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MIT license Commit: https://github.com/OpenTalker/SadTalker commit ae0b26359d44c9379450a8e02a38b45eeec15549 (HEAD -> main, origin/main, origin/HEAD) Author: shadowcun <shadowcun@tencent.com> Date: Mon Jul 3 13:48:35 2023 +0800 fixed bug: hacking facexlib of FAN
42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
from tqdm import tqdm
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import torch
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from torch import nn
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class Audio2Exp(nn.Module):
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def __init__(self, netG, cfg, device, prepare_training_loss=False):
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super(Audio2Exp, self).__init__()
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self.cfg = cfg
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self.device = device
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self.netG = netG.to(device)
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def test(self, batch):
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mel_input = batch['indiv_mels'] # bs T 1 80 16
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bs = mel_input.shape[0]
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T = mel_input.shape[1]
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exp_coeff_pred = []
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for i in tqdm(range(0, T, 10),'audio2exp:'): # every 10 frames
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current_mel_input = mel_input[:,i:i+10]
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#ref = batch['ref'][:, :, :64].repeat((1,current_mel_input.shape[1],1)) #bs T 64
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ref = batch['ref'][:, :, :64][:, i:i+10]
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ratio = batch['ratio_gt'][:, i:i+10] #bs T
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audiox = current_mel_input.view(-1, 1, 80, 16) # bs*T 1 80 16
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curr_exp_coeff_pred = self.netG(audiox, ref, ratio) # bs T 64
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exp_coeff_pred += [curr_exp_coeff_pred]
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# BS x T x 64
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results_dict = {
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'exp_coeff_pred': torch.cat(exp_coeff_pred, axis=1)
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}
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return results_dict
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