first commit

APIs.py

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+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
+from utils import get_service_port, get_service_url
+
+
+os.environ['OPENBLAS_NUM_THREADS'] = '1'
+SAMPLE_RATE = 32000
+
+
+with open('config.yaml', 'r') as file:
+    config = yaml.safe_load(file)
+    service_port = get_service_port()
+    localhost_addr = get_service_url()
+    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
+
+
+@retry(stop_max_attempt_number=5, wait_fixed=2000)
+def TTM(text, length=10, volume=-28, out_wav='out.wav'):
+    url = f'http://{localhost_addr}:{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'])
+
+@retry(stop_max_attempt_number=5, wait_fixed=2000)
+def TTA(text, length=5, volume=-35, out_wav='out.wav'):
+    url = f'http://{localhost_addr}:{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'])
+
+
+@retry(stop_max_attempt_number=5, wait_fixed=2000)
+def TTS(text, volume=-20, out_wav='out.wav', enhanced=enable_sr, speaker_id='', speaker_npz=''):
+    url = f'http://{localhost_addr}:{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)
+
+
+@retry(stop_max_attempt_number=5, wait_fixed=2000)
+def SR(processfile):
+    url = f'http://{localhost_addr}:{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'])
+
+
+@retry(stop_max_attempt_number=5, wait_fixed=2000)
+def VP(wav_path, out_dir):
+    url = f'http://{localhost_addr}:{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'])
+