Another blog post reminder, this time related on prerequisites to install dlib. And before start, a dlib description:
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib’s open source licensing allows you to use it in any application, free of charge.dlib.net
Dlib is a key piece in computer vision processes, so every time I deploy a new Windows 10 instance, I need to install DLib and here are some prerequisites or, as I like to call them, lessons learned on the hard way.
Visual Studio for C++
One of the key requisites is [Visual Studio for C++]. In my default VS installation, I don’t install C++, here is my excuse to install this again.
Install CMake is an easy one, and somehow, I always forget to do this. More information in references section, and if you don’t know what’s CMake:
CMake is a cross-platform free and open-source software tool for managing the build process of software using a compiler-independent method. It supports directory hierarchies and applications that depend on multiple libraries. It is used in conjunction with native build environments such as Make, Qt Creator, Ninja, Apple’s Xcode, and Microsoft Visual Studio. It has minimal dependencies, requiring only a C++ compiler on its own build system.CMake, Wikipedia
All to avoid this
Cuda Path and cudnn64_7.dll
And the last one:
- Download cudnn64_7.dll from https://developer.nvidia.com/cudnn
- Copy the cudnn64_7.dll into the %CUDA_PATH%/bin directory
- As reference, my CUDA Path is: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin
This one was deep in stack overflow and is super important!