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| CUDA_VISIBLE_DEVICES=0 python demo.py --input_dir ./examples \ | |
| --pretrained_weights skeleton_ckpts/puppeteer_skeleton_w_diverse_pose.pth \ | |
| --save_name infer_results_demo --input_pc_num 8192 \ | |
| --save_render --apply_marching_cubes --joint_token --seq_shuffle | |
| # If you found the results not satisfactory, try the model trained with bone-based tokenization: | |
| # CUDA_VISIBLE_DEVICES=0 python demo.py --input_dir ./examples \ | |
| # --pretrained_weights skeleton_ckpts/puppeteer_skeleton_w_diverse_pose_bone_token.pth \ | |
| # --save_name infer_results_demo_bone_token --input_pc_num 8192 \ | |
| # --save_render --apply_marching_cubes --hier_order --seq_shuffle | |
| # If you want to run the demo using MagicArticulate weights, run: | |
| # CUDA_VISIBLE_DEVICES=0 python demo.py --input_dir ./examples \ | |
| # --pretrained_weights skeleton_ckpts/checkpoint_trainonv2_hier.pth \ | |
| # --save_name infer_results_demo_magicarti --input_pc_num 8192 \ | |
| # --save_render --apply_marching_cubes --hier_order |