Exploring line features

Line features are a type of map data automatically extracted with Mapillary’s computer vision technology, representing line-shaped real-world objects such as sidewalks, guardrails, curbs, etc. (Learn more and see the full list of object types available as line features in the article about map features.)

Line features can be explored on the Mapillary web app. To turn on line features, click on the "Map data" icon at the top of the Mapillary web app and flip the switch for "Line features". You will see the map change to give you a better visualization of the features. You can use the same switch to return to the normal map view.

You will see some example object classes to help you start exploring line features. Click on e.g. curb, guardrail, or sidewalk to filter for these objects displayed as features on the map (one at a time). Alternatively, you can use the search box to search for whatever objects interest you.

As you type, you will see a list appear that helps you match your search to the available classes. To exit the list, press Esc on your keyboard. The currently applied filter appears above the search box and you can remove it by clicking on the cross in the top right corner.

You can close the label browsing window at any time by clicking the cross at its top right corner or the “Map data” button. Your applied searches will remain active and you can access the search box any time by just clicking on the “Map data” menu again.

As you apply object class filters, you might not see anything on the map at first if you are at a low zoom level (less than level 10). To start exploring, zoom into an area and you will see yellow lines appear on the map, representing the line features of your filtered classes.

You’ll notice the regular Mapillary sequence overlay in the background in a lighter grey color— when you click on any of the image markers around the line feature, you’ll also be able to see the detections of the respective object highlighted in the images (as a result of semantic segmentation).