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Image Labeling

With Firebase ML's cloud image labeling APIs, you can recognize entities in an image without having to provide any additional contextual metadata.

Image labeling gives you insight into the content of images. When you use the API, you get a list of the entities that were recognized: people, things, places, activities, and so on. Each label found comes with a score that indicates the confidence the ML model has in its relevance. With this information, you can perform tasks such as automatic metadata generation and content moderation.

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If you're a Flutter developer, you might be interested in FlutterFire, which includes a plugin for Firebase's ML Vision APIs.

Key capabilities

High-accuracy image labeling

Firebase ML's image labeling API is powered by Google Cloud's industry-leading image understanding capability, which can classify images with 10,000+ labels in many categories. (See below.)

Try it yourself with the Cloud Vision API demo.

Knowledge Graph entity support

In addition the text description of each label that Firebase ML returns, it also returns the label's Google Knowledge Graph entity ID. This ID is a string that uniquely identifies the entity represented by the label, 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.

Limited free use

Free for first 1000 uses of this feature per month: see Pricing

Example labels

The image labeling API supports 10,000+ labels, including the following examples and many more:

CategoryExample labelsCategoryExample labels
Arts & entertainment Sculpture
Musical Instrument
Dance
Astronomical objects Comet
Galaxy
Star
Business & industrial Restaurant
Factory
Airline
Colors Red
Green
Blue
Design Floral
Pattern
Wood Stain
Drink Coffee
Tea
Milk
Events Meeting
Picnic
Vacation
Fictional characters Santa Claus
Superhero
Mythical creature
Food Casserole
Fruit
Potato chip
Home & garden Laundry basket
Dishwasher
Fountain
Activities Wedding
Dancing
Motorsport
Materials Ceramic
Textile
Fiber
Media Newsprint
Document
Sign
Modes of transport Aircraft
Motorcycle
Subway
Occupations Actor
Florist
Police
Organisms Plant
Animal
Fungus
Organizations Government
Club
College
Places Airport
Mountain
Tent
Technology Robot
Computer
Solar panel
Things Bicycle
Pipe
Doll

Example results

Photo: Clément Bucco-Lechat / Wikimedia Commons / CC BY-SA 3.0
Label Knowledge Graph entity ID Confidence
sport venue /m/0bmgjqz 0.9860726
player /m/02vzx9 0.9797604
stadium /m/019cfy 0.9635762
soccer specific stadium /m/0404y4 0.95806926
football player /m/0gl2ny2 0.9510419
sports /m/06ntj 0.9253524
soccer player /m/0pcq81q 0.9033665
arena /m/018lrm 0.8897188