问如何使用EfficientNet Lite模型作为关键点回归的主干？

EN

# Get mobile-friendly CenterNet for Keypoint detection task.
# See TensorFlow 2 Detection Model Zoo for more details:
# https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf2_detection_zoo.md

wget http://download.tensorflow.org/models/object_detection/tf2/20210210/centernet_mobilenetv2fpn_512x512_coco17_kpts.tar.gz
tar -xf centernet_mobilenetv2fpn_512x512_coco17_kpts.tar.gz
rm centernet_mobilenetv2fpn_512x512_coco17_kpts.tar.gz*

# Export the intermediate SavedModel that outputs 10 detections & takes in an 
# image of dim 320x320.
# Modify these parameters according to your needs.

python models/research/object_detection/export_tflite_graph_tf2.py \
  --pipeline_config_path=centernet_mobilenetv2_fpn_kpts/pipeline.config \
  --trained_checkpoint_dir=centernet_mobilenetv2_fpn_kpts/checkpoint \
  --output_directory=centernet_mobilenetv2_fpn_kpts/tflite \
  --centernet_include_keypoints=true \
  --keypoint_label_map_path=centernet_mobilenetv2_fpn_kpts/label_map.txt \
  --max_detections=10 \
  --config_override=" \
    model{ \
      center_net { \
        image_resizer { \
          fixed_shape_resizer { \
            height: 320 \
            width: 320 \
          } \
        } \
      } \
    }"

tflite_convert --output_file=centernet_mobilenetv2_fpn_kpts/model.tflite \
  --saved_model_dir=centernet_mobilenetv2_fpn_kpts/tflite/saved_model