class_docstr: Generate the ground truth targets of FCENet: Fourier Contour Embedding
  for Arbitrary-Shaped Text Detection.
  
  [https://arxiv.org/abs/2104.10442]
  
  Args:
      fourier_degree (int): The maximum Fourier transform degree k.
      resample_step (float): The step size for resampling the text center
          line (TCL). It's better not to exceed half of the minimum width.
      center_region_shrink_ratio (float): The shrink ratio of text center
          region.
      level_size_divisors (tuple(int)): The downsample ratio on each level.
      level_proportion_range (tuple(tuple(int))): The range of text sizes
          assigned to each level.
docstr: Generate the ground truth targets for FCENet.
  
  Args:
      results (dict): The input result dictionary.
  
  Returns:
      results (dict): The output result dictionary.
docstr_tok: ["Generate","the","ground","truth","targets","for","FCENet",".","Args",":","results","(","dict",")",":","The","input","result","dictionary",".","Returns",":","results","(","dict",")",":","The","output","result","dictionary","."]
code: def generate_targets(self, results):
      """Generate the ground truth targets for FCENet.
  
      Args:
          results (dict): The input result dictionary.
  
      Returns:
          results (dict): The output result dictionary.
      """
  
      assert isinstance(results, dict)
      image = results["image"]
      polygons = results["polys"]
      ignore_tags = results["ignore_tags"]
      h, w, _ = image.shape
  
      polygon_masks = []
      polygon_masks_ignore = []
      for tag, polygon in zip(ignore_tags, polygons):
          if tag is True:
              polygon_masks_ignore.append(polygon)
          else:
              polygon_masks.append(polygon)
  
      level_maps = self.generate_level_targets(
          (h, w), polygon_masks, polygon_masks_ignore
      )
  
      mapping = {
          "p3_maps": level_maps[0],
          "p4_maps": level_maps[1],
          "p5_maps": level_maps[2],
      }
      for key, value in mapping.items():
          results[key] = value
  
      return results
  
imports: import cv2
  import numpy
  from numpy.fft import fft
  from numpy.linalg import norm
  import sys
label_desc: Use image node_id 17 for calling the FCENetTargets obj's underlying member method code with example usage: obj.generate_targets(results) and returns: results