从图像获取对象名称并将其写入文件

Question

我使用Tensorflow对象检测API在图像中指定对象的名称 我想将这些名称写到文件中，而不是在图像上显示它们，但是我找不到该变量的使用位置

def run_inference_for_single_image(image, graph):
  with graph.as_default():
  with tf.Session() as sess:
   # Get handles to input and output tensors
  ops = tf.get_default_graph().get_operations()
  all_tensor_names = {output.name for op in ops for output in op.outputs}
  tensor_dict = {}
  for key in [
      'num_detections', 'detection_boxes', 'detection_scores',
      'detection_classes', 'detection_masks'
  ]:
    tensor_name = key + ':0'
    if tensor_name in all_tensor_names:
      tensor_dict[key] = tf.get_default_graph().get_tensor_by_name(
          tensor_name)

  if 'detection_masks' in tensor_dict:
    # The following processing is only for single image
    detection_boxes = tf.squeeze(tensor_dict['detection_boxes'], [0])
    detection_masks = tf.squeeze(tensor_dict['detection_masks'], [0])
    # Reframe is required to translate mask from box coordinates to image coordinates and fit the image size.
    real_num_detection = tf.cast(tensor_dict['num_detections'][0], tf.int32)
    detection_boxes = tf.slice(detection_boxes, [0, 0], [real_num_detection, -1])
    detection_masks = tf.slice(detection_masks, [0, 0, 0], [real_num_detection, -1, -1])
    detection_masks_reframed = utils_ops.reframe_box_masks_to_image_masks(
        detection_masks, detection_boxes, image.shape[1], image.shape[2])
    detection_masks_reframed = tf.cast(
        tf.greater(detection_masks_reframed, 0.5), tf.uint8)
    # Follow the convention by adding back the batch dimension
    tensor_dict['detection_masks'] = tf.expand_dims(
        detection_masks_reframed, 0)
  image_tensor = tf.get_default_graph().get_tensor_by_name('image_tensor:0')
  # Run inference
  output_dict = sess.run(tensor_dict,
                         feed_dict={image_tensor: image})

  # all outputs are float32 numpy arrays, so convert types as appropriate
  output_dict['num_detections'] = int(output_dict['num_detections'][0])
  output_dict['detection_classes'] = output_dict[
      'detection_classes'][0].astype(np.int64)
  output_dict['detection_boxes'] = output_dict['detection_boxes'][0]
  output_dict['detection_scores'] = output_dict['detection_scores'][0]
  if 'detection_masks' in output_dict:
    output_dict['detection_masks'] = output_dict['detection_masks'][0]
  print(output_dict['num_detections'])
return output_dict