558 lines
23 KiB
Python
558 lines
23 KiB
Python
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# basic
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import time
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import json
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import random
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from collections import deque
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# log
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import logging
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import warnings
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# multiprocessing
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import queue
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import threading
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import multiprocessing
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# web request
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import requests
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import pyaudio
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class WebRequestMPManager:
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def __init__(self,
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server_args,
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audio_args,
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recorder_args,
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asr_args,
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video_args,
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emo_args,
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log_args):
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# server_args
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self.server_args = server_args
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# audio_args
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self.record_CHUNK_SIZE = audio_args['record_CHUNK_SIZE']
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self.voice_trigger = audio_args['voice_trigger']
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self.keywords = audio_args['keywords']
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# recorder_args
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self.recorder_args = recorder_args
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# asr_args
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self.asr_args = asr_args
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# video_args
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self.video_args = video_args
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# emo_args
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self.emo_args = emo_args
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# log_args
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self.log_args = log_args
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# TODO: 设计多进程log queue
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self.logger_init()
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def logger_init(self):
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# log_args
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log_level = self.log_args['log_level']
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log_file = self.log_args['log_file']
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if log_level == 'debug':
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log_level = logging.DEBUG
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elif log_level == 'info':
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log_level = logging.INFO
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# logger
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self.logger = logging.getLogger('mylogger')
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self.logger.setLevel(log_level)
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# handler 创建一个handler，用于写入日志文件
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handler = logging.FileHandler(log_file)
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handler.setLevel(log_level)
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# stream handler 创建一个handler，用于输出到控制台
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console = logging.StreamHandler()
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console.setLevel(logging.INFO)
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# 定义handler的输出格式（formatter）
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formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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handler.setFormatter(formatter)
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console.setFormatter(formatter)
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# 添加handler
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self.logger.addHandler(handler)
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self.logger.addHandler(console)
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self.logger.info("Logger started.")
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def process_init(self):
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# multiprocessing
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manager = multiprocessing.Manager()
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self.trigger_queue = manager.Queue()
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self.client_queue = manager.Queue()
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self.audio_queue = manager.Queue()
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self.audio_play_queue = manager.Queue()
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self.emo_display_queue = manager.Queue()
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processes = [
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multiprocessing.Process(target=self.audio_process, args=(self.logger,self.voice_trigger,self.trigger_queue,self.client_queue)),
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# multiprocessing.Process(target=self.camera_process, args=(self.trigger_queue,self.client_queue)),
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# multiprocessing.Process(target=self.local_client_process, args=(self.logger,self.client_queue,self.audio_play_queue,self.emo_display_queue)),
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# multiprocessing.Process(target=self.audio_play_process, args=(self.logger,self.audio_play_queue,)),
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# multiprocessing.Process(target=self.emo_display_process, args=(self.logger,self.emo_display_queue,)),
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]
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for process in processes:
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process.start()
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for process in processes:
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process.join()
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def audio_process(self, logger, voice_trigger, trigger_queue, client_queue):
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"""audio_process
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Args:
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voice_trigger: bool, whether to use voice trigger
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trigger_queue: multiprocessing.Queue, trigger queue
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client_queue: multiprocessing.Queue, client queue
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"""
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# from takway.audio_utils import Recorder
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from takway.audio_utils import VADRecorder
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recorder = VADRecorder(
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**self.recorder_args,
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)
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# two threads for hardware and voice trigger
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# shared data struct:
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self.shared_waiting = False
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self.shared_hd_trigger = False
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self.shared_kw_trigger = False
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self.shared_lock = threading.Lock()
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self.shared_data_lock = threading.Lock()
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self.shared_audio_data = None
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# vad
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self.shared_vad_data = None
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self.shared_vad_lock = threading.Lock()
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# stt
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# event
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self.record_event = threading.Event()
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self.vad_event = threading.Event()
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self.stt_event = threading.Event()
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self._debug_count = 0
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'''
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shared_waiting: 控制所有线程的待机状态，True表示待机，False表示工作
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shared_hd_trigger: 控制硬件触发器的状态，True表示触发，False表示未触发
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shared_kw_trigger: 控制语音触发器的状态，True表示触发，False表示未触发
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share_audio_data: 共享音频数据，用于存储从麦克风采集的音频数据
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'''
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# create threads
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threads = [threading.Thread(target=self.hardware_trigger_thread, args=(recorder,))]
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if self.voice_trigger:
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vioce_threads = [
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threading.Thread(target=self.voice_record_thread, args=(recorder,)),
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# threading.Thread(target=self.vad_thread, args=(recorder,)),
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threading.Thread(target=self.stt_thread, args=(recorder,)),
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]
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threads.extend(vioce_threads)
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for thread in threads:
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thread.start()
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# self.logger.info("Audio Process started.")
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while True:
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'''
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# Warning: 一定要加延时！！！否则会有bug！！！
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time.sleep(0.001)
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if (self.shared_hd_trigger or self.shared_kw_trigger):
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# print(f"self.shared_hd_trigger: {self.shared_hd_trigger}, self.shared_kw_trigger: {self.shared_kw_trigger}")
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audio_data = self.shared_audio_data
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trigger_queue.put(('trgrigger_status', True))
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client_queue.put(('audio', audio_data))
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self.shared_lock.acquire() # 加锁
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self.shared_hd_trigger = False
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self.shared_kw_trigger = False
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self.shared_audio_data = None
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self.shared_waiting = False
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self.shared_lock.release() # 释放锁
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'''
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self.record_event.wait() # 等待record线程被唤醒
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trigger_queue.put(('trgrigger_status', True))
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client_queue.put(('audio', self.shared_audio_data))
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# print(f"send audio data to client"); exit()
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def hardware_trigger_thread(self, recorder):
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"""hardware_trigger_thread
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Args:
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recorder: takway.audio_utils.Recorder, recorder object
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"""
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self.logger.info("Hardware trigger thread started.")
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trgrigger_status = False
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while True:
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time.sleep(0.2)
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if self.shared_waiting:
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continue
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trgrigger_status = recorder.get_hardware_trigger_status()
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if trgrigger_status:
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self.shared_lock.acquire()
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self.shared_waiting = True # shared_waiting 控制所有线程的待机状态，True表示待机，False表示工作
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self.shared_hd_trigger = True # share_hd_trigger 控制硬件触发器的状态，True表示触发，False表示未触发
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self.shared_lock.release()
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# record microphone data
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audio_data = recorder.record_hardware()
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self.shared_data_lock.acquire()
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self.shared_audio_data = audio_data # shared_audio_data 共享音频数据，用于存储从麦克风采集的音频数据
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self.shared_data_lock.release()
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self.record_event.set() # 唤醒record线程
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else:
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self.shared_lock.acquire()
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self.shared_waiting = False # 释放
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self.shared_lock.release()
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def voice_record_thread(self, recorder, keywords=['你好']):
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"""voice_record_thread
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Args:
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recorder: takway.audio_utils.Recorder, recorder object
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"""
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self.logger.info("voice record thread started.")
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while True:
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if self.shared_waiting:
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time.sleep(0.01)
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continue
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frames = []
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# status buffer
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is_currently_speaking = False
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buffer_size = recorder.vad_buffer_size
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# buffer_size = 6
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active_buffer = deque([False for i in range(buffer_size-1)]+[True], maxlen=buffer_size)
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audio_buffer = deque(maxlen=buffer_size)
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silence_buffer = deque([True for i in range(buffer_size)]+[False], maxlen=buffer_size)
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while True:
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data = recorder.record_chunk_voice(
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CHUNK=recorder.vad_chunk_size,
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return_type=None,
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exception_on_overflow=False)
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if data is None:
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continue
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t1 = time.time()
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# print(f"VAD is_speech: {recorder.is_speech(data)}")
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# print(f"VAD cost: {(time.time() - t1)/1000} ms")
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if recorder.is_speech(data):
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# 标志位buffer
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active_buffer.append(True); active_buffer.popleft()
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silence_buffer.append(False); silence_buffer.popleft()
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# 暂时增加到buffer中
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audio_buffer.append(data)
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# 如果满足检测要求
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if all(active_buffer):
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if not is_currently_speaking:
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print("Speech start detected")
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is_currently_speaking = True
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frames.extend(audio_buffer) # 把说话的buffer也加上
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if is_currently_speaking:
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frames.append(data)
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else:
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# 标志位buffer
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# active_buffer.append(False); active_buffer.popleft()
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silence_buffer.append(True); silence_buffer.popleft()
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if all(silence_buffer):
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# 检测到人声并持续录音
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if is_currently_speaking:
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# 结束标志位
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print("Speech end detected")
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# print("frames length: ", len(frames))
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self.shared_vad_lock.acquire()
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self.shared_vad_data = frames
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self.shared_vad_lock.release()
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self.stt_event.set() # 唤醒stt线程
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print("Wake stt thread")
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break
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else:
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frames = []
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'''
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# print(f"audio_data: {len(audio_data)}")
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self.shared_lock.acquire()
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self.shared_audio_data = audio_data
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self.shared_lock.release()
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self.vad_event.set() # 唤醒vad线程
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'''
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'''
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def vad_thread(self, recorder):
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self.logger.info("VAD thread started.")
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while True:
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frames = []
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# status buffer
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is_currently_speaking = False
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buffer_size = recorder.vad_buffer_size
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active_buffer = deque([False for i in range(buffer_size)], maxlen=buffer_size)
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audio_buffer = deque(maxlen=buffer_size)
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silence_buffer = deque([True for i in range(buffer_size)], maxlen=buffer_size)
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while True:
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self.vad_event.wait() # 等待vad线程被唤醒
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data = self.shared_audio_data
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if data is None:
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continue
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t1 = time.time()
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print(f"VAD is_speech: {recorder.is_speech(data)}")
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print(f"VAD cost: {(time.time() - t1)/1000} ms")
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if recorder.is_speech(data):
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# 标志位buffer
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active_buffer.append(True); active_buffer.popleft()
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silence_buffer.append(False); silence_buffer.popleft()
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# 暂时增加到buffer中
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audio_buffer.append(data)
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# 如果满足检测要求
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if all(active_buffer):
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if not is_currently_speaking:
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print("Speech start detected")
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is_currently_speaking = True
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frames.extend(audio_buffer) # 把说话的buffer也加上
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if is_currently_speaking:
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frames.append(data)
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else:
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# 标志位buffer
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active_buffer.append(False); active_buffer.popleft()
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silence_buffer.append(True); silence_buffer.popleft()
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# 检测到人声并持续录音
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if is_currently_speaking:
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# 结束标志位
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if all(silence_buffer):
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print("Speech end detected")
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# print("frames length: ", len(frames))
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self.shared_vad_lock.acquire()
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self.shared_vad_data = frames
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self.shared_vad_lock.release()
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self.stt_event.set() # 唤醒stt线程
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break
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'''
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def stt_thread(self, recorder):
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"""stt_thread
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Args:
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recorder: takway.audio_utils.Recorder, recorder object
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"""
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self.logger.info("STT thread started.")
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from takway.vosk_utils import AutoSpeechRecognizer
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asr = AutoSpeechRecognizer(**self.asr_args)
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asr.add_keyword(self.keywords)
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kw_trgrigger_status = False
|
|||
|
|
while True:
|
|||
|
|
self.stt_event.wait() # 等待stt线程被唤醒
|
|||
|
|
print("STT thread start")
|
|||
|
|
data = self.shared_vad_data
|
|||
|
|
if data is None:
|
|||
|
|
continue
|
|||
|
|
print("Start to Recongnize key words")
|
|||
|
|
kw_trgrigger_status = asr.recognize_keywords(data, partial_size=512)
|
|||
|
|
print("Finish to Recongnize key words")
|
|||
|
|
if kw_trgrigger_status:
|
|||
|
|
self.shared_lock.acquire()
|
|||
|
|
self.shared_kw_trigger = True # share_kw_trigger 语音关键词触发器的状态，True表示触发，False表示未触发
|
|||
|
|
self.shared_lock.release()
|
|||
|
|
self.record_event.set() # 唤醒record线程
|
|||
|
|
kw_trgrigger_status = False
|
|||
|
|
# print(f"Got keyword trigger"); exit()
|
|||
|
|
|
|||
|
|
def camera_process(self, logger, trigger_queue, client_queue):
|
|||
|
|
from takway.cam_utils import Camera
|
|||
|
|
cam = Camera(self.video_args)
|
|||
|
|
while True:
|
|||
|
|
if trigger_queue.empty():
|
|||
|
|
time.sleep(0.5)
|
|||
|
|
else:
|
|||
|
|
item = trigger_queue.get()
|
|||
|
|
if item[0] == 'trgrigger_status' and item[1]:
|
|||
|
|
_, frame = cap.read()
|
|||
|
|
client_queue.put(('image', frame))
|
|||
|
|
|
|||
|
|
|
|||
|
|
def local_client_process(self, logger, client_queue,audio_play_queue,emo_display_queue):
|
|||
|
|
from takway.client_utils import Client
|
|||
|
|
client = Client(**self.server_args)
|
|||
|
|
# print("Local client process started.")
|
|||
|
|
self.logger.info("Local client process started.")
|
|||
|
|
image = None; audio = None
|
|||
|
|
chat_status = 'init'
|
|||
|
|
while True:
|
|||
|
|
if client_queue.empty():
|
|||
|
|
time.sleep(0.2)
|
|||
|
|
else:
|
|||
|
|
item = client_queue.get()
|
|||
|
|
# print(f"Get item: {item[0]}")
|
|||
|
|
if item[0] == 'image':
|
|||
|
|
# TODO: analyise image and send text to server
|
|||
|
|
image = None
|
|||
|
|
if item[0] == 'audio':
|
|||
|
|
audio = item[1]
|
|||
|
|
print("get audio data.")
|
|||
|
|
emo_display_queue.put(('emo_data', 'happy'))
|
|||
|
|
'''
|
|||
|
|
# 发送数据到服务器
|
|||
|
|
response = client.send_data_to_server(
|
|||
|
|
text=None, audio_data=audio, image_data=None, chat_status=chat_status)
|
|||
|
|
print("get response from server.")
|
|||
|
|
chat_status = 'chating'
|
|||
|
|
print(f"response: {response}")
|
|||
|
|
|
|||
|
|
audio_play_queue.put(('audio', response))
|
|||
|
|
'''
|
|||
|
|
image = None; audio = None
|
|||
|
|
|
|||
|
|
def audio_play_process(self, logger, audio_play_queue):
|
|||
|
|
from takway.audio_utils import AudioPlayer
|
|||
|
|
audio_player = AudioPlayer()
|
|||
|
|
self.logger.info("Audio play process started.")
|
|||
|
|
while True:
|
|||
|
|
if audio_play_queue.empty():
|
|||
|
|
time.sleep(0.2)
|
|||
|
|
else:
|
|||
|
|
item = audio_play_queue.get()
|
|||
|
|
if item[0] == 'server_data':
|
|||
|
|
# 播放音频
|
|||
|
|
print("Playing audio...")
|
|||
|
|
server_data = item[1]
|
|||
|
|
audio_player.play(server_data['audio_base64'], audio_type='base64')
|
|||
|
|
|
|||
|
|
def emo_display_process(self, logger, emo_display_queue):
|
|||
|
|
from takway.emo_utils import EmoVideoPlayer
|
|||
|
|
emo_player = EmoVideoPlayer(**self.emo_args)
|
|||
|
|
self.logger.info("Emo display process started.")
|
|||
|
|
# logger.info("Emo display process started.")
|
|||
|
|
# print("Emo display process started.")
|
|||
|
|
while True:
|
|||
|
|
if emo_display_queue.empty():
|
|||
|
|
time.sleep(0.2)
|
|||
|
|
seed = random.randrange(0, 1000)
|
|||
|
|
print(f"seed: {seed}")
|
|||
|
|
if seed < 100:
|
|||
|
|
# emo_player.display_emo_opencv(emo_name='静态', stage='seldom_wink')
|
|||
|
|
emo_player.display_emo_maixsense(emo_name='静态', stage='seldom_wink')
|
|||
|
|
|
|||
|
|
else:
|
|||
|
|
item = emo_display_queue.get()
|
|||
|
|
print(f"Emo display process Get item: {item[0]}")
|
|||
|
|
if item[0] == 'emo_data':
|
|||
|
|
server_data = item[1]
|
|||
|
|
print("Displaying emo...")
|
|||
|
|
|
|||
|
|
# emo_player.display_emo_opencv(emo_name='静态', stage='seldom_wink')
|
|||
|
|
# emo_player.display_emo_opencv(emo_name='静态', stage='quick_wink')
|
|||
|
|
emo_player.display_emo_maixsense(emo_name='静态', stage='seldom_wink')
|
|||
|
|
emo_player.display_emo_maixsense(emo_name='静态', stage='quick_wink')
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
'''
|
|||
|
|
def display_process(q):
|
|||
|
|
print("Display process started.")
|
|||
|
|
while True:
|
|||
|
|
item = q.get()
|
|||
|
|
if item[0] == 'server_data':
|
|||
|
|
server_data = item[1]
|
|||
|
|
# 显示图像和文本
|
|||
|
|
# print("Displaying image and text:", item[1]['image'], item[1]['text'])
|
|||
|
|
print("Displaying image and text:")
|
|||
|
|
# 这里可以加上实际的显示图像和文本的代码
|
|||
|
|
if item[0] == 'image':
|
|||
|
|
# 显示图像和文本
|
|||
|
|
cv2.imshow('image', item[1])
|
|||
|
|
cv2.waitKey(1)
|
|||
|
|
'''
|
|||
|
|
|
|||
|
|
if __name__ == '__main__':
|
|||
|
|
|
|||
|
|
try:
|
|||
|
|
import gpiod as gpio
|
|||
|
|
model_path="vosk-model-small-cn-0.22"
|
|||
|
|
emo_dir="ResizedEmoji"
|
|||
|
|
except:
|
|||
|
|
model_path=r"G:\WorkSpace\CodeWorkspace\GPT_projects\vits_project\vits-uma-genshin-honkai\vosk-model-small-cn-0.22"
|
|||
|
|
emo_dir=r"G:\WorkSpace\CodeWorkspace\GPT_projects\vits_project\vits-uma-genshin-honkai\ResizedEmoji"
|
|||
|
|
|
|||
|
|
import argparse
|
|||
|
|
parser = argparse.ArgumentParser()
|
|||
|
|
# server params
|
|||
|
|
parser.add_argument('--server_url', type=str, default='http://127.0.0.1:5000/process_all', help='Server url')
|
|||
|
|
# audio paramters
|
|||
|
|
parser.add_argument('--voice_trigger', type=bool, default=True, help='Voice trigger')
|
|||
|
|
parser.add_argument('--record_CHUNK_SIZE', type=int, default=8000, help='Record chunk size')
|
|||
|
|
parser.add_argument('--keywords', type=list, default=['你好'], help='Voice trigger keywords')
|
|||
|
|
# recorder paramters
|
|||
|
|
parser.add_argument('--hd_trigger', type=str, default='keyboard', help='Hardware trigger')
|
|||
|
|
parser.add_argument('--keyboard_key', type=str, default='space', help='Keyboard key')
|
|||
|
|
parser.add_argument('--CHUNK', type=int, default=2048, help='Record chunk size')
|
|||
|
|
parser.add_argument('--RATE', type=int, default=8000, help='Audio rate')
|
|||
|
|
parser.add_argument('--FORMAT', type=int, default=16, help='Audio format')
|
|||
|
|
parser.add_argument('--CHANNELS', type=int, default=1, help='Audio channels')
|
|||
|
|
parser.add_argument('--filename', type=str, default=None, help='Audio file name')
|
|||
|
|
# ASR paramters
|
|||
|
|
# model_path="vosk-model-small-cn-0.22"
|
|||
|
|
# model_path=r"G:\WorkSpace\CodeWorkspace\GPT_projects\vits_project\vits-uma-genshin-honkai\vosk-model-small-cn-0.22"
|
|||
|
|
parser.add_argument('--model_path', type=str, default=model_path, help='Vosk model path')
|
|||
|
|
# video paramters
|
|||
|
|
parser.add_argument('--device', type=str, default='pc', help='Video device')
|
|||
|
|
parser.add_argument('--width', type=int, default=1280, help='Video width')
|
|||
|
|
parser.add_argument('--height', type=int, default=720, help='Video height')
|
|||
|
|
# emo paramters
|
|||
|
|
# emo_dir="ResizedEmoji"
|
|||
|
|
# emo_dir=r"G:\WorkSpace\CodeWorkspace\GPT_projects\vits_project\vits-uma-genshin-honkai\ResizedEmoji"
|
|||
|
|
parser.add_argument('--emo_dir', type=str, default=emo_dir, help='Emo dir')
|
|||
|
|
# log paramters
|
|||
|
|
parser.add_argument('--log_file', type=str, default='my.log', help='Log file')
|
|||
|
|
parser.add_argument('--log_level', type=str, default='INFO', help='Log level')
|
|||
|
|
|
|||
|
|
parser.add_argument('--debug', type=bool, default=True, help='Debug mode')
|
|||
|
|
args = parser.parse_args()
|
|||
|
|
|
|||
|
|
|
|||
|
|
# sort out args and params
|
|||
|
|
server_args = {
|
|||
|
|
'server_url': args.server_url,
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
audio_args = {
|
|||
|
|
'voice_trigger': args.voice_trigger,
|
|||
|
|
'keywords': args.keywords,
|
|||
|
|
'record_CHUNK_SIZE': args.record_CHUNK_SIZE,
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
recorder_args = {
|
|||
|
|
'hd_trigger': args.hd_trigger,
|
|||
|
|
'keyboard_key': args.keyboard_key,
|
|||
|
|
'model_path': args.model_path,
|
|||
|
|
'CHUNK': args.CHUNK,
|
|||
|
|
'FORMAT': pyaudio.paInt16 if args.FORMAT == 16 else pyaudio.paInt32,
|
|||
|
|
'CHANNELS': args.CHANNELS,
|
|||
|
|
'RATE': args.RATE,
|
|||
|
|
'filename': args.filename,
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
asr_args = {
|
|||
|
|
'model_path': args.model_path,
|
|||
|
|
'RATE': args.RATE,
|
|||
|
|
'debug': args.debug,
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
video_args = {
|
|||
|
|
'device': args.device,
|
|||
|
|
'width': args.width,
|
|||
|
|
'height': args.height,
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
emo_args = {
|
|||
|
|
'emo_dir': args.emo_dir,
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
log_args = {
|
|||
|
|
'log_file': args.log_file,
|
|||
|
|
'log_level': args.log_level,
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
|
|||
|
|
web_request_mp_manager = WebRequestMPManager(
|
|||
|
|
server_args=server_args,
|
|||
|
|
audio_args=audio_args,
|
|||
|
|
recorder_args=recorder_args,
|
|||
|
|
asr_args=asr_args,
|
|||
|
|
video_args=video_args,
|
|||
|
|
emo_args=emo_args,
|
|||
|
|
log_args=log_args)
|
|||
|
|
web_request_mp_manager.process_init()
|