Facebook’s AI team Releases Detectron – A Platform for Object Detection Research

Last Updated : 23 Jan, 2018
2 min read

We covered Google’s Cloud AutoML Vision last week and, as we predicted, Facebook has already come out with a platform for object detection of it’s own – Detectron.

                                                                          Source: Facebook

Detectron is a software system developed by Facebook’s AI Research team (FAIR) that “implements state-of the art object detection algorithms”. It is written in Python and leverages the Caffee2 deep learning framework underneath.

Detectron aims to provide a high quality and industry standard codebase for object detection research. The results it has posted are incredibly accurate. The image above shows the prediction power of the software. The following object related algorithms are embedded in Detectron:

  • Mask R-CNN
  • RetinaNet
  • Faster R-CNN
  • RPN
  • Fast R-CNN
  • R-FCN

Along with the Python code, FAIR has also released performance baselines for over 70 pre-trained models. Once the model(s) is trained, it can be deployed on the cloud and even on mobile devices.

You can check all of this out on the Github library for Detectron here and the official Facebook launch page Google’s Cloud AutoML Vision.

Our take on this

Detectron’s release will help research communities around the world immeasurably. It’s open source so you can download the code behind this software and even use the plethora of pre-trained models the team has released. From augmented reality to various computer vision tasks, Detectron has a wide variety of uses in the research community.

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Facebook Launched Detectron – A Platform for Object Detection Research
Facebook Launched Detectron – A Platform for Object Detection Research

[…] It’s open source so you can download the code behind this software and even use the plethora of pre-trained models the team has released. From augmented reality to various computer vision tasks, Detectron has a wide variety of uses in the research community. Read more from analyticsvidhya.com… […]

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