1.7 KiB
1.7 KiB
Documentation
- Class name: SEGSConcat
- Category: ImpactPack/Util
- Output node: False
- Repo Ref: https://github.com/ltdrdata/ComfyUI-Impact-Pack.git
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。
Input types
Required
- segs1
- '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。
- Comfy dtype: SEGS
- Python dtype: List[Tuple[Tuple[int, int], List[Any]]]
Output types
- output
- '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。
- Comfy dtype: SEGS
- Python dtype: Tuple[Tuple[int, int], List[Any]]
Usage tips
- Infra type: CPU
Source code
class SEGSConcat:
@classmethod
def INPUT_TYPES(s):
return {'required': {'segs1': ('SEGS',)}}
RETURN_TYPES = ('SEGS',)
FUNCTION = 'doit'
CATEGORY = 'ImpactPack/Util'
def doit(self, **kwargs):
dim = None
res = None
for (k, v) in list(kwargs.items()):
if v[0] == (0, 0) or len(v[1]) == 0:
continue
if dim is None:
dim = v[0]
res = v[1]
elif v[0] == dim:
res = res + v[1]
else:
print(f"ERROR: source shape of 'segs1'{dim} and '{k}'{v[0]} are different. '{k}' will be ignored")
if dim is None:
empty_segs = ((0, 0), [])
return (empty_segs,)
else:
return ((dim, res),)