code: def predict_single_image(self, style_input, text_input):
      style_input = self.rep_style_input(style_input, text_input)
      tensor_style_input = self.preprocess(style_input)
      tensor_text_input = self.preprocess(text_input)
      style_text_result = self.generator.forward(
          tensor_style_input, tensor_text_input
      )
      fake_fusion = self.postprocess(style_text_result["fake_fusion"])
      fake_text = self.postprocess(style_text_result["fake_text"])
      fake_sk = self.postprocess(style_text_result["fake_sk"])
      fake_bg = self.postprocess(style_text_result["fake_bg"])
      bbox = self.get_text_boundary(fake_text)
      if bbox:
          left, right, top, bottom = bbox
          fake_fusion = fake_fusion[top:bottom, left:right, :]
          fake_text = fake_text[top:bottom, left:right, :]
          fake_sk = fake_sk[top:bottom, left:right, :]
          fake_bg = fake_bg[top:bottom, left:right, :]
  
      # fake_fusion = self.crop_by_text(img_fake_fusion, img_fake_text)
      return {
          "fake_fusion": fake_fusion,
          "fake_text": fake_text,
          "fake_sk": fake_sk,
          "fake_bg": fake_bg,
      }
  
file_path: PaddleOCR/StyleText/engine/predictors.py
imports: import numpy
  import cv2
  import math
  import paddle
  from arch import style_text_rec
  from utils.sys_funcs import check_gpu
  from utils.logging import get_logger
label_desc: Use image node_id 3 for calling the StyleTextRecPredictor obj's underlying member method code with example usage: obj.predict_single_image(style_input, text_input) and returns: dict