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        k7  rt        d      | }nt        j                  |t
              }dz   }t        |      }t        | d      }	|j                  D 
cg c]  }
t        d       }}
t        |j                        D ]6  }|||<   d	|t        |      <   |	||<   d	|t        |      <   t        d      ||<   8 t        |d
d	      \  } }t        j                  | |         }t        j                  |dz         }t        j                   ||      }|| j#                  d         j#                  | j                        }|||<   |S c c}
w )a  Clear objects connected to the label image border.

    Parameters
    ----------
    labels : (M[, N[, ..., P]]) array of int or bool
        Imaging data labels.
    buffer_size : int, optional
        The width of the border examined.  By default, only objects
        that touch the outside of the image are removed.
    bgval : float or int, optional
        Cleared objects are set to this value.
    mask : ndarray of bool, same shape as `image`, optional.
        Image data mask. Objects in labels image overlapping with
        False pixels of mask will be removed. If defined, the
        argument buffer_size will be ignored.
    out : ndarray
        Array of the same shape as `labels`, into which the
        output is placed. By default, a new array is created.

    Returns
    -------
    out : (M[, N[, ..., P]]) array
        Imaging data labels with cleared borders

    Examples
    --------
    >>> import numpy as np
    >>> from skimage.segmentation import clear_border
    >>> labels = np.array([[0, 0, 0, 0, 0, 0, 0, 1, 0],
    ...                    [1, 1, 0, 0, 1, 0, 0, 1, 0],
    ...                    [1, 1, 0, 1, 0, 1, 0, 0, 0],
    ...                    [0, 0, 0, 1, 1, 1, 1, 0, 0],
    ...                    [0, 1, 1, 1, 1, 1, 1, 1, 0],
    ...                    [0, 0, 0, 0, 0, 0, 0, 0, 0]])
    >>> clear_border(labels)
    array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
           [0, 0, 0, 0, 1, 0, 0, 0, 0],
           [0, 0, 0, 1, 0, 1, 0, 0, 0],
           [0, 0, 0, 1, 1, 1, 1, 0, 0],
           [0, 1, 1, 1, 1, 1, 1, 1, 0],
           [0, 0, 0, 0, 0, 0, 0, 0, 0]])
    >>> mask = np.array([[0, 0, 1, 1, 1, 1, 1, 1, 1],
    ...                  [0, 0, 1, 1, 1, 1, 1, 1, 1],
    ...                  [1, 1, 1, 1, 1, 1, 1, 1, 1],
    ...                  [1, 1, 1, 1, 1, 1, 1, 1, 1],
    ...                  [1, 1, 1, 1, 1, 1, 1, 1, 1],
    ...                  [1, 1, 1, 1, 1, 1, 1, 1, 1]]).astype(bool)
    >>> clear_border(labels, mask=mask)
    array([[0, 0, 0, 0, 0, 0, 0, 1, 0],
           [0, 0, 0, 0, 1, 0, 0, 1, 0],
           [0, 0, 0, 1, 0, 1, 0, 0, 0],
           [0, 0, 0, 1, 1, 1, 1, 0, 0],
           [0, 1, 1, 1, 1, 1, 1, 1, 0],
           [0, 0, 0, 0, 0, 0, 0, 0, 0]])

    c              3   (   K   | ]	  }|k\    y w)N ).0sbuffer_sizes     ~/home/developers/rajanand/mypropertyqr-fmb-refixing-v2/venv/lib/python3.12/site-packages/skimage/segmentation/_clear_border.py	<genexpr>zclear_border.<locals>.<genexpr>?   s     
2;!
2s   Nz/buffer size may not be greater than labels sizez3labels and mask should have the same shape but are z and zmask should be of type bool.)dtype   Tr   )
background
return_num)anyshape
ValueErrorcopyr   bool	TypeErrornp
zeros_likeslicerangendimtupler   uniquearangeisinreshape)labelsr   bgvalmaskr   err_msgbordersextslstartslend_slicesdnumberborders_indicesindices
label_masks    `               r   clear_borderr2      s   r 
2V\\
22t|JKK
{kkm99+U4::,0 	 99

"w'':::;;% --40Ao*sdD!'*yy1!%+11sxx 	$AF1I%)GE&M"F1I%)GE&M"dF1I	$ 31>NFF iiw0Oii
#G/2JfnnR()11&,,?D CIJ/ 2s   &G)r   r   N)numpyr   measurer   r2   r       r   <module>r6      s     g4 gr5   