| ## Technical tricks to improve or accelerate ECON | |
| ### If the reconstructed geometry is not satisfying, play with the adjustable parameters in _config/econ.yaml_ | |
| - `use_smpl: ["hand"]` | |
| - [ ]: don't use either hands or face parts from SMPL-X | |
| - ["hand"]: only use the **visible** hands from SMPL-X | |
| - ["hand", "face"]: use both **visible** hands and face from SMPL-X | |
| - `thickness: 2cm` | |
| - could be increased accordingly in case final reconstruction **xx_full.obj** looks flat | |
| - `k: 4` | |
| - could be reduced accordingly in case the surface of **xx_full.obj** has discontinous artifacts | |
| - `hps_type: PIXIE` | |
| - "pixie": more accurate for face and hands | |
| - "pymafx": more robust for challenging poses | |
| - `texture_src: image` | |
| - "image": direct mapping the aligned pixels to final mesh | |
| - "SD": use Stable Diffusion to generate full texture (TODO) | |
| ### To accelerate the inference, you could | |
| - `use_ifnet: False` | |
| - True: use IF-Nets+ for mesh completion ( $\text{ECON}_\text{IF}$ - Better quality, **~2min / img**) | |
| - False: use SMPL-X for mesh completion ( $\text{ECON}_\text{EX}$ - Faster speed, **~1.8min / img**) | |
| ```bash | |
| # For single-person image-based reconstruction (w/o all visualization steps, 1.5min) | |
| python -m apps.infer -cfg ./configs/econ.yaml -in_dir ./examples -out_dir ./results -novis | |
| ``` | |