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Ultimatealpr SDK

Ultimatealpr SDK is a C++ deep-learning SDK for integrating automatic number-plate recognition into applications. Repository materials document Android Java samples, API guidance for C++ and other languages, and inference options for CPU, GPU, VPU and NPU hardware.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Ultimatealpr SDK — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when an application needs automatic plate recognition and the development team wants SDK-level integration with documented Android and C++ paths.

Who it is for

  • Developers adding plate recognition to camera-based applications.
  • Teams evaluating on-device recognition for Android, Linux, Windows, Raspberry Pi or NVIDIA Jetson targets.

Documented uses

  • Recognize license plates from still images or live camera video.
  • Build an Android application using the documented Java API and samples.
  • Compare parallel and sequential video-processing approaches using the provided Android examples.
  • Evaluate inference across listed hardware and software ecosystems.
Before you choose

Requirements & limits

  • The repository documents a Java API and Android examples, alongside C++ API guidance for other platforms.
  • Listed inference ecosystems include TensorFlow, TensorFlow Lite, TensorRT, OpenVX and OpenVINO.
  • The stated recognized plate character sets include Latin, Korean and Chinese.
  • The repository lists additional vehicle-analysis functions; consult feature documentation to determine which are relevant to a specific implementation.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Explore the Android sample applications

Use the repository’s Android sample applications as an introduction to its plate-recognition SDK.

Before you start

  • An Android development environment.
  • The ultimateALPR-SDK repository, which includes Android sample applications.

Steps

  1. Open the repository’s Android getting-started section.

  2. Choose one of the listed samples: Benchmark, VideoParallel, VideoSequential, or ImageSnap.

  3. Use VideoParallel as reference code for live-camera plate detection and recognition, or compare VideoParallel with VideoSequential to examine parallel and sequential modes.

Expected outcome

A selected Android sample provides a starting point for exploring SDK functionality; VideoParallel is identified as reference code for real-time recognition from a live camera stream.

Guide limitations

  • The repository content here identifies the samples and their purposes but does not provide the detailed build or launch procedure.
  • VideoSequential is described as slower than VideoParallel.
Documentation 1 ↗Documentation 2 ↗
Evidence and transparency

Sources & review

Official repository ↗Guide documentation ↗
Source record details
Source availability
Active
Sources checked
17 October 2026
Original website title
DoubangoTelecom/ultimateALPR-SDK · Official homepage title · retained in its source language
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