计算帧中的FFT并写入文件 [英] calculating FFT in frames and writing to a file
本文介绍了计算帧中的FFT并写入文件的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我是python的新手,我正在尝试获取上载的wav文件的FFT值,并返回文本文件每行中每帧的FFT(使用GCP)
I'm new to python,I'm trying get a FFT value of a uploaded wav file and return the FFT of each frame in each line of a text file (using GCP)
使用scipy或librosa
using scipy or librosa
我需要的帧速率为30fps
Frame rate i require is 30fps
wave文件的采样率为48k
wave file will be of 48k sample rate
所以我的问题是
- 如何将整个wav文件的样本划分为每一帧的样本
-
如何添加空白样本以使帧样本的长度为2的幂(如48000/30 = 1600,添加448个空白样本以使其为2048) - 如何将得到的FFT数组归一化为[-1,1]?
推荐答案
您可以将pyaudio与回调一起使用,以实现所执行的操作.
You can use pyaudio with callback to acheive whatever you are doing.
import pyaudio
import wave
import time
import struct
import sys
import numpy as np
if len(sys.argv) < 2:
print("Plays a wave file.\n\nUsage: %s filename.wav" % sys.argv[0])
sys.exit(-1)
wf = wave.open(sys.argv[1], 'rb')
# instantiate PyAudio (1)
p = pyaudio.PyAudio()
def callback_test(data, frame_count, time_info, status):
frame_count =1024
elm = wf.readframes(frame_count) # read n frames
da_i = np.frombuffer(elm, dtype='<i2') # convert to little endian int pairs
da_fft = np.fft.rfft(da_i) # fast fourier transform for real values
da_ifft = np.fft.irfft(da_fft) # inverse fast fourier transform for real values
da_i = da_ifft.astype('<i2') # convert to little endian int pairs
da_m = da_i.tobytes() # convert to bytes
return (da_m, pyaudio.paContinue)
# open stream using callback (3)
stream = p.open(format=p.get_format_from_width(wf.getsampwidth()),
channels=wf.getnchannels(),
rate=wf.getframerate(),# sampling frequency
output=True,
stream_callback=callback_test)
# # start the stream (4)
stream.start_stream()
# # wait for stream to finish (5)
while stream.is_active():
time.sleep(0.1)
# # stop stream (6)
stream.stop_stream()
stream.close()
wf.close()
# close PyAudio (7)
p.terminate()
请参考以下链接进行进一步研究:
Please refer these links for further study:
https://people.csail.mit.edu/hubert/pyaudio/docs/#example-callback-mode-audio-io 和 Python更改wav文件的音高
这篇关于计算帧中的FFT并写入文件的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!
查看全文