使用多处理的python pyaudio [英] python pyaudio using multiprocessing
问题描述
我正在尝试从音频流中获取样本，并将其放入共享队列中.我还有另一个从此队列中拉出的进程.
I'm trying to grab samples from a stream of audio and put them in a shared Queue. I have another process that pulls from this queue.
我跑步时出现此错误:
* recording
Traceback (most recent call last):
File "record.py", line 43, in <module>
data = stream.read(CHUNK)
File "/Library/Python/2.7/site-packages/pyaudio.py", line 605, in read
return pa.read_stream(self._stream, num_frames)
IOError: [Errno Input overflowed] -9981
显然问题已经存在了一段时间，没有发布解决方案(我尝试了他们的建议):
Apparently problem has been around for a while with no solution posted (I tried their suggestions):
获取IOError:[设置PyAudio Stream输入和输出为True时Errno输入溢出-9981
(简化)代码在这里:
import pyaudio
import wave
import array
import time
from multiprocessing import Queue, Process
CHUNK = 1024
FORMAT = pyaudio.paInt16
CHANNELS = 2
RATE = 44100
RECORD_SECONDS = 2
p = pyaudio.PyAudio()
left = Queue()
right = Queue()
def other(q1, q2):
while True:
try:
a = q1.get(False)
except Exception:
pass
try:
b = q2.get(False)
except Exception:
pass
stream = p.open(format=FORMAT,
channels=CHANNELS,
rate=RATE,
input=True,
frames_per_buffer=CHUNK)
print("* recording")
Process(target=other, args=(left, right)).start()
for i in range(0, int(RATE / CHUNK * RECORD_SECONDS)):
data = stream.read(CHUNK)
byte_string = ''.join(data)
nums = array.array('h', byte_string)
for elt in nums[1::2]:
left.put(elt)
for elt in nums[0::2]:
right.put(elt)
print("* done recording")
stream.stop_stream()
stream.close()
print "terminated"
我做错了什么?我在Mac OSX和Python 2.7上，我通过homebrew安装了portaudio，并尝试了
What am I doing wrong? I'm on Mac OSX and Python 2.7, I installed portaudio through homebrew and tried both the pip and dmg installation of `pyaudio with no luck with either.
推荐答案
缓冲区溢出错误是因为您的frames_per_buffer和读取的块大小可能太小. 尝试为其设置更大的值，例如512,2048、4096、8192等
The buffer overflow error is because your frames_per_buffer and read chunksize might be too small. Try larger values for them i.e. 512,2048, 4096, 8192 etc
CHUNK = 1024
FORMAT = pyaudio.paInt16
CHANNELS = 2
RATE = 44100
RECORD_SECONDS = 2
for CHUNK1 in [512,2048,4096,8192,16384]:
for CHUNK2 in [512,2048,4096,8192,16384]:
stream = p.open(format=FORMAT,
channels=CHANNELS,
rate=RATE,
input=True,
frames_per_buffer=CHUNK1)
try:
print CHUNK1,CHUNK2
for i in range(0, int(RATE / CHUNK * RECORD_SECONDS)):
data = stream.read(CHUNK2)
except:
print "Boohoo"
stream.stop_stream()
stream.close()
更新
好的，我想我明白了.如果您在下一次读取之前等待了太长时间，则pyaudio库将引发溢出错误.
ok i think I got it. the pyaudio library will raise an overflow error if you wait too long before your next read.
byte_string = ''.join(data)
nums = array.array('h', byte_string)
for elt in nums[1::2]:
left.put(elt)
for elt in nums[0::2]:
right.put(elt)
这在这里做了很多非常慢的处理.尤其是python中的两个for循环.让处理过程可以处理整个单流数据的大块，而不是一次处理一个int.
this does a whole lot of very slow processing here. especially the two for loops which are in python. let the processing process get a whole chunk of mono-stream data which it can deal with instead of one int at a time.
import numpy as np
...
n=np.fromstring(data,np.uint16)
left.put(n[1::2])
right.put(n[0::2])
我什至不想想象for循环对延迟的影响，但是即使相对在使用array和np.array之间的较小性能改进也值得注意:
I don't even want to imagine what the for loops were doing to latency, but even the relatively minor performance improvement between using array and np.array are worth noting:
a=array.array('h',s)
n=np.array(a)
In [26]: %timeit n[1::2]
1000000 loops, best of 3: 669 ns per loop
In [27]: %timeit n[1::2].copy()
1000 loops, best of 3: 725 us per loop
In [28]: %timeit a[1::2]
1000 loops, best of 3: 1.91 ms per loop
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