Dataset Analytics
Assess and improve the quality of your dataset.
Last updated
Was this helpful?
Assess and improve the quality of your dataset.
Last updated
Was this helpful?
Dataset Analytics shows a range of statistics about the dataset associated with a project. You can see the following pieces of information:
Number of images in your dataset;
Number of annotations;
Average image size;
Median image ratio;
Number of missing annotations;
Number of null annotations;
Image dimensions across your dataset;
Object count histogram, and;
A heatmap of annotation locations.
Using Dataset Analytics, you can derive a range of insights about your dataset. For example, if you have no null annotations, you may want to consider adding a few depending on the project on which you are working; if there are images with missing annotations, you can dig deeper to add the requisite annotations.
To see Dataset Analytics for a project, click "Analytics" in the left sidebar of a project:
The Dataset Analytics tab will then open:
On this page, you can see:
A breakdown of the number of classes in the images in your train, test, and valid datasets.
An overview of the sizes and aspect ratios of the images in your dataset.
A heatmap showing where most of your annotations are.
A histogram showing how many classes are annotated in each image in your dataset.