def count_object(network, class_ids, scores, bounding_boxes, object_label, threshold=0.75):
    """
    Counts objects of a given type that are predicted by the network.

    :param network: object detection network
    :type network: mx.gluon.nn.Block
    :param class_ids: predicted object class indexes (e.g. 123)
    :type class_ids: mx.nd.NDArrays
    :param scores: predicted object confidence
    :type scores: mx.nd.NDArrays
    :param bounding_boxes: predicted object locations
    :type bounding_boxes: mx.nd.NDArrays
    :param object_label: object to be counted (e.g. "person")
    :type object_label: str
    :param threshold: required confidence for object to be counted
    :type threshold: float
    
    :return: number of objects that are predicted by the network.
    :rtype: int
    """
    detected_objects=0
    while(scores[0][detected_objects]>threshold):
        detected_objects+=1
    count=0
    reqd_idx = network.classes.index(object_label)
    for idx in class_ids[0][:detected_objects]:
        if (idx==reqd_idx):
            count+=1
    return count