bookmark_borderbookmark
Stay organized with collections
Save and categorize content based on your preferences.
plat_iosplat_android
With ML Kit's landmark recognition API, you can recognize well-known
landmarks in an image.
When you pass an image to this API, you get the landmarks that were recognized
in it, along with each landmark's geographic coordinates and the region of the
image the landmark was found. You can use this information to automatically
generate image metadata, create individualized experiences for users based on
the content they share, and more.
Get the name and geographic coordinates of natural and constructed
landmarks, as well as the region of the image the landmark was found.
Try the
Cloud
Vision API demo to see what landmarks can be found in an image you
provide.
Get Google Knowledge Graph entity IDs
A Knowledge Graph entity ID is a string that uniquely identifies the
landmark that was recognized, and is the same ID used by the
Knowledge Graph
Search API. You can use this string to identify an entity across
languages, and independently of the formatting of the text description.
Low-volume use at no cost
Free for first 1000 uses of this feature per month: see
Pricing
Example Results
Photo: Arcalino / Wikimedia Commons / CC BY-SA 3.0
Result
Description
Brugge
Geographic Coordinates
51.207367, 3.226933
Knowledge Graph entity ID
/m/0drjd2
Bounding Polygon
(20, 342), (651, 342), (651, 798), (20, 798)
Confidence Score
0.77150935
Was this helpful?
Recommended for you
About these recommendations
These recommendations help you find the content you are looking for. They may be based on the page you’re currently viewing and your account’s saved web and app activity.
ML Kit for Firebase provided ready-to-use ML solutions for app developers. New apps should use the standalone ML Kit library for on-device ML and Firebase ML for cloud-based ML.
ML Kit for Firebase provided ready-to-use ML solutions for app developers. New apps should use the standalone ML Kit library for on-device ML and Firebase ML for cloud-based ML.
ML Kit for Firebase provided ready-to-use ML solutions for app developers. New apps should use the standalone ML Kit library for on-device ML and Firebase ML for cloud-based ML.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-02-20 UTC."],[],[]]