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Train recognition models for street scenes
Develop your algorithms with the most diverse data from all over the world, including different weather, season, time of day, camera, and viewpoint conditions.

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.
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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.
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Mapillary Street-level Sequences Dataset

A benchmark dataset for lifelong place recognition from image sequences. 1.6 million images from diverse geographies and scene characteristics, provided with GPS coordinates and sequence information.
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Mapillary Planet-Scale Depth Dataset

A diverse dataset of 750'000 street-level images with metric depth information for outdoor metric depth estimation.
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Start training the best
computer vision models

Get in touch with us to learn more about our datasets and how to get started.
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Autonomous Intelligent Driving uses Mapillary data to train robust perception models for autonomous vehicles.
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Toyota Research Institute accelerates deployment of machine learning algorithms with Mapillary data.
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Start accessing imagery and map data
Mapillary is the platform that makes street-level images and map data available to scale and automate mapping.
We’re committed to building a global service for everyone.