Spaces:
Running
on
A10G
Running
on
A10G
import os | |
import numpy as np | |
import requests | |
import yaml | |
import pyloudnorm as pyln | |
from scipy.io.wavfile import write | |
import torchaudio | |
from retrying import retry | |
os.environ['OPENBLAS_NUM_THREADS'] = '1' | |
SAMPLE_RATE = 32000 | |
with open('config.yaml', 'r') as file: | |
config = yaml.safe_load(file) | |
service_port = config['Service-Port'] | |
enable_sr = config['Speech-Restoration']['Enable'] | |
def LOUDNESS_NORM(audio, sr=32000, volumn=-25): | |
# peak normalize audio to -1 dB | |
peak_normalized_audio = pyln.normalize.peak(audio, -10.0) | |
# measure the loudness first | |
meter = pyln.Meter(sr) # create BS.1770 meter | |
loudness = meter.integrated_loudness(peak_normalized_audio) | |
# loudness normalize audio to -12 dB LUFS | |
normalized_audio = pyln.normalize.loudness(peak_normalized_audio, loudness, volumn) | |
return normalized_audio | |
def WRITE_AUDIO(wav, name=None, sr=SAMPLE_RATE): | |
""" | |
function: write audio numpy to .wav file | |
@params: | |
wav: np.array [samples] | |
""" | |
if name is None: | |
name = 'output.wav' | |
if len(wav.shape) > 1: | |
wav = wav[0] | |
# declipping | |
max_value = np.max(np.abs(wav)) | |
if max_value > 1: | |
wav *= 0.9 / max_value | |
# write audio | |
write(name, sr, np.round(wav*32767).astype(np.int16)) | |
def READ_AUDIO_NUMPY(wav, sr=SAMPLE_RATE): | |
""" | |
function: read audio numpy | |
return: np.array [samples] | |
""" | |
waveform, sample_rate = torchaudio.load(wav) | |
if sample_rate != sr: | |
waveform = torchaudio.functional.resample(waveform, orig_freq=sample_rate, new_freq=sr) | |
wav_numpy = waveform[0].numpy() | |
return wav_numpy | |
def MIX(wavs=[['1.wav', 0.], ['2.wav', 10.]], out_wav='out.wav', sr=SAMPLE_RATE): | |
""" | |
wavs:[[wav_name, absolute_offset], ...] | |
""" | |
max_length = max([int(wav[1]*sr + len(READ_AUDIO_NUMPY(wav[0]))) for wav in wavs]) | |
template_wav = np.zeros(max_length) | |
for wav in wavs: | |
cur_name, cur_offset = wav | |
cur_wav = READ_AUDIO_NUMPY(cur_name) | |
cur_len = len(cur_wav) | |
cur_offset = int(cur_offset * sr) | |
# mix | |
template_wav[cur_offset:cur_offset+cur_len] += cur_wav | |
WRITE_AUDIO(template_wav, name=out_wav) | |
def CAT(wavs, out_wav='out.wav'): | |
""" | |
wavs: List of wav file ['1.wav', '2.wav', ...] | |
""" | |
wav_num = len(wavs) | |
segment0 = READ_AUDIO_NUMPY(wavs[0]) | |
cat_wav = segment0 | |
if wav_num > 1: | |
for i in range(1, wav_num): | |
next_wav = READ_AUDIO_NUMPY(wavs[i]) | |
cat_wav = np.concatenate((cat_wav, next_wav), axis=-1) | |
WRITE_AUDIO(cat_wav, name=out_wav) | |
def COMPUTE_LEN(wav): | |
wav= READ_AUDIO_NUMPY(wav) | |
return len(wav) / 32000 | |
def TTM(text, length=10, volume=-28, out_wav='out.wav'): | |
url = f'http://127.0.0.1:{service_port}/generate_music' | |
data = { | |
'text': f'{text}', | |
'length': f'{length}', | |
'volume': f'{volume}', | |
'output_wav': f'{out_wav}', | |
} | |
response = requests.post(url, json=data) | |
if response.status_code == 200: | |
print('Success:', response.json()['message']) | |
else: | |
print('Error:', response.json()['API error']) | |
raise RuntimeError(response.json()['API error']) | |
def TTA(text, length=5, volume=-35, out_wav='out.wav'): | |
url = f'http://127.0.0.1:{service_port}/generate_audio' | |
data = { | |
'text': f'{text}', | |
'length': f'{length}', | |
'volume': f'{volume}', | |
'output_wav': f'{out_wav}', | |
} | |
response = requests.post(url, json=data) | |
if response.status_code == 200: | |
print('Success:', response.json()['message']) | |
else: | |
print('Error:', response.json()['API error']) | |
raise RuntimeError(response.json()['API error']) | |
def TTS(text, speaker='news_anchor', volume=-20, out_wav='out.wav', enhanced=enable_sr, speaker_id='', speaker_npz=''): | |
url = f'http://127.0.0.1:{service_port}/generate_speech' | |
data = { | |
'text': f'{text}', | |
'speaker_id': f'{speaker_id}', | |
'speaker_npz': f'{speaker_npz}', | |
'volume': f'{volume}', | |
'output_wav': f'{out_wav}', | |
} | |
response = requests.post(url, json=data) | |
if response.status_code == 200: | |
print('Success:', response.json()['message']) | |
else: | |
print('Error:', response.json()['API error']) | |
raise RuntimeError(response.json()['API error']) | |
if enhanced: | |
SR(processfile=out_wav) | |
def SR(processfile): | |
url = f'http://127.0.0.1:{service_port}/fix_audio' | |
data = {'processfile': f'{processfile}'} | |
response = requests.post(url, json=data) | |
if response.status_code == 200: | |
print('Success:', response.json()['message']) | |
else: | |
print('Error:', response.json()['API error']) | |
raise RuntimeError(response.json()['API error']) | |
def VP(wav_path, out_dir): | |
url = f'http://127.0.0.1:{service_port}/parse_voice' | |
data = { | |
'wav_path': f'{wav_path}', | |
'out_dir':f'{out_dir}' | |
} | |
response = requests.post(url, json=data) | |
if response.status_code == 200: | |
print('Success:', response.json()['message']) | |
else: | |
print('Error:', response.json()['API error']) | |
raise RuntimeError(response.json()['API error']) | |