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0.Get pre-trained models & Data
- Get the Binarized dataset following
docs/process_data/process_th1kh.md. You will seedata/binary/th1kh/train.data - Download
pretrained_ckpts.zipin this Google Drive, unzip it and place it intocheckpoints/pretrained_ckpts. You will seecheckpoints/pretrained_ckpts/mit_b0.pthandcheckpoints/pretrained_ckpts/eg3d_baseline_run2.
1. Train Img-to-Plane Model
1.1 image-to-triplane model in real3d-portrait
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python tasks/run.py --config=egs/os_avatar/img2plane.yaml --hparams=triplane_feature_type=triplane --exp_name=img2plane --reset
1.2 image-to-grid model in zera-portrait (Recommended)
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python tasks/run.py --config=egs/os_avatar/img2plane.yaml --exp_name=img2grid --reset
2.Train Motion-to-Video Model
# secc2plane_head
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python tasks/run.py --config=egs/os_avatar/srcc_img2plane.yaml --exp_name=secc2plane --hparams=init_from_ckpt=checkpoints/img2grid --reset
# secc2plane_torso
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python tasks/run.py --config=egs/os_avatar/srcc_img2plane_torso.yaml --exp_name=secc2plane_torso --hparams=init_from_ckpt=checkpoints/secc2plane --reset
3.Inference
- See
README.md, change the name of checkpoint to your own secc2plane_torso model.