gauravkaila

import tensorflow as tf

# Assuming object detection API is available for use
from object_detection.utils.config_util import create_pipeline_proto_from_configs
from object_detection.utils.config_util import get_configs_from_pipeline_file
import object_detection.exporter

# Configuration for model to be exported
config_pathname = ${Model_configuration}

gauravkaila

_write_saved_model(saved_model_path, trained_checkpoint_prefix,
                     placeholder_tensor, outputs)

gauravkaila

def _write_saved_model(saved_model_path,
                       trained_checkpoint_prefix,
                       inputs,
                       outputs):
  """Writes SavedModel to disk.
  Args:
    saved_model_path: Path to write SavedModel.
    trained_checkpoint_prefix: path to trained_checkpoint_prefix.
    inputs: The input image tensor to use for detection.
    outputs: A tensor dictionary containing the outputs of a DetectionModel.