Code Monkey home page Code Monkey logo

ssd-resnet50's Introduction

Deprecation notice

This repo is no longer in use or maintained, the detection benchmark in MLCommons was updated to use RetinaNet instead of SSD: https://github.com/mlcommons/training

SSD-ResNet50

This is an experimental repository that is based on Nvidia's SSD-RN50 and is used to test and evaluate the model as the new object detection benchmark for MLPerf training and inference.

Nvidia Deep Learning Examples

MLPerf-SSD

MLCommons

Usage instructions

build and launch the container:

./scripts/docker/build.sh
./scripts/docker/launch_local.sh  # you might want to change the dataset mount location

If necessary, Download MS-COCO dataset

./scripts/download_dataset.sh

To train the model, use any of the training scripts in scripts/train

ssd-resnet50's People

Contributors

ahmadki avatar

Watchers

James Cloos avatar avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.