1.8 KiB
1.8 KiB
tags
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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 {}