def validate_with_metrics(self, net, eval_loader):
print(
'********** Started metrics evaluation on validation set ********')
accu_stoi = 0.0
accu_pesq = 0.0
accu_snr = 0.0
net.eval()
with torch.no_grad():
mtime = 0.
ttime = 0.
count = 0.
for k, (mix_raw, cln_raw) in enumerate(eval_loader):
start = timeit.default_timer()
est_s = self.eval_forward(mix_raw,
net) # <class 'tuple'>: (70656,)
est_s = est_s[:mix_raw.size] # <class 'tuple'>: (70537,)
ideal_s = cln_raw # <class 'tuple'>: (70537,)
# 主要就是得到est_s和ideal_s，把他俩能逆变换成语音，注意cln_raw
st = stoi(cln_raw, est_s, self.srate)
sn = snr(cln_raw, est_s)
accu_stoi += st
accu_snr += sn
est_path = os.path.join(self.wav_path,
'{}_est.wav'.format(k + 1))
ideal_path = os.path.join(self.wav_path,
'{}_ideal.wav'.format(k + 1))
sf.write(est_path, normalize_wav(est_s)[0], self.srate)
sf.write(ideal_path, normalize_wav(ideal_s)[0], self.srate)
pe = getPESQ(self.tool_path, ideal_path, est_path)
accu_pesq += pe
count += 1
# print('{}, STOI: {:.4f}, SNR: {:.4f}, PESQ: {:.4f}'.format(k+1, st, sn, pe))
avg_stoi = accu_stoi / count
avg_snr = accu_snr / count
avg_pesq = accu_pesq / count
net.train()
return avg_stoi, avg_snr, avg_pesq
def getSTOI(self):
for i in range(len(self.assess_list)):
#print '\n[%d/%d] Assess on %s...' % ((i+1),len(self.assess_list), self.assess_list[i])
start1 = timeit.default_timer()
print('')
print('{}/{}, Started assess on {} ...'.format(i+1, len(self.assess_list), self.assess_list[i]))
print('')
f_mix = h5py.File(os.path.join(self.test_mixture_path, self.assess_list[i]+'_mix.dat'), 'r')
f_s = h5py.File(os.path.join(self.test_mixture_path, self.assess_list[i]+'_s.dat'), 'r')
f_est_s = h5py.File(os.path.join(self.prediction_path, self.assess_list[i]+'_s_est.dat'), 'r')
f_ideal_s = h5py.File(os.path.join(self.prediction_path, self.assess_list[i]+'_s_ideal.dat'), 'r')
# create arrays for stoi and snr
est_stoi_s_accu = 0.0
ideal_stoi_s_accu = 0.0
mix_stoi_s_accu = 0.0
est_snr_s_accu = 0.0
ideal_snr_s_accu = 0.0
mix_snr_s_accu = 0.0
for j in range(self.num_test_sentences):
mix = f_mix[str(j)][:]
s = f_s[str(j)][:]
est_s = f_est_s[str(j)][:]
ideal_s = f_ideal_s[str(j)][:]
# compute stoi
est_stoi_s = stoi(s, est_s, self.srate)
ideal_stoi_s = stoi(s, ideal_s, self.srate)
mix_stoi_s = stoi(s, mix, self.srate)
# compute snr
est_snr_s = snr(s, est_s)
ideal_snr_s = snr(s, ideal_s)
mix_snr_s = snr(s, mix)
# compute accu of them
est_stoi_s_accu += est_stoi_s
ideal_stoi_s_accu += ideal_stoi_s
mix_stoi_s_accu += mix_stoi_s
est_snr_s_accu += est_snr_s
ideal_snr_s_accu += ideal_snr_s
mix_snr_s_accu += mix_snr_s
print('#' * 5)
print('{}/{}, mix_stoi = {:.4f}, ideal_stoi = {:.4f}, est_stoi = {:.4f}'.format(j +1,
self.num_test_sentences,
mix_stoi_s,
ideal_stoi_s,
est_stoi_s))
print('{}/{}, mix_snr = {:.4f}, ideal_snr = {:.4f}, est_snr = {:.4f}'.format(j+1, self.num_test_sentences,
mix_snr_s,
ideal_snr_s,
est_snr_s))
mix_norm, scale_mix = normalize_wav(mix)
est_s_norm, scale_est_s = normalize_wav(est_s)
ideal_s_norm, scale_ideal_s = normalize_wav(ideal_s)
s_norm, scale_s = normalize_wav(s)
# save them into wav files
filepath = os.path.join(self.wav_path, self.assess_list[i])
if not os.path.isdir(filepath):
os.makedirs(filepath)
filename_mix = '%d_mix.wav' % (j)
filename_s_est = '%d_s_est.wav' % (j)
filename_s_ideal = '%d_s_ideal.wav' % (j)
filename_s = '%d_s.wav' % (j)
sf.write(os.path.join(filepath, filename_mix), mix_norm,int(self.srate))
sf.write(os.path.join(filepath, filename_s_est), est_s_norm,int(self.srate))
sf.write(os.path.join(filepath, filename_s_ideal), ideal_s_norm,int(self.srate))
sf.write(os.path.join(filepath, filename_s), s_norm,int(self.srate))
#bar.finish()
f_mix.close()
f_s.close()
f_est_s.close()
f_ideal_s.close()
mix_stoi_s_ave = mix_stoi_s_accu / float(self.num_test_sentences)
ideal_stoi_s_ave = ideal_stoi_s_accu / float(self.num_test_sentences)
est_stoi_s_ave = est_stoi_s_accu / float(self.num_test_sentences)
mix_snr_s_ave = mix_snr_s_accu / float(self.num_test_sentences)
ideal_snr_s_ave = ideal_snr_s_accu / float(self.num_test_sentences)
est_snr_s_ave = est_snr_s_accu / float(self.num_test_sentences)
end1 = timeit.default_timer()
print('')
print('{}/{}, Finished assess on {}. time taken = {:.4f}'.format(i+1, len(self.assess_list),
self.assess_list[i], end1 - start1))
print('')
print('#'*100)
print('#'*100)
print('mix_stoi: %.4f | ideal_stoi: %.4f | mix_stoi: %.4f' % (mix_stoi_s_ave, ideal_stoi_s_ave, est_stoi_s_ave))
print('mix_snr: %.2f | ideal_snr: %.2f | mix_snr: %.2f' % (mix_snr_s_ave, ideal_snr_s_ave, est_snr_s_ave))
print('#'*100)
print('#'*100)