---
title: "Car License Plate Detection Dataset"
description: "The license plate dataset contains vehicle images with annotated license plates, enabling accurate recognition of number plates across various traffic conditions and road environments"
url: "https://unidata.pro/datasets/car-license-plates-ocr-image/"
date_modified: "2026-02-03T13:00:14+03:00"
language: "en-US"
---
The license plate dataset contains vehicle images with annotated license plates, enabling accurate recognition of number plates across various traffic conditions and road environments

## Dataset Structure

### The Numbers Section

**Numbered list:**

- **Number:** 3 809 704 — **Text:** images
- **Number:** 93 — **Text:** Countries

### Tooltips Section

**Tooltip items:**

- **Name:** Computer Vision
- **Name:** Data annotation
- **Name:** Detection
- **Name:** Auto
- **Name:** Machine Learning
- **Name:** Security

### Dataset Information

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Description | Car license plate images with labeling for OCR tasks |
| Data types | Image |
| Tasks | Detection, Classification, OCR |
| Total number of files | 3 809 704 |
| Marking | OCR |
| Labeling | Model, details, plate text, tag, country |
| Countries | Russia, France, Poland, Germany, Ukraine, United Kingdom, Spain, Hungary, USA, Netherlands, Italy, Belgium, China, Serbia, Belarus, Lithuania, Turkey, Kazakhstan, Austria, Romania, Bulgaria, Switzerland, Slovakia, Vietnam, Latvia, Czech Republic, Croatia, Norway, Canada, Indonesia, Greece, Georgia, Finland, Estonia, Thailand, Uzbekistan, Israel, United Arab Emirates, Sweden, Moldova, Luxembourg, Slovenia, Ireland, Portugal, North Macedonia, Malta, Denmark, Azerbaijan, Kyrgyzstan, Armenia, Singapore, Monaco, Argentina, Iran, Andorra, Australia, Montenegro, Bosnia and Herzegovina, Brazil, Morocco, Mexico, Hong Kong, Cyprus, Malaysia, Bahrain, Liechtenstein, Albania, New Zealand, Tajikistan, Japan, Egypt, San Marino, Mongolia, Saudi Arabia, Iraq, Cambodia, Iceland, South Korea, Qatar, Åland Islands |

**Media Slider:**

- **Image in the slider:** ![](https://unidata.pro/wp-content/uploads/2024/06/plate-1.webp)
- **Image in the slider:** ![](https://unidata.pro/wp-content/uploads/2024/06/plate-2.webp)

**Link to the sample:** [Download sample](https://drive.google.com/drive/folders/1ThcqOqlq-_SzpsBQT196PzBUeuItv1oW?usp=sharing)

### LLM Languages

**Section Title:** Statistics

**List of Statistics:**

- **Filter by:** Continent Distribution — **GIF image:** Continent Distribution — **Table with data:**

| Continent | Quantity |
| --- | --- |
| Europe | 2,434,844 |
| Asia | 128,627 |
| North America | 84,629 |
| South America | 4,687 |
| Oceania | 5,265 |
| Africa | 2,596 |
- **Filter by:** Top Countries — **GIF image:** Top 20 Countries — **Table with data:**

| Country | Count |
| --- | --- |
| Russia | 1 299 630 |
| France | 222 912 |
| Poland | 220 474 |
| Germany | 200 062 |
| Ukraine | 189 947 |
| United Kingdom | 135 718 |
| Spain | 125 919 |
| Hungary | 107 272 |
| USA | 105 136 |
| Netherlands | 101 582 |
| Italy | 71 276 |
| Belgium | 62 183 |
| China | 46 890 |
| Serbia | 42 248 |
| Belarus | 41 409 |
| Lithuania | 40 073 |
| Turkey | 38 917 |
| Kazakhstan | 36 432 |
| Austria | 32 989 |
| Romania | 32 732 |
- **Filter by:** Top Tags — **GIF image:** Top 20 Tags — **Table with data:**

| Tag | Count |
| --- | --- |
| truck | 266 654 |
| transferred/re-issued plate | 226 645 |
| tractor unit | 148 792 |
| trailer | 106 685 |
| bus | 83 659 |
| cabriolet | 73 272 |
| oldtimer | 71 065 |
| new letter combination | 56 709 |
| motorcycle | 52 111 |
| taxicab | 43 570 |
| motorhome | 35 76 |
| non-standard plate | 26 572 |
| plate for brand or model of vehicle | 26 268 |
| abandoned vehicle | 22 309 |
| dump truck | 15 975 |
| vinyl wrapping | 15 728 |
| electric vehicle | 15 150 |
| police | 14 185 |
| damaged | 11 235 |
| tuning | 9 556 |

### Statistics - Charts

**Charts with Titles:** - **Shortcode:** [ays_chart id="66"] — **caption above the graph:** Continent Distribution

### Technical Specifications

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Image extensions | png |
| Extension of labeling file | csv |

**Source and data collection methodology:** Source and collection methodology: Data was collected by parsing videos from various sources

### Dataset Use Cases - Slider

**Industry Cards:**

- **Industry:** Transportation & Logistics — **Title:** Fleet Tracking and Toll Automation — **Text:** This car license plate dataset supports the development of AI-powered systems for automated fleet monitoring, toll collection, and delivery verification. By training models on annotated license plates in varied lighting, weather conditions, and traffic scenarios, logistics companies can ensure accurate license plate recognition across diverse road networks and urban areas.
- **Industry:** Smart City Infrastructure — **Title:** Traffic Management and Parking Automation — **Text:** Urban planners and technology providers use this license plate detection database to improve traffic flows, monitor traffic density, and automate parking access. The dataset enables integration with intelligent traffic systems, traffic signals, and parking control platforms, supporting better urban mobility and road safety in real-world conditions.
- **Industry:** Law Enforcement & Security — **Title:** Vehicle Identification and Access Control — **Text:** Police, customs, and private security agencies use this car plate detection dataset for number plate recognition, stolen vehicle recovery, and border security. Its precise bounding box and polygon annotations allow accurate vehicle identification even in challenging traffic patterns and weather conditions.
- **Industry:** Autonomous Vehicles & AI Research — **Title:** Real-Time Detection for Self-Driving Systems — **Text:** Autonomous driving developers rely on this license plate recognition database to train models for detecting and interpreting vehicle registrations in real-time traffic. By encompassing diverse road types, speed limits, and driving behaviors, the dataset ensures better performance in both simulated and real-world deployments.

### Fact

**FAQs Heading:** FAQs

**List of Questions:**

- **Question:** What is Car License Plate Detection Dataset used for? — **Answer:** The dataset is designed for license plate recognition, OCR tasks, and autonomous driving research. It supports detection, classification, and number plate recognition models, helping improve traffic management, smart city systems, and vehicle registration monitoring.
- **Question:** What types of annotations are provided? — **Answer:** Each image in the dataset contains OCR-based annotations, including plate text, vehicle model details, tags, and country information.
- **Question:** How was the data for this dataset collected? — **Answer:** The data was sourced from diverse real-world traffic flows, urban areas, and road conditions. Images were gathered across multiple countries and road types, ensuring broad coverage for traffic scenarios, vehicle registrations, and intelligent transportation research.
- **Question:** What should I consider before buying Car License Plate Detection Dataset? — **Answer:** Before purchasing, evaluate your project goals, such as character recognition, plate detection, or vehicle registration systems. Review the data diversity, country coverage, and annotation details, as these factors impact the performance of learning models, recognition technology, and real-time traffic applications.
- **Question:** Do Unidata datasets follow GDPR or other data privacy regulations? — **Answer:** Yes. Our datasets are developed in compliance with GDPR and related data privacy laws. Information comes only from lawful sources to ensure ethical handling.
- **Question:** How are Unidata datasets licensed? — **Answer:** Unidata datasets operate under a dual licensing framework: users may test free samples, but full dataset access is granted only via purchase.
- **Question:** How long does it take to receive the dataset? — **Answer:** After submitting your request, our team will reach out to review the details and complete the necessary paperwork. Once finalized and payment is received, the dataset will be provided within 3–10 days.
- **Question:** Is this a real-world dataset or synthetic data? — **Answer:** This is a real-world dataset. It contains over 3.8 million car license plate images collected by parsing videos from various sources.
- **Question:** Is this dataset suitable for training OCR models? — **Answer:** Yes. Every image includes OCR annotations containing the license plate text, making the dataset well suited for developing license plate OCR systems, text recognition models, and end-to-end ANPR pipelines.
- **Question:** Why is a multi-country license plate dataset important? — **Answer:** A dataset containing license plates from numerous countries helps AI models recognize different plate sizes, fonts, colors, and regional conventions. This leads to more accurate and scalable license plate recognition, ANPR, and OCR solutions deployed across international markets.

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