zhubenfu/License-Plate-Detect-Recognition-via-Deep-Neural-Networks-accuracy-up-to-99.9

Health v2 · maintenance only

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Adoption not part of the score

1384 stars · 321 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A C++ application that detects and recognizes Chinese license plates in real time using deep neural networks, claiming up to 99.8% accuracy at roughly 100 ms per plate. It bundles multiple detection approaches (haar+cascade, MTCNN, image processing) and recognition methods (CNN character classification, LSTM+CTC).

Use cases

• recognize Chinese license plates from camera footage
• detect vehicle plates in real time video
• build an ANPR/LPR system for parking or tolling
• train a plate recognition model with real plate datasets
• compare haar cascade vs MTCNN vs YOLO for plate detection
• perform OCR on segmented license plate characters

When to choose

• you need to detect and read Chinese license plates specifically
• you want a ready-made C++ pipeline with multiple detection/recognition backends
• you need a Windows/CUDA build for real-time plate recognition
• you want a large real-world Chinese plate dataset for training

When to avoid

• you need plates from regions other than China
• you require a maintained project with a clear license for commercial use (no license is provided)
• you need cross-platform or Linux-first deployment out of the box
• you want a pip-installable or well-documented library rather than a Visual Studio project

Facets

application · maturity maintenance

computer-vision ocr image-processing machine-learning deep-learning computer-vision image-processing artificial-intelligence developer-tools windows cpp license-plate-recognition alpr chinese-license-plates mtcnn haar-cascade yolo lstm-ctc cnn opencv real-time gpu

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