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: Computes the output shapes given the input shapes.
  
  Args
      input_shape : List of input shapes [boxes, classification, other[0], other[1], ...].
  
  Returns
      List of tuples representing the output shapes:
      [filtered_boxes.shape, filtered_scores.shape, filtered_labels.shape, filtered_other[0].shape, filtered_other[1].shape, ...]
docstr_tok: ["Computes","the","output","shapes","given","the","input","shapes",".","Args","input_shape",":","List","of","input","shapes","[","boxes",",","classification",",","other","[","0","]",",","other","[","1","]",",","...","]",".","Returns","List","of","tuples","representing","the","output","shapes",":","[","filtered_boxes.shape",",","filtered_scores.shape",",","filtered_labels.shape",",","filtered_other","[","0","]",".shape",",","filtered_other","[","1","]",".shape",",","...","]"]
code: def compute_output_shape(self, input_shape):
      """Computes the output shapes given the input shapes.
  
      Args
          input_shape : List of input shapes [boxes, classification, other[0], other[1], ...].
  
      Returns
          List of tuples representing the output shapes:
          [filtered_boxes.shape, filtered_scores.shape, filtered_labels.shape, filtered_other[0].shape, filtered_other[1].shape, ...]
      """
      return [
          (input_shape[0][0], self.max_detections, 4),
          (input_shape[1][0], self.max_detections),
          (input_shape[1][0], self.max_detections),
      ] + [
          tuple(
              [input_shape[i][0], self.max_detections]
              + list(input_shape[i][2:])
          )
          for i in range(2, len(input_shape))
      ]
  
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 3 for calling the FilterDetections obj's underlying member method code with example usage: obj.compute_output_shape(input_shape) and returns: unknown