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Split an audio file into multiple files based on detected onsets from librosa.
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#!/usr/bin/env python | |
import argparse | |
import matplotlib.pyplot as plt | |
import librosa | |
import numpy as np | |
import os | |
from progressbar import ProgressBar | |
parser = argparse.ArgumentParser( | |
description='Split audio into multiple files and save analysis.') | |
parser.add_argument('-i', '--input', type=str) | |
parser.add_argument('-o', '--output', type=str, default='transients') | |
parser.add_argument('-s', '--sr', type=int, default=44100) | |
args = parser.parse_args() | |
y, sr = librosa.load(args.input, sr=args.sr) | |
o_env = librosa.onset.onset_strength(y, sr=sr, feature=librosa.cqt) | |
onset_frames = librosa.onset.onset_detect(onset_envelope=o_env, sr=sr) | |
def prepare(y, sr=22050): | |
y = librosa.to_mono(y) | |
y = librosa.util.fix_length(y, sr) # 1 second of audio | |
y = librosa.util.normalize(y) | |
return y | |
def get_fingerprint(y, sr=22050): | |
y = prepare(y, sr) | |
cqt = librosa.cqt(y, sr=sr, hop_length=2048) | |
return cqt.flatten('F') | |
def normalize(x): | |
x -= x.min(axis=0) | |
x /= x.max(axis=0) | |
return x | |
def basename(file): | |
file = os.path.basename(file) | |
return os.path.splitext(file)[0] | |
vectors = [] | |
words = [] | |
filenames = [] | |
onset_samples = list(librosa.frames_to_samples(onset_frames)) | |
onset_samples = np.concatenate(onset_samples, len(y)) | |
starts = onset_samples[0:-1] | |
stops = onset_samples[1:] | |
analysis_folder = args.output | |
samples_folder = os.path.join(args.output, 'samples') | |
try: | |
os.makedirs(samples_folder) | |
except: | |
pass | |
pbar = ProgressBar() | |
for i, (start, stop) in enumerate(pbar(zip(starts, stops))): | |
audio = y[start:stop] | |
filename = os.path.join(samples_folder, str(i) + '.wav') | |
librosa.output.write_wav(filename, audio, sr) | |
vector = get_fingerprint(audio, sr=sr) | |
word = basename(filename) | |
vectors.append(vector) | |
words.append(word) | |
filenames.append(filename) | |
np.savetxt(os.path.join(analysis_folder, 'vectors'), vectors, fmt='%.5f', delimiter='\t') | |
np.savetxt(os.path.join(analysis_folder, 'words'), words, fmt='%s') | |
np.savetxt(os.path.join(analysis_folder, 'filenames.txt'), filenames, fmt='%s') |
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