Mapillary Data Licenses

License street-level imagery and map data for making better maps

Access fresh street-level imagery from all over the world and use automatically extracted data to keep your maps up to date.

Diverse and global
street-level imagery
People and organizations across the globe share their imagery in the world’s largest publicly available database. Powerful search tools help you find the time, place, and objects of interest to get a street-level view and do virtual inspections.
A street-level view of the whole world
Filtering imagery by date and contributor
Filtering imagery by objects detected in images
Key features
Key features
Global reach
Imagery from more than 190 countries combined into one navigable view.
Explore coverage
Visual search, filters, and geostatistics
Quickly find the images and data you need. Filter by geography, time, and objects contained in the images, with occurrence visualized on the map.
Frequent updates
Hundreds of thousands of images added daily all over the world, with the option to add your own or request fresh imagery from our contributors.
Learn more about capturing imagery
Automatically extracted map features
Scale and speed up map updates and asset inventories. Using computer vision, our technology recognizes objects in street-level imagery and places them on the map. Support for over 40 object classes and more than 1,500 different traffic signs.
Objects automatically detected in images
Objects located on the map as point features
Global traffic sign recognition
Key features
Key features
Automatic object detection
More than 60 object types automatically detected in imagery by award-winning machine learning algorithms for street scenes.
See which objects we detect
Point features on the map
Estimated coordinates of objects (triangulated from the images where the object has been detected). Currently supported for more than 40 object classes, including a further classification of traffic signs.
See which map features are available
Global traffic sign recognition
A detailed breakdown of traffic signs to aid inventories and map updates. Detectors for over 1,500 types of traffic signs in 100 countries.
See which traffic signs we recognize
Pixel-wise manual annotations in the Mapillary Vistas Dataset
Bounding box annotations in the Mapillary Traffic Sign Dataset
Machine-labeled images from the Mapillary database
Training data for machine learning
Train models that understand street scenes around the world to boost autonomous mobility and transport. Develop semantic segmentation models with the Mapillary Vistas Dataset and traffic sign recognition models with the Mapillary Traffic Sign Dataset, or pick a custom imagery set from our database.
Key features
Key features
Mapillary Vistas Dataset
A benchmark dataset of manually annotated training data for semantic segmentation of street scenes. 25,000 images pixel-accurately labeled into 152 object categories, 100 of those instance-specific.
Learn more about the Mapillary Vistas Dataset
Mapillary Traffic Sign Dataset
A benchmark dataset with bounding box annotations for detecting and classifying traffic signs around the world. 100,000 images with over 300 traffic sign classes, with manual and machine annotations.
Learn more about the Mapillary Traffic Sign Dataset
Custom sets of machine-labeled imagery
Select imagery from the whole Mapillary database based on the characteristics you need for your training data.
See which objects we detect
High diversity
Access half a billion images from more than 190 countries with a variety of weather, season, time of day, camera, and viewpoint conditions.
Explore the database
See how others use Mapillary
"This is great news for people passionate about mapping our planet. Now our community has even more resources at hand to help them make great maps."
Validate and update traffic data with fresh visuals
Supplement satellite imagery with views from the ground
Train robust perception models for autonomous vehicles

Start sharing images and accessing map data

Mapillary is an independent and neutral provider of street-level imagery and map data, untied to any particular mapping platform. We are committed to building a global service for everyone.
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