DTK WNR SDK

Introduction

DTK WNR SDK (Wagon Number Recognition) is a software development kit designed for software developers who want to integrate wagon number recognition into their software products. Wagon Number Recognition engine detects and recognizes 1520 mm gauge railways eight-digit wagon numbers (used in the former-USSR and now the CIS and Russia) and UIC-12 European railways wagon numbers from from various video sources (IP cameras, video files, video capture devices) and still images (JPEG, PNG, BMP). The fast and stable WNR Engine is built on the latest technologies and algorithms, provides highly accurate plate recognition from the real-time video at a resolution up to 1920x1080 (Full HD).

Programming Interfaces

The base programming interface for WNR Engine is C++ native library with header file (<DTKWNR.h>) where defined all available API functions.

However, WNR engine can be used with many other programming languages (like .NET, Java, etc.) and development environments.

The SDK package have samples included for various programming languages, such as C++, C#, Java.

The samples source codes you can find under the following directories:

/samples/cpp
/samples/csharp
/samples/java
etc.

WNR Engine Libraries

The WNR Engine is a library which is built for different architectures for Windows and Linux operating systems.

The SDK package include the following versions of WNR Engine:

/lib/windows/x86/DTKWNR.dll (Windows 32-bit)
/lib/windows/x64/DTKWNR.dll (Windows 64-bit)
/lib/linux/armhf/libDTKWNR.so (Linux ARM hard-float)
/lib/linux/arm64/libDTKWNR.so (Linux ARM64 / AArch64)
/lib/linux/x86_64/libDTKWNR.so (Linux 64-bit)

The DTKWNR library require the following dependency libraries:

for Windows:

DTKVID.dll
DTKAVCodec.dll
DTKAVFormat.dll
DTKAVUtil.dll
DTKSWScale.dll
DTKSWResample.dll

for Linux:

libDTKVID.so
libavcodec.so
libavformat.so
libavutil.so
libswscale.so
libswresample.so

Those libraries are located under folders where appropriate version of DTKWNR library is located.

CUDA Libraries

CUDA libraries (DTKWNR_Cuda.dll and libDTKWNR_Cuda.so) require the NVIDIA TensorRT and CUDA runtime libraries.

TensorRT-10.14.1
CUDA 12.6

You can download these libraries from the official NVIDIA website:

TensorRT 10.14.1

https://developer.nvidia.com/tensorrt/download/10x

CUDA 12.6

https://developer.nvidia.com/cuda-12-6-0-download-archive

For the Windows (64 bit) you can download a minimal set of required libraries from the DTK Software website using the link below.

https://www.dtksoft.com/download/windows-x64-trt10.14-cuda12.6.7z

Supported NVIDIA GPU Compute Capability: 7.5 and higher.

The list of supported NVIDIA GPUs you can find using the following link.

https://developer.nvidia.com/cuda/gpus

NOTE: Before using the CUDA library, you need to build the TensorRT engines on your computer. The built engines will be cached on your computer for future use. For more information, see the CUDA Functions section of the documentation.