61 lines
3.0 KiB
Markdown
61 lines
3.0 KiB
Markdown
# Documentation
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- Class name: BitwiseAndMaskForEach
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- Category: ImpactPack/Operation
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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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BitwiseAndMaskForEach节点的'doit'方法对段进行位运算，使用掩码确定重叠区域。它处理每个基础段与一组掩码段，识别重叠区域，并对非重叠区域应用掩码以消除它们。此方法对于细化分割结果至关重要，确保只保留真正重叠的区域。
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# Input types
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## Required
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- base_segs
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- 'base_segs'参数是一系列将由节点处理的分割对象集合。它至关重要，因为它构成了与掩码段进行位运算的基础。该参数直接影响节点执行的结果，决定了哪些段被考虑用于重叠检测。
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- Comfy dtype: SEGS
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- Python dtype: List[SEG]
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- mask_segs
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- 'mask_segs'参数由作为位运算掩码的分割对象组成。它至关重要，因为它定义了操作后要保留的区域。该参数在塑造节点的最终输出方面起着重要作用，通过指定要考虑重叠并应在操作后保留的区域。
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- Comfy dtype: SEGS
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- Python dtype: List[SEG]
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# Output types
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- result
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- 'result'输出是经过位运算处理的分割对象列表。它只包含基础段和掩码段之间有重叠的段。这个输出很重要，因为它代表了操作后细化的分割数据。
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- Comfy dtype: SEGS
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- Python dtype: Tuple[str, List[SEG]]
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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 BitwiseAndMaskForEach:
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@classmethod
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def INPUT_TYPES(s):
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return {'required': {'base_segs': ('SEGS',), 'mask_segs': ('SEGS',)}}
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RETURN_TYPES = ('SEGS',)
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FUNCTION = 'doit'
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CATEGORY = 'ImpactPack/Operation'
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def doit(self, base_segs, mask_segs):
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result = []
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for bseg in base_segs[1]:
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cropped_mask1 = bseg.cropped_mask.copy()
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crop_region1 = bseg.crop_region
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for mseg in mask_segs[1]:
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cropped_mask2 = mseg.cropped_mask
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crop_region2 = mseg.crop_region
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intersect_region = (max(crop_region1[0], crop_region2[0]), max(crop_region1[1], crop_region2[1]), min(crop_region1[2], crop_region2[2]), min(crop_region1[3], crop_region2[3]))
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overlapped = False
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for i in range(intersect_region[0], intersect_region[2]):
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for j in range(intersect_region[1], intersect_region[3]):
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if cropped_mask1[j - crop_region1[1], i - crop_region1[0]] == 1 and cropped_mask2[j - crop_region2[1], i - crop_region2[0]] == 1:
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overlapped = True
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pass
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else:
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cropped_mask1[j - crop_region1[1], i - crop_region1[0]] = 0
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if overlapped:
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item = SEG(bseg.cropped_image, cropped_mask1, bseg.confidence, bseg.crop_region, bseg.bbox, bseg.label, None)
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result.append(item)
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return ((base_segs[0], result),)
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``` |