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Facilitates saving SMPL model data with customizable prefix for organization, storage, and reuse in motion capture and animation tasks.
The SaveSMPL node is designed to facilitate the saving of SMPL (Skinned Multi-Person Linear) model data, which is crucial for motion capture and 3D character animation tasks. This node allows you to store the parameters and metadata of an SMPL model into a file, making it easy to manage and reuse motion data across different projects. By appending a customizable prefix to the filename, it ensures that your saved files are organized and easily identifiable. The primary function of this node is to save the theta parameters and metadata of the SMPL model into a .pt
file, which can be later loaded and used for rendering or further processing. This capability is particularly beneficial for AI artists and animators who need to work with complex motion data and require a reliable method to save and retrieve their work.
This parameter represents the SMPL model data that you want to save. It is a tuple containing the model path, theta parameters, and metadata. The theta parameters define the pose of the model, while the metadata includes additional information such as normalization details. This input is essential as it encapsulates all the necessary data required to recreate the SMPL model's pose and characteristics.
This is a string parameter that allows you to specify a prefix for the filename under which the SMPL data will be saved. The default value is "motiondiff_pt". This prefix helps in organizing and identifying the saved files, especially when dealing with multiple SMPL models. The node appends a suffix "_smpl" to this prefix to create a unique filename for each saved file.
The SaveSMPL node does not produce any direct output parameters. Its primary function is to save the provided SMPL data to a file, and it does not return any values upon completion.
smpl
parameter contains valid SMPL model data, including the model path, theta parameters, and metadata, to avoid errors during the saving process.filename_prefix
to easily identify and organize your saved SMPL files, especially when working on large projects with multiple models.smpl
parameter is not correctly formatted or is missing required data.smpl
parameter is a tuple containing the model path, theta parameters, and metadata. Ensure that all required data is present and correctly formatted.© Copyright 2024 RunComfy. All Rights Reserved.