Save SMPL

Documentation

• Class name: SaveSMPL
• Category: MotionDiff/smpl
• Output node: True

The SaveSMPL node is designed for saving SMPL model data, including thetas and metadata, to a specified output directory. It supports appending a custom prefix to the filename and saving the data in a structured format for further use or analysis.

Input types

Required

• smpl
  • The SMPL model data to be saved, including thetas and metadata, which are crucial for reconstructing the 3D model.
  • Comfy dtype: SMPL
  • Python dtype: Tuple[torch.Tensor, torch.Tensor, Dict]
• filename_prefix
  • A prefix for the filename to help organize and identify the saved SMPL model data files easily.
  • Comfy dtype: STRING
  • Python dtype: str

Output types

The node doesn't have output types

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class SaveSMPL:
    def __init__(self):
        self.output_dir = folder_paths.get_output_directory()
        self.type = "output"
        self.prefix_append = "_smpl"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "smpl": ("SMPL", ),
                "filename_prefix": ("STRING", {"default": "motiondiff_pt"})
            }
        }

    RETURN_TYPES = ()
    FUNCTION = "save_smpl"

    OUTPUT_NODE = True

    CATEGORY = "MotionDiff/smpl"

    def save_smpl(self, smpl, filename_prefix):
        _, thetas, meta = smpl
        filename_prefix += self.prefix_append
        full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir, 196, 24)
        file = f"{filename}_{counter:05}_.pt"
        torch.save({ "thetas": thetas, "meta": meta }, os.path.join(full_output_folder, file))
        return {}