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DATA:
dataset: multi
data_root: sample_dataset
wav_path: wav
vertices_path: npy
template_file: templates.pkl
train_subjects: Arabic English French German Greek Italian Portuguese Russian Spanish Korean Mandarin Japanese
NETWORK:
arch: stage2
in_dim: 15069
hidden_size: 1024
num_hidden_layers: 6
num_attention_heads: 8
intermediate_size: 1536
window_size: 1
quant_factor: 0
face_quan_num: 16
neg: 0.2
autoencoder: stage1_vocaset
INaffine: False
style_emb_method: nnemb # onehot or nnemb
VQuantizer:
n_embed: 256
zquant_dim: 64
PREDICTOR:
feature_dim: 1024
vertice_dim: 15069
device: cuda
period: 25
vqvae_pretrained_path: checkpoints/stage1.pth.tar
wav2vec2model_path: facebook/wav2vec2-large-xlsr-53
teacher_forcing: True
num_layers: 6
n_head: 4 # not used
DEMO:
model_path: checkpoints/stage2.pth.tar
#condition: False #if false, the waveform file has the cue for the type of language
condition: English
subject: id
demo_wav_dir_path: demo/input/
demo_output_path: demo/output/
fps: 25
background_black: True # chose the background color of your rendered video |