Yolo license plate detection github This repository provides a comprehensive toolkit for training a License Plate Detection model using YOLOv8 - Arijit1080/Licence-Plate-Detection-using-YOLO-V8 Jan 8, 2025 · About Recognition of license plate numbers, in any format, by automatic detection with Yolov8, pipeline of filters and paddleocr as OCR rtsp surveillance tensorflow ip-camera nvr cuda motion-detection yolo face-recognition object-detection hardware-acceleration hacktoberfest darknet coral network-video-capture license-plate-recognition google-coral edgetpu network-video-recorder viseron Updated 6 hours ago Python This project focuses on detecting license plates from images and video feeds using the YOLOv8 (You Only Look Once) object detection model. Dec 14, 2024 · YOLO-based Object Detection: Uses YOLO models for detecting license plates in real-time. Neural Network in YOLO uses weights trained by the user through annotated training data by using bounding boxes. Licence-Plate-Detection-and-Recognition-using-YOLO-V8-EasyOCR by Chulindra Rai This project is for recognizing motorbike license plate in Vietnam. A License-Plate detecttion application based on YOLO - alitourani/yolo-license-plate-detection Jan 10, 2025 · Accurate Detection: Uses YOLOv8 for license plate detection in various scenarios (e. Oct 20, 2024 · License plate detection using YOLOv11. or you can read the state of the art of object detection State-of-the-art of Object Detection This project covers a License Plate Detection and Recognition Tool built upon YOLOv4/YOLOv7 for license plate detection and PaddleOCR for license plate character recognition. License plate recognition. The model was trained with Yolov8 using this dataset. Photo by mali maeder from Pexels applied to a custom-built YOLO license plate detection model Why do you need YOLO? What’s wrong Japanese license plate recognition project implemented with PyTorch, YOLOv8 and OpenCV. The goal is to accurately detect and localize license plates in images for applications like traffic monitoring and vehicle identification. Detect license plates Nov 5, 2021 · Github Repository In this repository you can find a custom function to feed Tesseract OCR the bounding box regions of license plates found by my custom YOLOv4 model in order to read and extract the license plate numbers. Hence YOLO takes an image as input puts it through a Neural Network and gives the output in the image through Automatic Number Plate Recognition (ANPR) is the process of reading the characters on the plate with various optical character recognition (OCR) methods by separating the plate region on the vehicle image obtained from automatic plate recognition. The Persian License Plate Recognition (PLPR) system is a state-of-the-art solution designed for detecting and recognizing Persian license plates in images and video streams. GPU=0 # Change to 1 if using GPU License Plate Recognition 🚗 License Plate Detection and Extraction with YoloV8 and EasyOCR Using both the COCO Model to detect the vehicles and the License Plate Model to recognize the plate, and then with EasyOCR to extract the info from the cropped plate image. This project implements an Automatic Number Plate Recognition (ANPR) system using YOLO for object detection and Tesseract for Optical Character Recognition (OCR). Contribute to HimanshuKamdi/YoloV5_License_Plate_Detection development by creating an account on GitHub. Contribute to tungedng2710/AI-Traffic-Analysis development by creating an account on GitHub. Github Repository YOLOv8 License Plate Detection Pre-Trained YOLOv8 Retraining YOLOv8 YOLOv8-License-Plate-Insights This repository demonstrates license plate recognition using the YOLOv8 object detection algorithm, showcasing the versatility of the YOLO architecture in real-world scenarios such as vehicle identification, traffic monitoring, and geospatial analysis. Contribute to computervisioneng/automatic-number-plate-recognition-python-yolov8 development by creating an account on GitHub. Approach To predict the license plate number, the following things need to be done: The license plate needs to be detected from the overall image. Implementing YOLO for Automatic Number Plate Recognition (ANPR) involves training a YOLO model on a custom dataset of license plate images and then integrating it with an OCR (Optical Character Recognition) system to read the characters from the detected license plate regions steps involved: Dataset Collection: Collect a dataset of annotated license plate images. But I replaced the DeepSORT Dependency with the YOLOv8 included Track function. Object detection is manualy segmenting plate, and recognize each candidate number or alphabet using knn method. The dataset should contain YOLO (You Only Look Once) is a state-of-the-art, real-time object detection system. Additionally, it utilizes a specialized model Nov 10, 2024 · 🚀 Overview This project implements an advanced License Plate Detection and Recognition System using state-of-the-art computer vision techniques. I'll write report later 😅 - Trung-Rei/License-plate-recognition-YOLO Using YOLO object detection for Detecting plates and a combination of CNN and LSTM with CTC Loss for OCR. About AI-powered license plate detection software with React. Contribute to debi-ml/yolo-license-plate-detection development by creating an account on GitHub. Jan 6, 2025 · Security & Surveillance Conclusion This project demonstrates the power of AI in automated license plate recognition by combining YOLO for object detection and Google Gemini API for OCR. This repository contains code and instructions for performing object detection using YOLOv5 inference with ONNX Runtime. Cropping the car from the image. Contribute to Arijit1080/Licence-Plate-Detection-and-Recognition-using-YOLO-V8-EasyOCR development by creating an account on GitHub. Today you’ll enter the world of modern computer vision with a hands-on example. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects. Jan 25, 2025 · This project is a License Plate Detection and Text Extraction application built using YOLOv8 and Streamlit. Unlike traditional object detection systems that repurpose classifiers or localizers to perform detection, YOLO frames object detection as a single regression problem, straight from image pixels to bounding box coordinates and class probabilities. The images were annotated with bounding boxes around the license plates, indicating their precise location in the image. This is the Automatic license plate detection and recognition system using Yolov5. Object Detection Example: This repository includes a practical example of vehicle license plate recognition, where the model is trained and validated using YOLOv11 for object detection. OCR is then applied to extract the text from the plates. The goal is to accurately identify and localize license plates in real-time, making it useful for applications like automated toll collection, parking management Automatic License Plate Recognition (ALPR) or Automatic Number Plate Recognition (ANPR) software that works with any camera. Key Features: Pre-Trained YOLOv11 Model: Use the pre-trained model for object detection, image segmentation, image classification, and pose estimation. Scalable Workflow: Handles single images, video frames, or large datasets efficiently. Includes . GitHub is where people build software. , moving vehicles, different lighting conditions). This project aims to detect license plates in images using the YOLOv9 object detection model. I noticed that detecting the car first and then detcting the license plate was more accurate than detecting the license plate from the original bigger image. Nov 22, 2020 · Computer vision is everywhere – from facial recognition, manufacturing, agriculture, to self-driving vehicles. The model has really low precision in detecting the license plates. A powerful and efficient license plate detection system that utilizes YOLOv8 for vehicle detection, a custom YOLO model for license plate detection, and PaddleOCR for optical character recognition. You will learn how to detect license plates with the YOLO algorithm. A Yolov8 pre-trained model (YOLOv8n) was used to detect vehicles. Run the add_missing_data. onnx model files, sample output images, and a comprehensive README for usage via Pyth Vietnamese license plate recognition. License-Plate-Detection-and-Recognition-using-YOLOv5 License Plate Detection and Recognition using YOLO is a computer vision project that detects vehicle number plates in images using the YOLO algorithm. The model is available here. It can efficiently and accurately detect and recognize vehicle license plates in real-time. The system processes video frames in real-time, detects number plates, and performs OCR to extract the text from the detected plates. The dataset comprises images of cars with annotated license plate bounding boxes. Notifications You must be signed in to change notification settings Fork 8 An accurate object detection model was created to carry out Automatic Number Plate Recognition using YOLOv5 and transfer learning along with Pytorch. The system not only detects license plates but also extracts and recognizes the text content, supporting both Arabic and Latin characters. The dataset comprises a total of 724 images, each of which includes one or more car license plates. EasyOCR for Text Recognition: Extracts alphanumeric characters from detected license plates. Leveraging advanced deep learning models and a user-friendly interface, it ensures reliable performance across different This repository contains an enhanced method to detect vehicle license plates using YOLO v3 with integrated OCR (Optical Character Recognition) capabilities. It combines the power of YOLOv5 for object detection and PyTesseract for Optical Character Recognition (OCR) to accurately identify and read license plates from images of vehicles. Thorough preprocessing is done on the license plate in order to correctly extract the license plate number from the image. The YOLO model processes video frames from a CCTV feed to detect license plates, extracts text from the detected plates using Optical Character Recognition (OCR), and annotates the video with the recognized license numbers. Includes detecting LP and recognizing characters on it. Data Augmentation: Includes transformations like Train the YOLOv8 model on the prepared dataset for license plate and car detection. pt and . Model Selection: Evaluate multiple trained models and select the best-performing one based on detection accuracy and OCR performance. Licence-Plate-Recognition-with-YOLO-V8-and-Easy-OCR Project Overview This project integrates YOLOv8 for license plate detection and EasyOCR for optical character recognition (OCR) to read the detected license plate numbers. It includes a variety of license plate types and environmental Detect and recognize vehicle license plates using YOLOv8 for precise detection and CRNN for accurate character recognition. Aug 1, 2025 · Car Plate Recognition using YOLO for automatic license plate detection, cropping, and visualization in images with Python, OpenCV, and the Ultralytics YOLO library. py file for interpolation of values to match up for the missing YOLOv11-License-Plate Detection This is a fine-tuned version of YOLOv11 (n, s, m, l, x) specialized for License Plate Detection, using a public dataset from Roboflow Universe: License Plate Recognition Dataset (10,125 images) 🚀 Use Cases Smart Parking Systems Tollgate / Access Control Automation Traffic Surveillance & Enforcement ALPR with OCR Integration 🏋️ Training Details Base Model Sep 15, 2023 · YOLOv8 License Plate Detection Using the YOLOv8 Object Tracker and EasyOCR to record License Plates. Aug 7, 2025 · A Chinese license plate training project using CCPD dataset with YOLO that supports detection and plate number recognition (for self-learning) - Leo204-LKY/plate-detection-recognition About Automatic Number Plate Detection YOLOv8 opencv pytorch yolo anpr licence license-plate-recognition yolov8 yolov8-deepsort Readme Contributing Activity This dataset contains images of car license plates captured in various locations and under different lighting conditions. Automatic number plate recognition is a technology designed to identify and extract vehicle number plate information from images or videos. A licensed plate detector was used to detect license plates. A deep learning-based computer v License Plate Detection using YOLOv3 YOLO abbreviates to You Only Look Once depicting its ability to detect objects and entities by using CNN (Convolutional Neural Network). This repository provides a comprehensive toolkit for training a License Plate Detection model using YOLOv8 - Arijit1080/Licence-Plate-Detection-using-YOLO-V8 This repository, License Plate Detection, is a project for detecting and extracting information from license plates using YOLO (You Only Look Once) for object detection and easyOCR for Optical Character Recognition (OCR). Contribute to bhaskrr/number-plate-recognition-using-yolov11 development by creating an account on GitHub. OCR Integration: Employs EasyOCR to extract and recognize text from detected license plates. This can be done using object detection methods like finding contours, using You-Only-Look-Once (YOLO), etc. Contribute to FlyIsPowerful/Yolo5 development by creating an account on GitHub. In order to solve this problem, I will use YOLOv5 which is most powerful object detection model. js frontend for uploading pictures of license plates, fine-tuning YOLO's real-time object detection model and leveraging open source OCR software. As you can see, first step is detect the plate with May 2, 2025 · YOLOv11n → YOLOv11x models fine-tuned for license plate detection using the Roboflow dataset. Section 5 - License Plate Detection with YOLOv5 Notebook: 05_YOLO. The dataset used is Keremberke's License Plate Object Detection , and the model is trained using the Ultralytics YOLOv8 framework . Communication between client and server powered by WebSockets. About YOLO v5 algorithm for Vehicle Number Plate Detection on custom dataset A licensed plate detector was used to detect license plates. Both plate detection and character detection and recognition using Yolov5. The accuracy of bounding boxes and the frame rate was found to be good. The combination allows both the detection of plates in images or videos and the extraction of plate numbers in real-time. ALPR with YOLOv4 is an advanced Automatic License Plate Recognition (ALPR) system that leverages the powerful YOLOv4 (You Only Look Once) one-stage object detection framework. I used EnglishLP dataset for experiment but you can try with any other dataset also Approach To predict the license plate number, the following things need to be done: The license plate needs to be detected from the overall image. The dataset used for training is available on Roboflow here. The application detects license plates in images and videos, draws bounding boxes around them, and extracts the text from the detected license plates using Tesseract OCR. The model was trained with Yolov8 using this dataset and following this step by step tutorial on how to train an object detector with Yolov8 on your custom data. This guide is based on the DeepSORT & EasyOCR Repository by @computervisioneng. g. This project develops a real-time vehicle detection and license plate recognition system using advanced deep learning techniques. By leveraging the powerful capabilities of Ultralytics YOLO11 for object detection and OpenAI gpt-4o-mini for text recognition, ANPR becomes an efficient solution for automating vehicle identification tasks. By integrating the YOLO (You Only Look Once) model for object detection and the SORT (Simple Online and Realtime Tracking) algorithm for tracking, the system efficiently identifies and tracks vehicles in video footage. For research purpose only. Here for the detail : Video Explanation KNN Note : It is recommended to use a newer method like yolo or ssd. License Plate Text Extraction: Implement Optical Character Recognition (OCR) to extract text from detected license plates. This project uses the YOLOv8 object detection model to detect license plates. - eepj/lprs-jp. It allows the processing of images and videos to accurately detect license plates and extract their characters, enabling a This project focuses on automatic license plate detection using YOLOv8 (You Only Look Once), leveraging PyTorch, Python, and computer vision techniques. This project leverages annotated datasets to train models for efficient vehicle image analysis and license plate identification. Automated license plate detection and recognition (ANPR) is implemented using YOLO and PaddleOCR. Hybrid Dataset: Combines three different datasets containing a variety of challenging scenarios such as occlusions, lighting inconsistencies, and pose variations. ipynb The biggest problem of this project is the accuracy of the model. Detecting License Plate using Yolo V5. njzhpiq noclnnlb frzazatm eyezidub bzfpum czoy ptns uonhf hvidt clakfz cblxxu rmpc dfql qhfll tkpn