120 lines
3.9 KiB
Python
120 lines
3.9 KiB
Python
#encoding = utf8
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import logging
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import queue
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import time
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from queue import Queue
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import multiprocessing as mp
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from threading import Thread, Event
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import numpy as np
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import audio
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from audio_render import AudioRender
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class Chunk2Mal:
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def __init__(self, human):
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# self._audio_chunk_queue = Queue()
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self._human = human
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self._thread = None
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self.frames = []
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self.queue = Queue()
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# self.output_queue = mp.Queue()
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# self.feat_queue = mp.Queue(2)
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# 320 samples per chunk (20ms * 16000 / 1000)audio_chunk
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self.chunk = self._human.get_audio_sample_rate() // self._human.get_fps()
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self._exit_event = Event()
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self._thread = Thread(target=self._on_run)
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self._exit_event.set()
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self._thread.start()
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# self._audio_render = AudioRender()
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self._stream_len = 0
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logging.info('chunk2mal start')
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def _on_run(self):
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logging.info('chunk2mal run')
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while self._exit_event.is_set():
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self._run_step()
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time.sleep(0.01)
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logging.info('chunk2mal exit')
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def _run_step(self):
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for _ in range(self._human.get_batch_size() * 2):
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frame, _type = self.get_audio_frame()
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self.frames.append(frame)
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# put to output
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self._human.push_out_put(frame, _type)
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# self.output_queue.put((frame, _type))
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# context not enough, do not run network.
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if len(self.frames) <= self._human.get_stride_left_size() + self._human.get_stride_right_size():
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return
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inputs = np.concatenate(self.frames) # [N * chunk]
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mel = audio.melspectrogram(inputs)
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# print(mel.shape[0],mel.shape,len(mel[0]),len(self.frames))
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# cut off stride
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left = max(0, self._human.get_stride_left_size() * 80 / 50)
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right = min(len(mel[0]), len(mel[0]) - self._human.get_stride_right_size() * 80 / 50)
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mel_idx_multiplier = 80. * 2 / self._human.get_fps()
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mel_step_size = 16
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i = 0
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mel_chunks = []
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while i < (len(self.frames) - self._human.get_stride_left_size() - self._human.get_stride_right_size()) / 2:
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start_idx = int(left + i * mel_idx_multiplier)
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# print(start_idx)
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if start_idx + mel_step_size > len(mel[0]):
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mel_chunks.append(mel[:, len(mel[0]) - mel_step_size:])
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else:
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mel_chunks.append(mel[:, start_idx: start_idx + mel_step_size])
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i += 1
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self._human.push_mel_chunks(mel_chunks)
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# self.feat_queue.put(mel_chunks)
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# discard the old part to save memory
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self.frames = self.frames[-(self._human.get_stride_left_size() + self._human.get_stride_right_size()):]
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def stop(self):
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if self._exit_event is None:
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return
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self._exit_event.clear()
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if self._thread.is_alive():
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self._thread.join()
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logging.info('chunk2mal stop')
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def pause_talk(self):
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self.queue.queue.clear()
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def put_audio_frame(self, audio_chunk): #16khz 20ms pcm
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self.queue.put(audio_chunk)
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def get_audio_frame(self):
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try:
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frame = self.queue.get(block=True, timeout=0.01)
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type = 0
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# print(f'[INFO] get frame {frame.shape}')
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except queue.Empty:
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frame = np.zeros(self.chunk, dtype=np.float32)
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type = 1
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return frame, type
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def get_audio_out(self): # get origin audio pcm to nerf
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return self.output_queue.get()
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def warm_up(self):
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for _ in range(self._human.get_stride_left_size() + self._human.get_stride_right_size()):
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audio_frame, _type = self.get_audio_frame()
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self.frames.append(audio_frame)
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self.output_queue.put((audio_frame, type))
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for _ in range(self._human.get_stride_right_size()):
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self.output_queue.get()
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def get_next_feat(self, block, timeout):
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return self.feat_queue.get(block, timeout)
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