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from .imagefunc import *
NODE_NAME = 'CheckMaskV2'
# 检查mask是否有效,如果mask面积少于指定比例则判为无效mask
class CheckMaskV2:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
method_list = ['simple', 'detect_percent']
blank_mask_list = ['white', 'black']
return {
"required": {
"mask": ("MASK",), #
"method": (method_list,), #
"white_point": ("INT", {"default": 1, "min": 1, "max": 254, "step": 1}), # 用于判断mask是否有效的白点值,高于此值被计入有效
"area_percent": ("FLOAT", {"default": 0.01, "min": 0, "max": 100, "step": 0.01}), # 区域百分比,低于此则mask判定无效
},
"optional": { #
}
}
RETURN_TYPES = ("BOOLEAN",)
RETURN_NAMES = ('bool',)
FUNCTION = 'check_mask_v2'
CATEGORY = '😺dzNodes/LayerUtility'
def check_mask_v2(self, mask, method, white_point, area_percent,):
if mask.dim() == 2:
mask = torch.unsqueeze(mask, 0)
tensor_mask = mask[0]
print(f"tensor_mask={tensor_mask},shape is {tensor_mask.shape}")
pil_mask = tensor2pil(tensor_mask)
if pil_mask.width * pil_mask.height > 262144:
target_width = 512
target_height = int(target_width * pil_mask.height / pil_mask.width)
pil_mask = pil_mask.resize((target_width, target_height), Image.LANCZOS)
ret_bool = False
if method == 'simple':
ret_bool = is_valid_mask(tensor_mask)
else:
ret_bool = mask_white_area(pil_mask, white_point) * 100 > area_percent
return (ret_bool,)
NODE_CLASS_MAPPINGS = {
"LayerUtility: CheckMaskV2": CheckMaskV2
}
NODE_DISPLAY_NAME_MAPPINGS = {
"LayerUtility: CheckMaskV2": "LayerUtility: Check Mask V2"
}