A two stage lightweight and high performance license plate recognition in MTCNN and LPRNet

The implementation of ECCV 2018 paper "License Plate Detection and Recognition in Unconstrained Scenarios" in PyTorch

License_Plate_Detection_Pytorch

Automatic license plate detection and recognition.High performance frameworks tensorflow and pytorch,python .

OCR system for vehicle license plate detection and recognition using PyTorch, YOLOv5, and ONNX, with automated data processing and results exported to CSV.

Clone from https://github.com/xuexingyu24/License_Plate_Detection_Pytorch

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A License Plate Detection and Recognition model in Pytorch

the pytorch implementation of faster rcnn for license plate detection

convert Pytorch RetinaFace license plate detection model to TensorRT engine

YOLOv8-based vehicle detection and license plate recognition project using PyTorch. Detects cars, trucks, and license plates from static images or live video streams with GPU acceleration (WSL2 + CUDA). Includes automatic bounding boxes, counting, and OCR (EasyOCR) for reading vehicle license plates.

A deep learning-based system for real-time helmet detection in video streams. Utilizes YOLOv8 for object detection (motorcyclists, helmets) and PaddleOCR for license plate recognition of non-helmeted riders. Implemented in Python with PyTorch.

An end-to-end real-time Automatic Number Plate Recognition (ANPR) system that combines YOLOv8 for precise license plate detection and a CRNN (PyTorch) for accurate alphanumeric recognition. It efficiently processes live video feeds from a smartphone’s IP camera, enabling fast, reliable, and practical number plate identification.

A PyTorch-based real-time facial emotion recognition system using live camera input. Training and deployment of a CNN with deep learning. A foundational infrastructure for future applications like object detection, license plate recognition, and defense technologies

stn-lptnet

Clone from https://github.com/xuexingyu24/License_Plate_Detection_Pytorch

Automatic license plate detection using YOLO and Pytorch

Automatic License Plate Recognition (ALPR) using PyTorch – plate detection + OCR models, training pipeline and deployment.

In this project i have made license plate detection using pytorch and MobileNetv2 algorithm was used

License Plate Detection using YOLO11 is a deep learning project that leverages the YOLO11 model to detect car license plates from images. It uses PyTorch for model training and OpenCV for image preprocessing.

Learning experiments and projects, including core PyTorch practice, distillation & self-distillation models, EMNIST classification, OCR systems, and license plate detection workflows.

Object detection project using YOLOv8 trained on a custom dataset to detect cars and license plates. Built with Python, PyTorch, and Roboflow.

Real-time Helmet Detection using Faster R-CNN built with PyTorch, trained on custom labeled dataset for detecting helmets, license plates, and bikes.

leverage Python Tensorflow Object Detection to be able to detect license plates using Kaggle Data. Once those plates have been detected you'll then be able to apply OCR to extract the text from each and every plate using PyTorch and EachOCR.

This project implements a license plate detection system using a custom object detection pipeline with **Faster R-CNN** and a **MobileNet V2 backbone** with **Feature Pyramid Network (FPN)** in **PyTorch**. The training data is sourced from **Roboflow Universe**, and the model is trained to accurately detect license plates in images.

A deep learning-based vehicle license plate detection system using YOLOv9, trained on the PlateDetectionYolov8 dataset. Built with PyTorch, OpenCV, and Ultralytics, it achieves high accuracy (mAP@50 > 90%) for real-time detection.

"Vehicle Speed & Violation Detection using ML & LPR. Detects speeding vehicles, recognizes license plates & identifies traffic violations. Utilizes ML (TensorFlow, PyTorch), OpenCV & LPR to improve road safety & automate traffic monitoring."

Developed an Automatic Number Plate Recognition (ANPR) System using YOLOv8, PyTorch, and OpenCV, optimizing real-time license plate detection with custom-trained YOLO weights for improved accuracy and reduced latency, while automating image preprocessing and inference for seamless deployment.

An end-to-end Red Light Violation Detection System built with Python, OpenCV, and PyTorch. It uses YOLO-based vehicle and license plate detection, traffic light simulation, and line-crossing logic to detect violations, extract plate numbers via OCR, and generate annotated images, records, and processed output videos for traffic monitoring.

ParkBy is an AI-powered smart parking and traffic monitoring system that uses YOLOv8 for real-time vehicle detection and ALPR for license plate recognition. Developed in Python with OpenCV and PyTorch, it offers real-time monitoring, violation detection, and live parking availability through dashboards.