code: def create_gradio_app(self):
      import gradio as gr
      import tempfile
      import os
      from PIL import Image
  
      def inference(image, shrink, confs_threshold):
          with tempfile.TemporaryDirectory() as temp_dir:
              self.face_detection(
                  paths=[image],
                  use_gpu=False,
                  visualization=True,
                  output_dir=temp_dir,
                  shrink=shrink,
                  confs_threshold=confs_threshold,
              )
              return Image.open(
                  os.path.join(temp_dir, os.listdir(temp_dir)[0])
              )
  
      interface = gr.Interface(
          inference,
          [
              gr.inputs.Image(type="filepath"),
              gr.Slider(0.0, 1.0, 0.5, step=0.01),
              gr.Slider(0.0, 1.0, 0.6, step=0.01),
          ],
          gr.outputs.Image(type="ndarray"),
          title="pyramidbox_lite_mobile_mask",
      )
      return interface
  
imports: from __future__ import absolute_import
  from __future__ import division
  import argparse
  import ast
  import os
  import numpy
  from paddle.inference import Config
  from paddle.inference import create_predictor
  import paddlehub
  from .data_feed import reader
  from .processor import base64_to_cv2
  from .processor import postprocess
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.module import runnable
  from paddlehub.module.module import serving
label_desc: Use image node_id 10 for calling the PyramidBoxLiteMobileMask obj's underlying member method code with example usage: obj.create_gradio_app() and returns: interface, Image