54 lines
1.7 KiB
Markdown
54 lines
1.7 KiB
Markdown
# Documentation
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- Class name: SEGSConcat
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- Category: ImpactPack/Util
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- Output node: False
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- Repo Ref: https://github.com/ltdrdata/ComfyUI-Impact-Pack.git
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SEGSConcat节点旨在将多个分割（SEGS）合并为一个统一的分割。它高效地合并分割数据，确保生成的分割是连贯的，并且保持原始数据形状的完整性。
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# Input types
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## Required
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- segs1
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- 'segs1'参数是要被连接的分割集合。它在定义节点的输入数据中起着关键作用，这些数据将被合并为单个分割输出。
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- Comfy dtype: SEGS
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- Python dtype: List[Tuple[Tuple[int, int], List[Any]]]
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# Output types
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- output
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- 'output'参数代表合并过程生成的连接分割。它很重要，因为它是节点的主要输出，包含了合并后的分割数据。
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- Comfy dtype: SEGS
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- Python dtype: Tuple[Tuple[int, int], List[Any]]
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# Usage tips
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- Infra type: CPU
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# Source code
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```
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class SEGSConcat:
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@classmethod
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def INPUT_TYPES(s):
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return {'required': {'segs1': ('SEGS',)}}
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RETURN_TYPES = ('SEGS',)
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FUNCTION = 'doit'
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CATEGORY = 'ImpactPack/Util'
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def doit(self, **kwargs):
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dim = None
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res = None
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for (k, v) in list(kwargs.items()):
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if v[0] == (0, 0) or len(v[1]) == 0:
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continue
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if dim is None:
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dim = v[0]
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res = v[1]
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elif v[0] == dim:
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res = res + v[1]
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else:
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print(f"ERROR: source shape of 'segs1'{dim} and '{k}'{v[0]} are different. '{k}' will be ignored")
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if dim is None:
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empty_segs = ((0, 0), [])
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return (empty_segs,)
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else:
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return ((dim, res),)
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``` |