import numpy as np
from inference import VisemeRegressor
pb_filepath = "./visemenet_frozen.pb"
wav_file_path = "./test_audio.wav"
out_txt_path = "./maya_viseme_outputs.txt"
viseme_regressor = VisemeRegressor(pb_filepath=pb_filepath)
viseme_outputs = viseme_regressor.predict_outputs(wav_file_path=wav_file_path)
np.savetxt(out_txt_path, viseme_outputs, '%.4f')
Setup the envs and packages
# Install Virtualenv using pyenv
pyenv install 3.6.5
pyenv virtualenv 3.6.5 visemenet-freeze
pyenv activate visemenet-freeze
# Install packages
pip install tensorflow==1.1.0
Clone the repo
# Clone Visemenet repo and the pretrained model
git clone https://github.com/yzhou359/VisemeNet_tensorflow.git
curl -L https://www.dropbox.com/sh/7nbqgwv0zz8pbk9/AAAghy76GVYDLqPKdANcyDuba?dl=0 > pretrained_model.zip
unzip prtrained_model.zip -d VisemeNet_tensorflow/data/ckpt/pretrain_biwi/
Freeze Graph and Save as pb
# Freeze Graph
python freeze_graph.py