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import os, fnmatch
import numpy as np
import random
import soundfile as sf
from scipy.io.wavfile import write
# import librosa
import RT60
folder_path = "/cephfs/anton/room-impulse-responses/AIR/RWCP_REVERB_AACHEN/real_rirs_isotropic_noises/"
final_path = "/cephfs/anton/room-impulse-responses/AIR/RWCP_REVERB_AACHEN/AACHEN/"
tfs =16000
file_label = open("RT60.txt","w")
for root, dirnames, filenames in os.walk(folder_path):
for filename in filenames:
if filename.endswith(".wav"):
ACE_Path = os.path.join(root, filename)
wave,fs = sf.read(ACE_Path)
channel = int(wave.size/len(wave))
if(channel == 1):
wave_single = wave #librosa.resample(wave, fs, tfs)
max_loc = np.where(wave_single == np.amax(wave_single))
min_loc = np.where(wave_single == np.amin(wave_single))
start = min(max_loc[0][0],min_loc[0][0])
wave_single =wave_single[start:len(wave_single)]
T60_val = RT60.t60_impulse(wave_single,tfs)
if(T60_val<1):
file_label.write(str(T60_val)+"\n")
save_path = final_path+ filename
write(save_path,tfs,wave_single.astype(np.float32))
else:
for n in range(channel):
wave_single = wave[:,n]#librosa.resample(wave[:,n], fs, tfs)
max_loc = np.where(wave_single == np.amax(wave_single))
min_loc = np.where(wave_single == np.amin(wave_single))
start = min(max_loc[0][0],min_loc[0][0])
wave_single =wave_single[start:len(wave_single)]
T60_val = RT60.t60_impulse(wave_single,tfs)
if(T60_val<1):
file_label.write(str(T60_val)+"\n")
save_path = final_path+filename+str(n)+".wav"
write(save_path,tfs,wave_single.astype(np.float32))
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