code: def main():
      args = argsparser()
      if args.device == "gpu" and paddle.is_compiled_with_cuda():
          place = "gpu"
      elif args.device == "xpu" and paddle.is_compiled_with_xpu():
          place = "xpu"
      elif args.device == "npu" and paddle.is_compiled_with_npu():
          place = "npu"
      elif args.device == "mlu" and paddle.is_compiled_with_mlu():
          place = "mlu"
      else:
          place = "cpu"
      paddle.set_device(place)
  
      inputs = os.path.abspath(args.input)
      pipeline = Pipeline(args)
      result = pipeline.run(inputs)
      return result
  
file_path: PaddleSeg/contrib/QualityInspector/tools/end2end/predict.py
imports: from __future__ import absolute_import, division, print_function
  import os
  import sys
  import paddle
  from qinspector.apis.pipeline import Pipeline
  from qinspector.cvlib.configs import ArgsParser
label_desc: Use image node_id 2 for calling a global function with example usage: main() and returns: result