LgoBE / CarMakeandModelDetection / 1.2.0



This algorithm provides a solution to classify cars by their make, model, body style and model year from images. The capabilities provided by the algorithm:

  • Identifies multiple cars in one image
  • Recognizes over 3000 car models
  • Detection from multiple angles
  • Coverage of a great portion of Western brands and models, from 1990 (and older) to present
  • Provides the top 3 most accurate results

The algorithm is trained on cars sold on the European and US markets. We are updating it regularly with newly introduced car models.

Visit us at https://www.elaidata.com.

Example result



The algorithm takes an image URL as input. The image should be in JPEG or PNG format. Note that all images will be resized to 512x512 pixels. Images are downloaded with Algorithmia's SmartImageDownloader utility ( https://algorithmia.com/algorithms/util/SmartImageDownloader ).



The output of the algorithm is a JSON document, containing multiple prediction objects with a class, confidence and bounding box for each prediction.


Bounding box: coordinates (in pixels) of the box that contains one car.

Make: name of the car brand, e.g. BMW, Ford, Land Rover.

Model: name of the car model, e.g. X5, Mustang, Discovery

Body_style is one of these values: Convertible, Coupe, Hardtop, Sedan, Wagon, SUV, Cargo Van, Club Cab, Crew Cab, Double Cab, Extended Cab, King Cab, Mega Cab, Quad Cab, Regular Cab, SuperCab Fastback, Hatchback, Van, Wagon Van, Minivan, Passenger Van, MPV, Mini MPV, Buggy, Racing, Roadster, Truck

Model_Year: The model year, or the start-of-production year.

Confidence: a number between 0 and 1 indicating the confidence in the prediction, rounded to two decimal places.