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Germany License Plate Detection Dataset

The dataset contains annotated license plates from real-world traffic in Germany, providing high-quality images for license plate recognition, license plate detection, and OCR tasks, supporting autonomous vehicles, traffic management, and smart city applications

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  • images
    177 827
  • Auto
  • Computer Vision
  • Machine Learning
  • Detection
  • Data annotation
  • Security
  • images
    177 827

Dataset Info

Characteristic Data
Description License plate images with labeling for OCR tasks
Tasks Detection, Classification, OCR
Total number of files 177 827
Marking OCR
Labeling Model, details, plane text, tag, country, number
Download sample

Technical
Characteristics

Characteristic Data
Image extensions png
Extension of labeling file csv
Source and collection methodology: Data was collected by parsing videos from various sources

Dataset Use Cases

  • Transportation & Tolling

    Automating Billing and Vehicle Tracking

    Germany License Plate Detection Dataset is built for license plate recognition in tolling and logistics operations. Since the datasets contain annotated license plates under different road conditions and traffic flows, it ensures reliable billing, accurate vehicle registrations, and efficient monitoring of fleets across national highways and transportation systems.



  • Smart City & Traffic Management

    Enhancing Urban Mobility and Traffic Control

    City planners rely on license plate detection datasets to optimize traffic lights, improve traffic management, and monitor traffic density in busy urban areas. With real-world data covering traffic patterns and road networks, municipalities reduce traffic congestion, strengthen road safety, and support sustainable urban mobility projects.



  • Law Enforcement & Security

    Vehicle Identification and Road Safety Enforcement

    This car plate dataset supports police forces in tracking number plates, enforcing speed limits, and identifying stolen vehicles. With annotated license plates collected across various traffic scenarios and weather conditions, it enhances recognition systems for surveillance, roadside checks, and traffic control throughout Germany’s road segments and public transport hubs.



  • Automotive & AI Research

    Training Recognition Models for Autonomous Driving

    Car license plate datasets are a valuable resource for developing learning models for autonomous vehicles and intelligent traffic applications. Benchmark datasets that cover different road types, driving behaviors, and traffic volumes provide the high-quality real-world data needed to improve plate recognition systems for autonomous driving.



FAQs

How large is Germany License Plate Detection Dataset?
The dataset consists of 177,827 images, making it one of the larger benchmark datasets available for license plate recognition and detection tasks. Its scale allows for training deep learning models with high accuracy.
What file formats are included in the dataset?
The images are provided in PNG format, while annotations are delivered in CSV format. This structure ensures easy integration into machine learning workflows and OCR pipelines.
Does the dataset include different traffic and weather conditions?
Yes, the dataset encompasses a wide range of traffic conditions, including highways, city roads, and intersections. It also includes variations in lighting and weather, making it suitable for training robust recognition models.
Can this dataset be used as a benchmark for license plate recognition models?
Yes, due to its large scale and detailed annotations, this dataset is frequently used as a benchmark for OCR and detection algorithms. Researchers and developers use it to measure performance and improve recognition accuracy.
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