Run MobileNet* SSD Int8 Inference Using a TensorFlow* Container

Published: 11/09/2020  

Last Updated: 06/15/2022

Pull Command

docker pull intel/object-detection:tf-latest-ssd-mobilenet-int8-inference


This document has instructions for running MobileNet SSD Int8 inference using Intel® Optimization for TensorFlow*.

The COCO validation dataset is used in these Mobilenet SSD quick start scripts. The inference and accuracy quick start scripts require the dataset to be converted into the TF records format. See the COCO dataset for instructions on downloading and preprocessing the COCO validation dataset.

Quick Start Scripts

Script name Description
int8_inference Runs inference on TF records and outputs performance metrics.
int8_accuracy Runs inference and checks accuracy on the results.


The model container includes the scripts and libraries needed to run MobileNet SSD Int8 inference. To run one of the quick start scripts using this container, you'll need to provide volume mounts for the dataset and an output directory.

DATASET_DIR=<path to the coco tf record file>
OUTPUT_DIR=<directory where log files will be written>

docker run \
  --env http_proxy=${http_proxy} \
  --env https_proxy=${https_proxy} \
  --volume ${DATASET_DIR}:${DATASET_DIR} \
  --volume ${OUTPUT_DIR}:${OUTPUT_DIR} \
  --privileged --init -t \
  intel/object-detection:tf-latest-ssd-mobilenet-int8-inference \
  /bin/bash quickstart/<script name>.sh

Documentation and Sources

Get Started​
Docker* Repository
Main GitHub*
Release Notes
Get Started Guide

Code Sources
Report Issue

License Agreement

LEGAL NOTICE: By accessing, downloading or using this software and any required dependent software (the “Software Package”), you agree to the terms and conditions of the software license agreements for the Software Package, which may also include notices, disclaimers, or license terms for third party software included with the Software Package. Please refer to the license file for additional details.

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MobileNet SSD Int8 Inference TensorFlow* Model Package

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Product and Performance Information


Performance varies by use, configuration and other factors. Learn more at