024
    window = np.hanning(window_size)
    for sample_start in range(0, len(y), slen):
        audio_part = y[sample_start:sample_start + slen]
        plt.figure(figsize=(12,5))
        plt.subplot(2, 1, 1)
        X= librosa.stft(audio_part)
        Xdb = librosa.amplitude_to_db(abs(X))
        librosa.display.specshow(X, sr=sr,  y_axis='hz', x_axis='time')

        plt.subplot(2, 1, 2)
        librosa.display.specshow(Xdb, sr=sr,  y_axis='log', x_axis='time')       
        plt.savefig(f"{filename}_{sample_start / sr}.png")

if __name__ == "__main__":
    dirname = sys.argv[1]
    sample_length = float(sys.argv[2])
    files = glob.glob(f"{dirname}/*.wav")
    for	fname in files:
	    save_spectrogram(fname, sample_length)