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audio.py
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audio.py
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import pyaudio
import time
import numpy as np
from matplotlib import pyplot as plt
import scipy.signal as signal
from scipy.fftpack import rfft, irfft, fftfreq
CHANNELS = 1
RATE = 44100
p = pyaudio.PyAudio()
#fulldata = np.array([])
#dry_data = np.array([])
mask=[]
novoarray=[]
def main():
dados=open("dados.txt","r")
dados=dados.read()
print (dados)
dados=dados.split(",")
global filtrob
global filtroa
global efeito
global tempo
filtrob=int(dados[1])
filtroa=int(dados[2])
efeito= int(dados[3])
tempo= int(dados[0])
global lista
global novoarray
l=0
stream = p.open(format=pyaudio.paFloat32,
channels=CHANNELS,
rate=RATE,
output=True,
input=True,
stream_callback=callback)
stream.start_stream()
while stream.is_active():
for i in range(1025):
novoarray.append(0)
time.sleep(tempo)
stream.stop_stream()
stream.close()
#numpydata = np.hstack(fulldata)
#plt.plot(numpydata)
#plt.title("Wet")
#plt.show()
#numpydata = np.hstack(dry_data)
#plt.plot(numpydata)
#plt.title("Dry")
#plt.show()
#p.terminate()
def callback(in_data, frame_count, time_info, flag):
global novoarray
LOWPASS = filtrob # Hz
SAMPLE_RATE = 44100 # Hz
FFT_LENGTH = 2048
OVERLAP = 512
HIGHPASS = filtroa # Hz
FFT_SAMPLE = FFT_LENGTH - OVERLAP
NYQUIST_RATE = SAMPLE_RATE / 2.0
LOWPASS /= (NYQUIST_RATE / (FFT_LENGTH / 2.0))
HIGHPASS /= (NYQUIST_RATE / (FFT_LENGTH / 2.0))
audio_data = np.fromstring(in_data, dtype=np.float32)
novoarray1=np.asarray(novoarray)
freq=fftfreq(1024)
l=len(audio_data)
ff=0
fff=0
for ff in range(0, 1024):
rampdown = 1.0
if ff > LOWPASS:
rampdown = 0.0
elif ff < HIGHPASS:
rampdown = 0.0
mask.append(rampdown)
fff+=1
ff=0
print (len(mask))
x=audio_data.astype(np.float32)
y=rfft(x)
print (y[512])
#print (mask[len(mask)-1])
for ff in range(fff):
y[ff] *= mask[ff]
ff+=1
ff=0
i=0
yy = y.copy()
yy[(freq<0.001)] = 0
N=len(yy)
shifted_freq = np.zeros(N, yy.dtype)
#aqui se altera a voz e cria o efeito distorção
shift=efeito
S = np.round(shift if shift > 0 else N + shift, 0)
s = N - S
shifted_freq[:S] = yy[s:]
shifted_freq[S:] = yy[:s]
z=irfft(shifted_freq)
print(yy)
return (z, pyaudio.paContinue)
main()