class_docstr: Keras layer for filtering detections using score threshold and NMS.
      
class_docstr_tok: ["Keras","layer","for","filtering","detections","using","score","threshold","and","NMS","."]
docstr: Gets the configuration of this layer.
  
  Returns
      Dictionary containing the parameters of this layer.
docstr_tok: ["Gets","the","configuration","of","this","layer",".","Returns","Dictionary","containing","the","parameters","of","this","layer","."]
code: def get_config(self):
      """Gets the configuration of this layer.
  
      Returns
          Dictionary containing the parameters of this layer.
      """
      config = super(FilterDetections, self).get_config()
      config.update(
          {
              "nms": self.nms,
              "class_specific_filter": self.class_specific_filter,
              "nms_threshold": self.nms_threshold,
              "score_threshold": self.score_threshold,
              "max_detections": self.max_detections,
              "parallel_iterations": self.parallel_iterations,
          }
      )
  
      return config
  
file_path: ImageAI/imageai_tf_deprecated/Detection/keras_retinanet/layers/filter_detections.py
imports: import tensorflow
  from tensorflow import keras
  from ..None import backend
label_desc: Use image node_id 5 for calling the FilterDetections obj's underlying member method code with example usage: obj.get_config() and returns: config