Vehicle Brand Recognition

The vehicle brand recognition neural network is an open-source model that can be freely integrated into any software that needs vehicle recognition features. It uses MobileNetV3 architecture which is optimized for fast inference. The supported vehicle brands are over 400. The web demo is available at: car make recognition web demo.

There are lots of industries that could benefit from our car recognition module, including security, marketing and law enforcement. Some sample use cases are:

  • Intelligent Video Surveillance
  • Smart Billboards
  • Traffic Analytics
  • Tagging of Video and Images
  • License Plate Verification
Car make recognition

Source code

Vehicle brand and color recognition C++ example: https://github.com/spectrico/vehicle-recognition-yolov4-cpp

Vehicle Make Recognition using YOLOv4 Object Detector: https://github.com/spectrico/vehicle-brand-recognition-yolov4-python

Vehicle Recognition API: https://github.com/spectrico/vehicle-recognition-api-yolov4-python

Car color recognition example with YOLOv4 object detector: https://github.com/spectrico/car-color-classifier-yolo4-python

Car Make and Model classification example with YOLOv3 object detector C++: https://github.com/spectrico/car-make-model-classifier-yolo3-cpp

Car Make and Model classification example with YOLOv3 object detector Python: https://github.com/spectrico/car-make-model-classifier-yolo3-python

Business Applications

Intelligent Video Analytics

Intelligent Video Analytics

Public safety and security organizations can include advanced search and car analytics functionalities into their software to find or redact relevant information in video records.

Traffic Analytics

Traffic Analytics

Cities are getting smarter and by using Big Data supplied by the traffic cameras, the transportation systems can be managed more efficiently.

Digital Asset Management

Digital Asset Management

Organizing, storing, and retrieving multimedia content like photos and videos. Building searchable car image databases for video and image archives.