Spaces:
Running
on
Zero
Running
on
Zero
| 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 | |
| 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" | |
| } |