Optimize an R-FCN Int8 Inference Container with TensorFlow*

Published: 11/09/2020  

Last Updated: 06/15/2022

Pull Command

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

Description

This document has instructions for running R-FCN int8 inference using Intel® Optimization for TensorFlow*.

The COCO validation dataset is used in these R-FCN quick start scripts. The inference quick start scripts use raw images, and the accuracy quick start scripts require the dataset to be converted into the TensorFlow* 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 a directory of raw images for 500 steps and outputs performance metrics.
int8_accuracy Processes the TensorFlow* records to run inference and check accuracy on the results.

Docker*

The model container includes the scripts and libraries needed to run R-FCN 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.

To run inference with performance metrics:

DATASET_DIR=<path to the coco val2017 directory>
OUTPUT_DIR=<directory where log files will be written>

docker run \
  --env DATASET_DIR=${DATASET_DIR} \
  --env OUTPUT_DIR=${OUTPUT_DIR} \
  --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-rfcn-int8-inference \
  /bin/bash quickstart/<script name>.sh

To get accuracy metrics:

DATASET_DIR=<path to the COCO validation TF record directory>
OUTPUT_DIR=<directory where log files will be written>

docker run \
  --env DATASET_DIR=${DATASET_DIR} \
  --env OUTPUT_DIR=${OUTPUT_DIR} \
  --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-rfcn-int8-inference \
  /bin/bash quickstart/<script name>.sh

 

Documentation and Sources

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

Code Sources
Dockerfile
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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R-FCN Int8 Inference TensorFlow* Model Package

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Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.