65 lines
2.0 KiB
Markdown
65 lines
2.0 KiB
Markdown
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# Documentation
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- Class name: SMPLLoader
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- Category: MotionDiff/smpl
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- Output node: False
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SMPLLoader节点旨在从指定文件加载和处理SMPL模型数据，便于将SMPL模型集成到运动分析和合成工作流程中。
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# Input types
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## Required
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- smpl
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- 指定要加载的SMPL模型文件名。该文件包含运动合成所需的关键数据，如姿势参数。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- smpl_model
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- 确定要使用的具体SMPL模型，影响加载的SMPL数据的解释方式。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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# Output types
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- smpl
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- 输出一个元组，包含SMPL模型的路径、姿势参数（thetas）和元数据，可供进一步处理或可视化。
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- Comfy dtype: SMPL
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- Python dtype: Tuple[str, torch.Tensor, Dict]
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class SMPLLoader:
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@classmethod
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def INPUT_TYPES(s):
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global smpl_model_dicts
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smpl_model_dicts = get_smpl_models_dict()
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input_dir = folder_paths.get_input_directory()
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files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f))]
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files = folder_paths.filter_files_extensions(files, ['.pt'])
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return {
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"required": {
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"smpl": (files, ),
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"smpl_model": (list(smpl_model_dicts.keys()), {"default": "SMPL_NEUTRAL.pkl"})
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}
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}
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RETURN_TYPES = ("SMPL", )
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FUNCTION = "load_smpl"
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CATEGORY = "MotionDiff/smpl"
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def load_smpl(self, smpl, smpl_model):
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input_dir = folder_paths.get_input_directory()
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smpl_dict = torch.load(os.path.join(input_dir, smpl))
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thetas, meta = smpl_dict["thetas"], smpl_dict["meta"]
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global smpl_model_dicts
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if smpl_model_dicts is None:
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smpl_model_dicts = get_smpl_models_dict()
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smpl_model_path = smpl_model_dicts[smpl_model]
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return ((smpl_model_path, thetas, meta), )
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```
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