human/tts/Chunk2Mal.py

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#encoding = utf8
import logging
import queue
from queue import Queue
from threading import Thread, Event
import numpy as np
import audio
class Chunk2Mal:
def __init__(self, human):
self._audio_chunk_queue = Queue()
self._human = human
self._thread = None
self._exit_event = None
self._chunks = []
def _on_run(self):
logging.info('chunk2mal run')
while not self._exit_event.is_set():
try:
chunk, type = self.pull_chunk()
self._chunks.append(chunk)
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print("1")
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except queue.Empty:
continue
if len(self._chunks) <= self._human.get_stride_left_size() + self._human.get_stride_right_size():
continue
inputs = np.concatenate(self._chunks) # [N * chunk]
mel = audio.melspectrogram(inputs)
left = max(0, self._human.get_stride_left_size() * 80 / 50)
right = min(len(mel[0]), len(mel[0]) - self._human.get_stride_right_size() * 80 / 50)
mel_idx_multiplier = 80. * 2 / self._human.get_fps()
mel_step_size = 16
i = 0
mel_chunks = []
while i < (len(self._chunks) - self._human.get_stride_left_size()
- self._human.get_stride_right_size()) / 2:
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print("14")
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start_idx = int(left + i * mel_idx_multiplier)
# print(start_idx)
if start_idx + mel_step_size > len(mel[0]):
mel_chunks.append(mel[:, len(mel[0]) - mel_step_size:])
else:
mel_chunks.append(mel[:, start_idx: start_idx + mel_step_size])
i += 1
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print("13")
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self._human.push_feat_queue(mel_chunks)
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print("15")
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# discard the old part to save memory
self._chunks = self._chunks[-(self._human.get_stride_left_size() + self._human.get_stride_right_size()):]
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print("12")
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logging.info('chunk2mal exit')
def start(self):
if self._exit_event is not None:
return
self._exit_event = Event()
self._thread = Thread(target=self._on_run)
self._thread.start()
logging.info('chunk2mal start')
def stop(self):
if self._exit_event is None:
return
self._exit_event.set()
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if self._thread.is_alive():
self._thread.join()
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logging.info('chunk2mal stop')
def push_chunk(self, chunk):
self._audio_chunk_queue.put(chunk)
def pull_chunk(self):
try:
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chunk = self._audio_chunk_queue.get(block=True, timeout=1)
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type = 1
except queue.Empty:
chunk = np.zeros(self._human.get_chunk(), dtype=np.float32)
type = 0
return chunk, type