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import cv2
import torch
import numpy as np
import numpy.typing as npt
from torch import Tensor
from kornia.morphology import erosion, dilation
def clean_mask_torch(mask: Tensor) -> Tensor:
kernel = torch.ones(2, 2).to(mask.device)
if len(mask.shape) == 2:
mask = mask[None, None, :, :]
if mask.dtype == torch.bool:
mask = mask.int()
return dilation(erosion(mask, kernel), kernel)
def clean_mask_np(mask: npt.NDArray) -> npt.NDArray:
kernel = np.ones((2, 2), np.uint8)
return cv2.dilate(cv2.erode(mask, kernel, iterations=1), kernel, iterations=1)
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