SSD-ResNet34 Int8 Inference Tensorflow* Container

Pull Command

docker pull intel/object-detection:tf-2.3.0-imz-2.0.0-ssd-resnet34-int8-inference

Description

This document has instructions for running SSD-ResNet34 Int8 inference using Intel® Optimizations for TensorFlow*.

SSD-ResNet34 uses the COCO dataset for accuracy testing.

Download and preprocess the COCO validation images using the instructions here. After the script to convert the raw images to the TF records file completes, rename the tf_records file:

$ mv ${OUTPUT_DIR}/coco_val.record ${OUTPUT_DIR}/validation-00000-of-00001

Set the DATASET_DIR to the folder that has the validation-00000-of-00001 file when running the accuracy test. Note that the inference performance test uses synthetic dataset.

Quick Start Scripts

Script name Description
int8_inference.sh Run inference using synthetic data and outputs performance metrics.
int8_accuracy.sh Tests accuracy using the COCO dataset in the TF Records format.

Docker

The model container includes the pretrained model, scripts and libraries needed to run SSD-ResNet34 Int8 inference. To run one of the quickstart scripts using this container, you'll need to provide a volume mount for an output directory where logs will be written. If you are testing accuracy, then the directory where the coco dataset validation-00000-of-00001 file located will also need to be mounted.

To run inference using synthetic data:

OUTPUT_DIR=<directory where log files will be written>

docker run \
  --env OUTPUT_DIR=${OUTPUT_DIR} \
  --env http_proxy=${http_proxy} \
  --env https_proxy=${https_proxy} \
  --volume ${OUTPUT_DIR}:${OUTPUT_DIR} \
  --privileged --init -t \
  intel/object-detection:tf-2.3.0-imz-2.0.0-ssd-resnet34-int8-inference \
  /bin/bash quickstart/int8_inference.sh

To test accuracy using the COCO dataset:

DATASET_DIR=<path to the COCO 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-2.3.0-imz-2.0.0-ssd-resnet34-int8-inference \
  /bin/bash quickstart/int8_accuracy.sh

 

Documentation and Sources

Get Started
Docker Repo
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.


Related Containers and Solutions

SSD-Resnet34 Int8 Inference TensorFlow* Model Package

Product and Performance Information

1

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804