lipasr.py
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###############################################################################
# Copyright (C) 2024 LiveTalking@lipku https://github.com/lipku/LiveTalking
# email: lipku@foxmail.com
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import time
import torch
import numpy as np
import queue
from queue import Queue
#import multiprocessing as mp
from baseasr import BaseASR
from wav2lip import audio
class LipASR(BaseASR):
def run_step(self):
############################################## extract audio feature ##############################################
# get a frame of audio
for _ in range(self.batch_size*2):
frame,type,eventpoint = self.get_audio_frame()
self.frames.append(frame)
# put to output
self.output_queue.put((frame,type,eventpoint))
# context not enough, do not run network.
if len(self.frames) <= self.stride_left_size + self.stride_right_size:
return
inputs = np.concatenate(self.frames) # [N * chunk]
mel = audio.melspectrogram(inputs)
#print(mel.shape[0],mel.shape,len(mel[0]),len(self.frames))
# cut off stride
left = max(0, self.stride_left_size*80/50)
right = min(len(mel[0]), len(mel[0]) - self.stride_right_size*80/50)
mel_idx_multiplier = 80.*2/self.fps
mel_step_size = 16
i = 0
mel_chunks = []
while i < (len(self.frames)-self.stride_left_size-self.stride_right_size)/2:
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
self.feat_queue.put(mel_chunks)
# discard the old part to save memory
self.frames = self.frames[-(self.stride_left_size + self.stride_right_size):]