README.md

• GPU acceleration
  • Tensorflow libraries
    • Windows
    • Linux
• Cross compilation
  • Raspberry Pi
    • Installing the toolchain
      • Windows
      • Ubuntu

There are 3 C++ samples: Benchmark, Recognizer and RuntimeKey. Check here, here and here on how to build and use them.

The C++ samples are common to all platforms: Android, Windows, iOS, Raspberry Pi (3 or 4), Linux...

For Android, we recommend using the Java samples under android folder. These are complete samples with support for reatime recognition from video stream (camera) and require Android Studio to build. More info on how to install these samples is available here.

GPU acceleration

We use Tensorflow as deep learning framework. The current repository contains Tensorflow libraries built without GPU functions to reduce the size. Also, few developers need GPU accelerated libraries. The GPU libraries will work on your device even if you don't have NVIDIA GPU.

Tensorflow libraries

The Tensorflow libraries are hosted at:

• [1] Windows_x86_64_CPU+GPU: https://doubango.org/deep_learning/libtensorflow_r1.15_cpu+gpu_windows_x86-64.zip
• [2] Windows_x86_64_CPU: https://doubango.org/deep_learning/libtensorflow_r1.15_cpu_windows_x86-64.zip
• [3] Linux_x86_64_CPU+GPU: https://doubango.org/deep_learning/libtensorflow_r1.14_cpu+gpu_linux_x86-64.tar.gz
• [4] Linux_x86_64_CPU: https://doubango.org/deep_learning/libtensorflow_r1.14_cpu_linux_x86-64.tar.gz

Windows

To use the Tensorflow version with GPU funtions you'll need to download [1], extract tensorflow.dll and override CPU-only tensorflow.dll in binaries/windows/x86_64

Linux

On Linux, libtensorflow.so is missing in the binaries folder. You'll need to download your preferred Tensorflow version ([3] or [4]) and copy the content to binaries/linux/x86_64.

Cross compilation

Every sample contain a single C++ source file and is easy to cross compile.

Raspberry Pi (Raspbian OS)

This section explain how to install Raspberry Pi 4 (Raspbian OS) toolchain to cross compile the samples. These instructions can be easily adapted to another target platform (e.g Android).

Installing the toolchain

Windows

The toolchain for Raspberry Pi 4 could be found at http://sysprogs.com/getfile/566/raspberry-gcc8.3.0.exe and more toolchain versions are at https://gnutoolchains.com/raspberry/.

If you haven't changed the installation dir then, it should be installed at C:\SysGCC. To add the toolchain to the %PATH:

set PATH=%PATH%;C:\SysGCC\raspberry\bin

Ubuntu

sudo apt-get update
sudo apt-get install crossbuild-essential-armhf