Выходное состояние модуля обнаружения тензорного объекта

Question

Следующий код является частью кода обнаружения объекта тензорного потока, который я скачал с github .

#intializing the web camera device

import cv2
cap = cv2.VideoCapture(0)
# Running the tensorflow session
with detection_graph.as_default():
  with tf.Session(graph=detection_graph) as sess:
   ret = True
   while (ret):
      ret,image_np = cap.read()
      # Expand dimensions since the model expects images to have shape: [1, None, None, 3]
      image_np_expanded = np.expand_dims(image_np, axis=0)
      image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
      # Each box represents a part of the image where a particular object was detected.
      boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
      # Each score represent how level of confidence for each of the objects.
      # Score is shown on the result image, together with the class label.
      scores = detection_graph.get_tensor_by_name('detection_scores:0')
      classes = detection_graph.get_tensor_by_name('detection_classes:0')
      num_detections = detection_graph.get_tensor_by_name('num_detections:0')
      # Actual detection.
      (boxes, scores, classes, num_detections) = sess.run(
          [boxes, scores, classes, num_detections],
          feed_dict={image_tensor: image_np_expanded})
      # Visualization of the results of a detection.
      vis_util.visualize_boxes_and_labels_on_image_array(
          image_np,
          np.squeeze(boxes),
          np.squeeze(classes).astype(np.int32),
          np.squeeze(scores),
          category_index,
          use_normalized_coordinates=True,
          line_thickness=8)

      cv2.imshow('image',cv2.resize(image_np,(900,600)))
      if cv2.waitKey(25) & 0xFF == ord('q'):
          cv2.destroyAllWindows()
          cap.release()
          break

Я хочу, чтобы это условие выхода if cv2.waitKey(25) & 0xFF == ord('q'): было запущено, когда функция возвращает какое-либо значение, например True.

Как я могу это сделать?