试图将mp3文件转换为Numpy数组，而ffmpeg只是挂起

Question

我正在使用Scikit-learn研究音乐分类方法，该过程的第一步是将音乐文件转换为numpy数组。

在尝试从python脚本调用ffmpeg失败后，我决定直接通过管道将文件导入:

FFMPEG_BIN = "ffmpeg"
cwd = (os.getcwd())
dcwd = (cwd + "/temp")
if not os.path.exists(dcwd): os.makedirs(dcwd)
folder_path = sys.argv[1]
f = open("test.txt","a")
for f in glob.glob(os.path.join(folder_path, "*.mp3")):
    ff = f.replace("./", "/")
    print("Name: " + ff)
    aa = (cwd + ff)
    command = [ FFMPEG_BIN,
        '-i',  aa,
        '-f', 's16le',
        '-acodec', 'pcm_s16le',
        '-ar', '22000', # ouput will have 44100 Hz
        '-ac', '1', # stereo (set to '1' for mono)
        '-']
    pipe = sp.Popen(command, stdout=sp.PIPE, bufsize=10**8)
    raw_audio = pipe.proc.stdout.read(88200*4)
    audio_array = numpy.fromstring(raw_audio, dtype="int16")
    print (str(audio_array))
    f.write(audio_array + "n")

问题是，当我运行文件时，它启动ffmpeg，然后什么也不做:

[mp3 @ 0x1446540] Estimating duration from bitrate, this may be inaccurate
Input #0, mp3, from '/home/don/Code/Projects/MC/Music/Spaz.mp3':
  Metadata:
    title           : Spaz
    album           : Seeing souns
    artist          : N*E*R*D
    genre           : Hip-Hop
    encoder         : Audiograbber 1.83.01, LAME dll 3.96, 320 Kbit/s, Joint Stereo, Normal quality
    track           : 5/12
    date            : 2008
  Duration: 00:03:50.58, start: 0.000000, bitrate: 320 kb/s
    Stream #0:0: Audio: mp3, 44100 Hz, stereo, s16p, 320 kb/s
Output #0, s16le, to 'pipe:':
  Metadata:
    title           : Spaz
    album           : Seeing souns
    artist          : N*E*R*D
    genre           : Hip-Hop
    date            : 2008
    track           : 5/12
    encoder         : Lavf56.4.101
    Stream #0:0: Audio: pcm_s16le, 22000 Hz, mono, s16, 352 kb/s
    Metadata:
      encoder         : Lavc56.1.100 pcm_s16le
Stream mapping:
  Stream #0:0 -> #0:0 (mp3 (native) -> pcm_s16le (native))
Press [q] to stop, [?] for help

它只是坐在那里，悬着，比歌曲的时间长得多。我哪里做错了?

Answer 1

我推荐您使用pymedia或audioread或decoder.py。也有pyffmpeg和类似的模块可以做您想做的事情。看一下pypi.python.org。

当然，这些不能帮助您将数据转换为numpy数组。

无论如何，这就是如何使用管道来完成ffmpeg:

from subprocess import Popen, PIPE
import numpy as np
def decode (fname):
    # If you are on Windows use full path to ffmpeg.exe
    cmd = ["./ffmpeg.exe", "-i", fname, "-f", "wav", "-"]
    # If you are on W add argument creationflags=0x8000000 to prevent another console window jumping out
    p = Popen(cmd, stdin=PIPE, stdout=PIPE, stderr=PIPE)
    data = p.communicate()[0]
    return np.fromstring(data[data.find("data")+4:], np.int16)

基本使用时应该是这样的

它应该工作，因为ffmpeg的输出默认是16位音频。但是如果你搞混了，你应该知道numpy没有int24，所以你将被迫做一些位操作，并将24位音频表示为32位音频。只是，不用24位，世界就幸福了。: D

如果你需要更复杂的东西，我们可以讨论在注释中改进代码。

Answer 2

我使用的是:它使用pydub(它使用ffmpeg)和scipy。

完整设置(在Mac上，可能与其他系统不同):

pip install scipy
pip install pydub
brew install ffmpeg  # Or probably "sudo apt-get install ffmpeg on linux"

然后读mp3:

import tempfile
import os
import pydub
import scipy
import scipy.io.wavfile

def read_mp3(file_path, as_float = False):
    """
    Read an MP3 File into numpy data.
    :param file_path: String path to a file
    :param as_float: Cast data to float and normalize to [-1, 1]
    :return: Tuple(rate, data), where
        rate is an integer indicating samples/s
        data is an ndarray(n_samples, 2)[int16] if as_float = False
            otherwise ndarray(n_samples, 2)[float] in range [-1, 1]
    """
    path, ext = os.path.splitext(file_path)
    assert ext=='.mp3'
    mp3 = pydub.AudioSegment.from_mp3(file_path)
    _, path = tempfile.mkstemp()
    mp3.export(path, format="wav")
    rate, data = scipy.io.wavfile.read(path)
    os.remove(path)
    if as_float:
        data = data/(2**15)
    return rate, data

来源:James Thompson的博客