---
tags:
- SMPLModel
---

# 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
```python
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 {}

```