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Exporting a trained model for inference

TensorFlow 1.15

After your model has been trained, you should export it to a TensorFlow graph proto. A checkpoint will typically consist of three files:

  • model.ckpt-${CHECKPOINT_NUMBER}.data-00000-of-00001
  • model.ckpt-${CHECKPOINT_NUMBER}.index
  • model.ckpt-${CHECKPOINT_NUMBER}.meta

After you've identified a candidate checkpoint to export, run the following command from tensorflow/models/research:

# From tensorflow/models/research/
PIPELINE_CONFIG_PATH={path to pipeline config file}
TRAINED_CKPT_PREFIX={path to model.ckpt}
EXPORT_DIR={path to folder that will be used for export}
python object_detection/ \
    --input_type=${INPUT_TYPE} \
    --pipeline_config_path=${PIPELINE_CONFIG_PATH} \
    --trained_checkpoint_prefix=${TRAINED_CKPT_PREFIX} \

NOTE: We are configuring our exported model to ingest 4-D image tensors. We can also configure the exported model to take encoded images or serialized tf.Examples.

After export, you should see the directory ${EXPORT_DIR} containing the following:

  • saved_model/, a directory containing the saved model format of the exported model
  • frozen_inference_graph.pb, the frozen graph format of the exported model
  • model.ckpt.*, the model checkpoints used for exporting
  • checkpoint, a file specifying to restore included checkpoint files
  • pipeline.config, pipeline config file for the exported model