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Facilitates exporting SMPL models to 3D CGI software for AI artists, streamlining workflow and enhancing usability.
The ExportSMPLTo3DSoftware
node is designed to facilitate the export of SMPL (Skinned Multi-Person Linear) models to various 3D CGI software formats. This node is particularly useful for AI artists who work with human motion data and need to integrate these models into 3D software for further animation, rendering, or analysis. By converting SMPL models into widely supported 3D file formats, this node streamlines the workflow, allowing for seamless transitions between different software environments. The primary goal of this node is to ensure that the complex SMPL data can be easily utilized in popular 3D applications, enhancing the versatility and usability of the motion data.
This parameter expects an SMPL model, which is a detailed representation of human body shapes and poses. The SMPL model includes information about the body mesh, joint positions, and other relevant data. Providing a valid SMPL model is crucial as it forms the basis of the export process.
This is a string parameter that allows you to specify a prefix for the folder name where the exported files will be saved. The default value is "motiondiff_meshes". This prefix helps in organizing the output files and can be customized to suit your project needs.
This parameter defines the file format for the exported 3D models. It accepts a list of available mesh formats, with the default being 'glb'. The choice of format can impact the compatibility and quality of the exported models, so it is important to select a format that is supported by your target 3D software.
This node does not produce any direct output parameters. Instead, it performs the action of saving the SMPL models to the specified directory in the chosen format.
foldername_prefix
to keep your exported files organized, especially when working on multiple projects.format
based on the requirements of your target 3D software to ensure compatibility and optimal quality.© Copyright 2024 RunComfy. All Rights Reserved.