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4LPR - License Plate Recognition on Windows Pc

Developed By: cefaci

License: Free

Rating: 5,0/5 - 1 votes

Last Updated: April 21, 2024

Download on Windows PC

Compatible with Windows 10/11 PC & Laptop

App Details

Version 1.3.13
Size 26 MB
Release Date November 20, 20
Category Libraries & Demo Apps

App Permissions:
Required to be able to access the camera device. [see more (1)]

What's New:
Pixel 5 tested! [see more]

Description from Developer:
Just a DEMO to play around. Won't work on every mobile. This version has lesser resolution etc. for speed. For the encoder model NN API delegate is deactivated for all devices... [read more]

App preview ([see all 3 screenshots]  /  [view video])

App preview

About this app

On this page you can download 4LPR - License Plate Recognition and install on Windows PC. 4LPR - License Plate Recognition is free Libraries & Demo app, developed by cefaci. Latest version of 4LPR - License Plate Recognition is 1.3.13, was released on 2020-11-20 (updated on 2024-04-21). Estimated number of the downloads is more than 10. Overall rating of 4LPR - License Plate Recognition is 5,0. Generally most of the top apps on Android Store have rating of 4+. This app had been rated by 1 users, 1 users had rated it 5*, 1 users had rated it 1*.

How to install 4LPR - License Plate Recognition on Windows?

Instruction on how to install 4LPR - License Plate Recognition on Windows 10 Windows 11 PC & Laptop

In this post, I am going to show you how to install 4LPR - License Plate Recognition on Windows PC by using Android App Player such as BlueStacks, LDPlayer, Nox, KOPlayer, ...

Before you start, you will need to download the APK/XAPK installer file, you can find download button on top of this page. Save it to easy-to-find location.

[Note] You can also download older versions of this app on bottom of this page.

Below you will find a detailed step-by-step guide, but I want to give you a fast overview of how it works. All you need is an emulator that will emulate an Android device on your Windows PC and then you can install applications and use it - you see you're playing it on Android, but this runs not on a smartphone or tablet, it runs on a PC.

If this doesn't work on your PC, or you cannot install, comment here and we will help you!

Step By Step Guide To Install 4LPR - License Plate Recognition using BlueStacks

  1. Download and Install BlueStacks at: https://www.bluestacks.com. The installation procedure is quite simple. After successful installation, open the Bluestacks emulator. It may take some time to load the Bluestacks app initially. Once it is opened, you should be able to see the Home screen of Bluestacks.
  2. Open the APK/XAPK file: Double-click the APK/XAPK file to launch BlueStacks and install the application. If your APK/XAPK file doesn't automatically open BlueStacks, right-click on it and select Open with... Browse to the BlueStacks. You can also drag-and-drop the APK/XAPK file onto the BlueStacks home screen
  3. Once installed, click "4LPR - License Plate Recognition" icon on the home screen to start using, it'll work like a charm :D

[Note 1] For better performance and compatibility, choose BlueStacks 5 Nougat 64-bit read more

[Note 2] about Bluetooth: At the moment, support for Bluetooth is not available on BlueStacks. Hence, apps that require control of Bluetooth may not work on BlueStacks.

How to install 4LPR - License Plate Recognition on Windows PC using NoxPlayer

  1. Download & Install NoxPlayer at: https://www.bignox.com. The installation is easy to carry out.
  2. Drag the APK/XAPK file to the NoxPlayer interface and drop it to install
  3. The installation process will take place quickly. After successful installation, you can find "4LPR - License Plate Recognition" on the home screen of NoxPlayer, just click to open it.

Discussion

(*) is required

Download older versions

Other versions available: 1.3.13.

Download 4LPR - License Plate Recognition 1.3.13 on Windows PC – 26 MB

Just a DEMO to play around. Won't work on every mobile. This version has lesser resolution etc. for speed. For the encoder model NN API delegate is deactivated for all devices except Google, as errors and not working. Both models optimized for speed and size.

Features
- No internet used
- 1-liner
- Image Recognition with TensorFlow 2.x based on LPRNet
- TensorFlow Object Detection API with TensorFlow 2.x

DEMO Features
- GDPR compliant
- No text selection or copy
- No pictures are saved or uploaded
- No internet is used or any data is resolved
- No logging
- Process image size: 1024x768
- Detection image size: 640x640
- Maximum 8 license plates shown at once
- NN API delegate is deactivated because of issues on Samsung/Huawei devices, maybe will affect performance.
- Most country patterns will fail or show wrong results, I just fixed some EU country patterns
- Both models minimal optimized for speed and size
- Allowed the just image recognition mode in the DEMO (slide the switch to left)

Tested
Please bare with me and keep in mind, it won't work on every mobile, it is a specific DEMO, and I haven't checked all specific hardware vendor differences... It is as well not battery optimized, as I am using minimum 4 threads, it will surely drain your battery, once you start processing the images.

Versions
Only Android versions starting from 8.1 to 11 were tested.

Hardware
- Google Pixel 5 (Android 11) - deactivated NN API delegate for the encoder
- Google Pixel 2 XL (Android 10/11)
- Google Nexus 6p (Android 8.1)
- Samsung Galaxy S8/S9/S10 - deactivated NN API delegate for the encoder
- Unspecific Huawei - deactivated NN API delegate for the encoder

Links and sources
- My "quick" journey creating license plate recognition on Android with TensorFlow 2
On mobile HTML-links are not shown:
https://medium.com/swlh/my-quick-journey-creating-license-plate-recognition-on-android-with-tensorflow-2-51e89387fac4
- LPRNet: License Plate Recognition via Deep Neural Networks (Sergey Zherzdev, Alexey Gruzdev)
- Photo credits by Roman Kraft
- TensorFlow* Object Detection API
Pixel 5 tested!
Required to be able to access the camera device.