from_array#

static rlemasklib.RLEMask.from_array(mask_array, thresh128=False, is_sparse=True)[source]#

Create an RLEMask object from a dense mask.

By default, any nonzero value is considered foreground and zero is considered background. If thresh128 is set to True, then values greater than or equal to 128 are considered foreground and less than 128 are considered background.

If mask_array is C contiguous, a transpose has to take place since the internal RLE format encodes the mask in Fortran order. If is_sparse is set to True, the transpose, if necessary, will be performed in RLE format, otherwise it will be performed in dense array format.

Parameters:

  • mask_array (ndarray) – a numpy array of numerical type where nonzero means foreground and zero means background.

  • thresh128 (bool) – whether to use 128 as the threshold for binarization (default is 1)

  • is_sparse (bool) – hint that it is more efficient to transpose the mask in RLE form, only affects efficiency when the mask is C contiguous.

Return type:

RLEMask