57 lines
1.8 KiB
Markdown
57 lines
1.8 KiB
Markdown
|
|
# Documentation
|
|
- Class name: LoadInstanceFusersNode
|
|
- Category: instance/loaders
|
|
- Output node: False
|
|
|
|
此节点旨在从指定目录加载和准备实例融合器模型，并根据提供的参数调整其比例。它促进了融合器模型在实例扩散过程中的动态整合，从而实现对实例特定特征融合的增强控制。
|
|
|
|
# Input types
|
|
## Required
|
|
- model_filename
|
|
- 指定要加载的模型文件名。这个参数对于从指定目录中识别和检索正确的融合器模型至关重要。
|
|
- Comfy dtype: COMBO[STRING]
|
|
- Python dtype: str
|
|
- fusers_scale
|
|
- 确定要应用于融合器的缩放因子，影响它们在实例融合过程中的作用。这允许对融合器对生成实例的影响进行微调。
|
|
- Comfy dtype: FLOAT
|
|
- Python dtype: float
|
|
|
|
# Output types
|
|
- fusers
|
|
- 提供已加载和缩放的融合器模型列表，可以直接集成到实例扩散过程中。
|
|
- Comfy dtype: FUSERS
|
|
- Python dtype: Dict[str, List[torch.nn.Module]]
|
|
|
|
|
|
## Usage tips
|
|
- Infra type: `GPU`
|
|
- Common nodes: unknown
|
|
|
|
|
|
## Source code
|
|
```python
|
|
class LoadInstanceFusersNode:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {"required": {
|
|
"model_filename": (get_model_list(constants.INSTANCE_FUSERS_DIR),),
|
|
"fusers_scale": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
|
|
}}
|
|
|
|
RETURN_TYPES = ("FUSERS",)
|
|
FUNCTION = "load_model"
|
|
|
|
CATEGORY = "instance/loaders"
|
|
|
|
def load_model(self, model_filename: str, fusers_scale: float):
|
|
checkpoint = load_checkpoint(
|
|
constants.INSTANCE_FUSERS_DIR, model_filename)
|
|
fusers_list = prepare_fusers(checkpoint, fusers_scale)
|
|
fusers = {
|
|
'model_list': fusers_list
|
|
}
|
|
return (fusers,)
|
|
|
|
```
|