| import os |
| import sys |
|
|
| os.environ['CUDA_VISIBLE_DEVICES'] = '0' |
| sys.path.append(os.getcwd()) |
|
|
| from tqdm import tqdm |
| from transformers import Wav2Vec2Processor |
|
|
| from evaluation.metrics import LVD |
|
|
| import numpy as np |
| import smplx as smpl |
|
|
| from data_utils.lower_body import part2full, poses2pred, c_index_3d |
| from nets import * |
| from nets.utils import get_path, get_dpath |
| from trainer.options import parse_args |
| from data_utils import torch_data |
| from trainer.config import load_JsonConfig |
|
|
| import torch |
| from torch.utils import data |
| from data_utils.get_j import to3d, get_joints |
| from scripts.test_body import init_model, init_dataloader |
|
|
|
|
| def test(test_loader, generator, config): |
| print('start testing') |
|
|
| loss_dict = {} |
| B = 1 |
| with torch.no_grad(): |
| count = 0 |
| for bat in tqdm(test_loader, desc="Testing......"): |
| count = count + 1 |
| aud, poses, exp = bat['aud_feat'].to('cuda').to(torch.float32), bat['poses'].to('cuda').to(torch.float32), \ |
| bat['expression'].to('cuda').to(torch.float32) |
| id = bat['speaker'].to('cuda') - 20 |
| betas = bat['betas'][0].to('cuda').to(torch.float64) |
| poses = torch.cat([poses, exp], dim=-2).transpose(-1, -2).squeeze() |
| poses = to3d(poses, config).unsqueeze(dim=0).transpose(1, 2) |
| |
|
|
| cur_wav_file = bat['aud_file'][0] |
|
|
| pred = generator.infer_on_audio(cur_wav_file, |
| initial_pose=poses, |
| id=id, |
| fps=30, |
| B=B |
| ) |
| pred = torch.tensor(pred, device='cuda') |
| bat_loss_dict = {'capacity': (poses[:, c_index_3d, :pred.shape[0]].transpose(1,2) - pred).abs().sum(-1).mean()} |
|
|
| if loss_dict: |
| for key in list(bat_loss_dict.keys()): |
| loss_dict[key] += bat_loss_dict[key] |
| else: |
| for key in list(bat_loss_dict.keys()): |
| loss_dict[key] = bat_loss_dict[key] |
| for key in loss_dict.keys(): |
| loss_dict[key] = loss_dict[key] / count |
| print(key + '=' + str(loss_dict[key].item())) |
|
|
|
|
| def main(): |
| parser = parse_args() |
| args = parser.parse_args() |
| device = torch.device(args.gpu) |
| torch.cuda.set_device(device) |
|
|
| config = load_JsonConfig(args.config_file) |
|
|
| os.environ['smplx_npz_path'] = config.smplx_npz_path |
| os.environ['extra_joint_path'] = config.extra_joint_path |
| os.environ['j14_regressor_path'] = config.j14_regressor_path |
|
|
| print('init dataloader...') |
| test_set, test_loader, norm_stats = init_dataloader(config.Data.data_root, args.speakers, args, config) |
| print('init model...') |
| model_name = 's2g_body_vq' |
| model_type = 'n_com_8192' |
| model_path = get_path(model_name, model_type) |
| generator = init_model(model_name, model_path, args, config) |
|
|
| test(test_loader, generator, config) |
|
|
|
|
| if __name__ == '__main__': |
| main() |
|
|
