Use Intel® Optimizations for TensorFlow* to run a MobileNet* SSD FP32 Inference

ID 679180
Updated 6/15/2022
Version Latest



Pull Command

docker pull intel/object-detection:tf-latest-ssd-mobilenet-fp32-inference


This document has instructions for running SSD-MobileNet FP32 inference using Intel® Optimizations for TensorFlow*.

The COCO validation dataset is used in these SSD-Mobilenet quickstart scripts. The inference and accuracy quickstart 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
fp32_inference Runs inference on TF records and outputs performance metrics.
fp32_accuracy Processes the TF records to run inference and check accuracy on the results.


When running in docker, the SSD-MobileNet FP32 inference container includes the libraries and the model package, which are needed to run SSD-MobileNet FP32 inference. To run the quickstart scripts, you'll need to provide volume mounts for the COCO validation dataset TF Record file and an output directory where log files will be written.

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-fp32-inference \
  /bin/bash quickstart/<script name>.sh

Documentation and Sources

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