EasyPR is an open-source license plate recognition system designed to detect and recognize vehicle license plates from images using computer vision and machine learning techniques. The project focuses primarily on recognizing Chinese license plates but also demonstrates general approaches to automatic number plate recognition systems. Built on top of the OpenCV computer vision library, EasyPR provides algorithms for detecting license plate regions in images, segmenting characters, and recognizing the characters through machine learning models. The system is designed to work in unconstrained environments, meaning it can handle images with varying lighting conditions, perspectives, and backgrounds. Its architecture includes multiple stages such as plate localization, character segmentation, and character classification to achieve accurate recognition results.

Features

  • License plate detection and recognition using computer vision
  • Built on the OpenCV library for image processing
  • Character segmentation and classification pipeline
  • Support for recognizing Chinese license plate characters
  • High recognition accuracy under clear image conditions
  • Cross-platform source code suitable for custom integration

Project Samples

Project Activity

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Categories

Machine Learning

License

Apache License V2.0

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Additional Project Details

Programming Language

C++

Related Categories

C++ Machine Learning Software

Registered

2026-03-10