text: import os
  
  from ndu_gate_camera.api.ndu_camera_runner import NDUCameraRunner
  from ndu_gate_camera.utility import onnx_helper, yolo_helper, constants
  from ndu_gate_camera.utility.geometry_helper import *
  from ndu_gate_camera.utility.ndu_utility import NDUUtility
  
  
  class TranspaletDetectorRunner(NDUCameraRunner):
      def __init__(self, config, connector_type):
          super().__init__()
  
          # onnx_fn = "/data/transpalet_last.onnx"
          onnx_fn = "/data/transpalet_best.onnx"
          self.input_size = 608
  
          if not os.path.isfile(onnx_fn):
              onnx_fn = os.path.dirname(os.path.abspath(__file__)) + onnx_fn.replace("/", os.path.sep)
  
          classes_filename = "/data/class.names"
          if not os.path.isfile(classes_filename):
              classes_filename = os.path.dirname(os.path.abspath(__file__)) + classes_filename.replace("/", os.path.sep)
          self.class_names = onnx_helper.parse_class_names(classes_filename)
          self.sess_tuple = onnx_helper.get_sess_tuple(onnx_fn, config.get("max_engine_count", 0))
  
      def get_name(self):
          return "transpalet_detector"
  
      def get_settings(self):
          settings = {}
          return settings
  
      def process_frame(self, frame, extra_data=None):
          super().process_frame(frame)
          # return yolo_helper.predict_v5(self.sess_tuple, self.input_size, self.class_names, frame)
          return yolo_helper.predict_v4(self.sess_tuple, self.input_size, self.class_names, frame)
  