59 lines
1.6 KiB
Markdown
59 lines
1.6 KiB
Markdown
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# Documentation
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- Class name: SaltCLIPSegLoader
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- Category: SALT/Loaders
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- Output node: False
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SaltCLIPSegLoader节点旨在加载和初始化用于图像分割任务的CLIPSeg模型。它简化了从指定源获取模型及其处理器的过程，并将它们本地缓存以提高重用效率。
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# Input types
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## Required
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- model
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- 指定要加载的CLIPSeg模型的标识符。这为选择不同的CLIPSeg模型版本或配置提供了灵活性。
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- Comfy dtype: STRING
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- Python dtype: str
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# Output types
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- clipseg_model
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- 返回一个包含CLIPSeg处理器和CLIPSeg模型的元组，可直接用于图像分割任务。
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- Comfy dtype: CLIPSEG_MODEL
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- Python dtype: Tuple[CLIPSegProcessor, CLIPSegForImageSegmentation]
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## Usage tips
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- Infra type: `GPU`
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- Common nodes: unknown
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## Source code
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```python
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class SaltCLIPSegLoader:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"model": ("STRING", {"default": "CIDAS/clipseg-rd64-refined", "multiline": False}),
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},
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}
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RETURN_TYPES = ("CLIPSEG_MODEL",)
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RETURN_NAMES = ("clipseg_model",)
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FUNCTION = "clipseg_model"
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CATEGORY = f"{NAME}/Loaders"
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def clipseg_model(self, model):
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from transformers import CLIPSegProcessor, CLIPSegForImageSegmentation
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cache = os.path.join(models_dir, 'clipseg')
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inputs = CLIPSegProcessor.from_pretrained(model, cache_dir=cache)
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model = CLIPSegForImageSegmentation.from_pretrained(model, cache_dir=cache)
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return ( (inputs, model), )
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```
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