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363 lines
12 KiB
363 lines
12 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import asyncio
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import base64
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import io
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import json
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import logging
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import os
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import random
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import time
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from typing import List
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import numpy as np
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import requests
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import soundfile
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from ..executor import BaseExecutor
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from ..util import cli_client_register
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from ..util import stats_wrapper
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from paddlespeech.cli.log import logger
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from paddlespeech.server.tests.asr.online.websocket_client import ASRAudioHandler
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from paddlespeech.server.utils.audio_process import wav2pcm
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from paddlespeech.server.utils.util import wav2base64
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__all__ = ['TTSClientExecutor', 'ASRClientExecutor', 'CLSClientExecutor']
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@cli_client_register(
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name='paddlespeech_client.tts', description='visit tts service')
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class TTSClientExecutor(BaseExecutor):
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def __init__(self):
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super(TTSClientExecutor, self).__init__()
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self.parser = argparse.ArgumentParser(
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prog='paddlespeech_client.tts', add_help=True)
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self.parser.add_argument(
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'--server_ip', type=str, default='127.0.0.1', help='server ip')
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self.parser.add_argument(
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'--port', type=int, default=8090, help='server port')
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self.parser.add_argument(
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'--input',
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type=str,
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default=None,
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help='Text to be synthesized.',
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required=True)
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self.parser.add_argument(
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'--spk_id', type=int, default=0, help='Speaker id')
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self.parser.add_argument(
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'--speed',
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type=float,
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default=1.0,
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help='Audio speed, the value should be set between 0 and 3')
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self.parser.add_argument(
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'--volume',
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type=float,
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default=1.0,
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help='Audio volume, the value should be set between 0 and 3')
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self.parser.add_argument(
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'--sample_rate',
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type=int,
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default=0,
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choices=[0, 8000, 16000],
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help='Sampling rate, the default is the same as the model')
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self.parser.add_argument(
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'--output', type=str, default=None, help='Synthesized audio file')
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def postprocess(self, wav_base64: str, outfile: str) -> float:
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audio_data_byte = base64.b64decode(wav_base64)
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# from byte
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samples, sample_rate = soundfile.read(
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io.BytesIO(audio_data_byte), dtype='float32')
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# transform audio
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if outfile.endswith(".wav"):
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soundfile.write(outfile, samples, sample_rate)
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elif outfile.endswith(".pcm"):
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temp_wav = str(random.getrandbits(128)) + ".wav"
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soundfile.write(temp_wav, samples, sample_rate)
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wav2pcm(temp_wav, outfile, data_type=np.int16)
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os.system("rm %s" % (temp_wav))
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else:
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logger.error("The format for saving audio only supports wav or pcm")
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def execute(self, argv: List[str]) -> bool:
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args = self.parser.parse_args(argv)
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input_ = args.input
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server_ip = args.server_ip
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port = args.port
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spk_id = args.spk_id
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speed = args.speed
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volume = args.volume
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sample_rate = args.sample_rate
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output = args.output
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try:
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time_start = time.time()
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res = self(
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input=input_,
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server_ip=server_ip,
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port=port,
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spk_id=spk_id,
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speed=speed,
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volume=volume,
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sample_rate=sample_rate,
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output=output)
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time_end = time.time()
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time_consume = time_end - time_start
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response_dict = res.json()
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logger.info(response_dict["message"])
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logger.info("Save synthesized audio successfully on %s." % (output))
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logger.info("Audio duration: %f s." %
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(response_dict['result']['duration']))
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logger.info("Response time: %f s." % (time_consume))
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return True
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except Exception as e:
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logger.error("Failed to synthesized audio.")
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return False
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@stats_wrapper
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def __call__(self,
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input: str,
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server_ip: str="127.0.0.1",
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port: int=8090,
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spk_id: int=0,
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speed: float=1.0,
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volume: float=1.0,
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sample_rate: int=0,
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output: str=None):
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"""
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Python API to call an executor.
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"""
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url = 'http://' + server_ip + ":" + str(port) + '/paddlespeech/tts'
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request = {
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"text": input,
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"spk_id": spk_id,
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"speed": speed,
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"volume": volume,
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"sample_rate": sample_rate,
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"save_path": output
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}
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res = requests.post(url, json.dumps(request))
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response_dict = res.json()
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if output is not None:
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self.postprocess(response_dict["result"]["audio"], output)
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return res
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@cli_client_register(
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name='paddlespeech_client.asr', description='visit asr service')
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class ASRClientExecutor(BaseExecutor):
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def __init__(self):
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super(ASRClientExecutor, self).__init__()
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self.parser = argparse.ArgumentParser(
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prog='paddlespeech_client.asr', add_help=True)
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self.parser.add_argument(
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'--server_ip', type=str, default='127.0.0.1', help='server ip')
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self.parser.add_argument(
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'--port', type=int, default=8090, help='server port')
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self.parser.add_argument(
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'--input',
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type=str,
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default=None,
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help='Audio file to be recognized',
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required=True)
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self.parser.add_argument(
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'--sample_rate', type=int, default=16000, help='audio sample rate')
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self.parser.add_argument(
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'--lang', type=str, default="zh_cn", help='language')
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self.parser.add_argument(
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'--audio_format', type=str, default="wav", help='audio format')
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def execute(self, argv: List[str]) -> bool:
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args = self.parser.parse_args(argv)
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input_ = args.input
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server_ip = args.server_ip
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port = args.port
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sample_rate = args.sample_rate
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lang = args.lang
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audio_format = args.audio_format
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try:
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time_start = time.time()
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res = self(
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input=input_,
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server_ip=server_ip,
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port=port,
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sample_rate=sample_rate,
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lang=lang,
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audio_format=audio_format)
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time_end = time.time()
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logger.info(res.json())
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logger.info("Response time %f s." % (time_end - time_start))
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return True
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except Exception as e:
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logger.error("Failed to speech recognition.")
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return False
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@stats_wrapper
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def __call__(self,
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input: str,
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server_ip: str="127.0.0.1",
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port: int=8090,
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sample_rate: int=16000,
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lang: str="zh_cn",
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audio_format: str="wav"):
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"""
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Python API to call an executor.
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"""
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url = 'http://' + server_ip + ":" + str(port) + '/paddlespeech/asr'
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audio = wav2base64(input)
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data = {
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"audio": audio,
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"audio_format": audio_format,
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"sample_rate": sample_rate,
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"lang": lang,
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}
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res = requests.post(url=url, data=json.dumps(data))
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return res
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@cli_client_register(
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name='paddlespeech_client.asr_online',
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description='visit asr online service')
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class ASRClientExecutor(BaseExecutor):
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def __init__(self):
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super(ASRClientExecutor, self).__init__()
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self.parser = argparse.ArgumentParser(
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prog='paddlespeech_client.asr', add_help=True)
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self.parser.add_argument(
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'--server_ip', type=str, default='127.0.0.1', help='server ip')
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self.parser.add_argument(
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'--port', type=int, default=8091, help='server port')
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self.parser.add_argument(
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'--input',
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type=str,
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default=None,
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help='Audio file to be recognized',
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required=True)
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self.parser.add_argument(
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'--sample_rate', type=int, default=16000, help='audio sample rate')
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self.parser.add_argument(
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'--lang', type=str, default="zh_cn", help='language')
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self.parser.add_argument(
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'--audio_format', type=str, default="wav", help='audio format')
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def execute(self, argv: List[str]) -> bool:
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args = self.parser.parse_args(argv)
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input_ = args.input
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server_ip = args.server_ip
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port = args.port
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sample_rate = args.sample_rate
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lang = args.lang
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audio_format = args.audio_format
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try:
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time_start = time.time()
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res = self(
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input=input_,
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server_ip=server_ip,
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port=port,
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sample_rate=sample_rate,
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lang=lang,
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audio_format=audio_format)
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time_end = time.time()
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logger.info(res.json())
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logger.info("Response time %f s." % (time_end - time_start))
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return True
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except Exception as e:
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logger.error("Failed to speech recognition.")
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return False
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@stats_wrapper
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def __call__(self,
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input: str,
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server_ip: str="127.0.0.1",
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port: int=8091,
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sample_rate: int=16000,
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lang: str="zh_cn",
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audio_format: str="wav"):
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"""
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Python API to call an executor.
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"""
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logging.basicConfig(level=logging.INFO)
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logging.info("asr websocket client start")
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handler = ASRAudioHandler(server_ip, port)
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loop = asyncio.get_event_loop()
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loop.run_until_complete(handler.run(input))
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logging.info("asr websocket client finished")
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@cli_client_register(
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name='paddlespeech_client.cls', description='visit cls service')
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class CLSClientExecutor(BaseExecutor):
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def __init__(self):
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super(CLSClientExecutor, self).__init__()
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self.parser = argparse.ArgumentParser(
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prog='paddlespeech_client.cls', add_help=True)
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self.parser.add_argument(
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'--server_ip', type=str, default='127.0.0.1', help='server ip')
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self.parser.add_argument(
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'--port', type=int, default=8090, help='server port')
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self.parser.add_argument(
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'--input',
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type=str,
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default=None,
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help='Audio file to classify.',
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required=True)
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self.parser.add_argument(
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'--topk',
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type=int,
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default=1,
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help='Return topk scores of classification result.')
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def execute(self, argv: List[str]) -> bool:
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args = self.parser.parse_args(argv)
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input_ = args.input
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server_ip = args.server_ip
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port = args.port
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topk = args.topk
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try:
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time_start = time.time()
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res = self(input=input_, server_ip=server_ip, port=port, topk=topk)
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time_end = time.time()
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logger.info(res.json())
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logger.info("Response time %f s." % (time_end - time_start))
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return True
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except Exception as e:
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logger.error("Failed to speech classification.")
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return False
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@stats_wrapper
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def __call__(self,
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input: str,
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server_ip: str="127.0.0.1",
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port: int=8090,
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topk: int=1):
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"""
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Python API to call an executor.
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"""
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url = 'http://' + server_ip + ":" + str(port) + '/paddlespeech/cls'
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audio = wav2base64(input)
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data = {"audio": audio, "topk": topk}
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res = requests.post(url=url, data=json.dumps(data))
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return res
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