def get_arr_int(self, background_threshold=<NUM_LIT>, background_class_id=None):
if self.input_was[<NUM_LIT:0>] in ["<STR_LIT:bool>", "<STR_LIT:float>"]:<EOL><INDENT>ia.do_assert(background_class_id is None,<EOL>"<STR_LIT>"<EOL>+ "<STR_LIT>")<EOL><DEDENT>if background_class_id is None:<EOL><INDENT>background_class_id = <NUM_LIT:0><EOL><DEDENT>channelwise_max_idx = np.argmax(self.arr, axis=<NUM_LIT:2>)<EOL>if self.input_was[<NUM_LIT:0>] in ["<STR_LIT:bool>", "<STR_LIT:float>"]:<EOL><INDENT>result = <NUM_LIT:1> + channelwise_max_idx<EOL><DEDENT>else:  <EOL><INDENT>result = channelwise_max_idx<EOL><DEDENT>if background_threshold is not None and background_threshold > <NUM_LIT:0>:<EOL><INDENT>probs = np.amax(self.arr, axis=<NUM_LIT:2>)<EOL>result[probs < background_threshold] = background_class_id<EOL><DEDENT>return result.astype(np.int32)<EOL>
Get the segmentation map array as an integer array of shape (H, W).

Each pixel in that array contains an integer value representing the pixel's class.
If multiple classes overlap, the one with the highest local float value is picked.
If that highest local value is below `background_threshold`, the method instead uses
the background class id as the pixel's class value.
By default, class id 0 is the background class. This may only be changed if the original
input to the segmentation map object was an integer map.

Parameters
----------
background_threshold : float, optional
    At each pixel, each class-heatmap has a value between 0.0 and 1.0. If none of the
    class-heatmaps has a value above this threshold, the method uses the background class
    id instead.

background_class_id : None or int, optional
    Class id to fall back to if no class-heatmap passes the threshold at a spatial
    location. May only be provided if the original input was an integer mask and in these
    cases defaults to 0. If the input were float or boolean masks, the background class id
    may not be set as it is assumed that the background is implicitly defined
    as 'any spatial location that has zero-like values in all masks'.

Returns
-------
result : (H,W) ndarray
    Segmentation map array (int32).
    If the original input consisted of boolean or float masks, then the highest possible
    class id is ``1+C``, where ``C`` is the number of provided float/boolean masks. The value
    ``0`` in the integer mask then denotes the background class.