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Dataset Analytics provides a service for generating analytics so users can learn additional insights about their datasets. Today there are three types of dataset analytics supported: Mean Brightness, Object Metrics and Properties. In this tutorial we will describe how to generate these analytics and review the output from each type of analytics.

Generating Dataset Analytics

We start by navigating to the Dataset Library page in the workspace that contains the dataset. Select the dataset then click the + icon next to Analytics in that dataset.

Dataset Analytics

Next, we just need to choose a type of analytics we’d like to run on the dataset. Click Create to create the new analytics job.

Create Analytics dialog

A new analytics job is started, it will show the time dial symbol while the job is still running.

Analytics job running

As a reminder, all dataset services share the same symbols for job status:

No symbol means that the service job is complete and ready to use.

The sand dial symbol means that the job is running. It will remain this way until the job has either completed or failed.

The error symbol means that the job has an issue. You can click on the symbol to fetch a log of the service to help determine what caused the issue.

Once complete, the symbol underneath Status will disappear and we will be able to download or go-to the Analytics. By clicking on the go-to symbol, it navigates us to the Analyses library with that analytics job selected.

Analytics job in Analyses

The same process can be done to generate the other types of analytics. Below we’ll dig into what each of these types of analytics provides us.

Mean Brightness

Mean Brightness generates a plot of the “brightness” density which can be helpful in comparing one or more datasets.

Mean Brightness output

Object Metrics

Object Metrics generates some data on the types of objects in our imagery and two plots that indicate the size of bounding boxes and aspect ratio density of those bounding boxes.

Object Metrics output


The properties analytics type generates metrics on image counts, mean size and modes. It also provides helpful metrics on mean objects per image and annotation counts.

Properties output

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