Pull Command
docker pull intel/object-detection:tf-latest-ssd-mobilenet-fp32-inference
Description
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. |
Docker
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 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-ssd-mobilenet-fp32-inference \
/bin/bash quickstart/<script name>.sh
Documentation and Sources
Get Started
Docker Repo
Main GitHub
Readme
Release Notes
Get Started Guide
Code Sources
Dockerfile
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License Agreement
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