code: def get_detector(net, prefix, epoch, data_shape, mean_pixels, ctx, num_class,
                   nms_thresh=0.5, force_nms=True, nms_topk=400):
      
      if net is not None:
          if isinstance(data_shape, tuple):
              data_shape = data_shape[0]
          net = get_symbol(net, data_shape, num_classes=num_class, nms_thresh=nms_thresh,
              force_nms=force_nms, nms_topk=nms_topk)
      detector = Detector(net, prefix, epoch, data_shape, mean_pixels, ctx=ctx)
      return detector
docs: wrapper for initialize a detector
  
      Parameters:
      ----------
      net : str
          test network name
      prefix : str
          load model prefix
      epoch : int
          load model epoch
      data_shape : int
          resize image shape
      mean_pixels : tuple (float, float, float)
          mean pixel values (R, G, B)
      ctx : mx.ctx
          running context, mx.cpu() or mx.gpu(?)
      num_class : int
          number of classes
      nms_thresh : float
          non-maximum suppression threshold
      force_nms : bool
          force suppress different categories