Mapillary’s computer vision technology automatically detects objects depicted in images, such as buildings, cars, pedestrians, bicycle racks, and much more. This is based on a method called semantic segmentation—an algorithm is trained to detect and assign a category label to every pixel in the image.
Since each image has geocoordinates, it is possible to also visualize the object detections on the map. This will let you filter for images that contain specific kinds of objects. The map visualizations at this stage reflect positions of the images where certain objects are visible. This is not the same as map features, which is one step further—triangulating the location of an object that has been detected in several images, so we can determine the location of that object in the real world and place it on the map as a map feature.
Please note that to retrieve and use these automatically extracted object detections, you must query map data using the Mapillary API.
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