#Sample Apps for Affdex SDK for Windows and Linux Welcome to our repository on GitHub! Here you will find example code to get you started with our Affdex Linux SDK 3.2, Affdex Windows SDK 3.4 and begin emotion-enabling you own app! Documentation for the SDKs is available on the Affectiva's Developer Portal. *Build Status* - Windows: [![Build status](https://ci.appveyor.com/api/projects/status/pn2y9h8a3nnkiw41?svg=true)] (https://ci.appveyor.com/project/ahamino/win-sdk-samples) - Ubuntu: [![Build Status](https://travis-ci.org/Affectiva/cpp-sdk-samples.svg?branch=master)](https://travis-ci.org/Affectiva/cpp-sdk-samples) Dependencies ------------ *Windows* - Affdex SDK 3.4 (64 bit) - Visual Studio 2013 or higher *Linux* - Ubuntu 14.04 or CentOS 7 - Affdex SDK 3.2 - CMake 2.8 or higher - GCC 4.8 *Additional dependencies* - OpenCV 2.4 - Boost 1.59 - libuuid - libcurl - libopenssl Installation ------------ *Windows* - Download Affdex SDK [from here](https://knowledge.affectiva.com/docs/getting-started-with-the-emotion-sdk-for-windows) - Install the SDK using MSI installer. - The additional dependencies get installed automatically by NuGet. *Ubuntu* - Download Affdex SDK [from here](https://knowledge.affectiva.com/docs/getting-started-with-the-affectiva-sdk-for-linux) ```bashrc sudo apt-get install build-essential libopencv-dev libboost1.55-all-dev libcurl4-openssl uuid-dev cmake wget https://download.affectiva.com/linux/affdex-cpp-sdk-3.2-20-ubuntu-xenial-xerus-64bit.tar.gz mkdir $HOME/affdex-sdk tar -xzvf affdex-cpp-sdk-3.2-20-ubuntu-xenial-xerus-64bit.tar.gz -C $HOME/affdex-sdk export AFFDEX_DATA_DIR=$HOME/affdex-sdk/data git clone https://github.com/Affectiva/cpp-sdk-samples.git $HOME/sdk-samples mkdir $HOME/build cd $HOME/build cmake -DOpenCV_DIR=/usr/ -DBOOST_ROOT=/usr/ -DAFFDEX_DIR=$HOME/affdex-sdk $HOME/sdk-samples make export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$HOME/affdex-sdk/lib ``` *CentOS* ```bashrc sudo yum install libcurl-devel.x86_64 libuuid-devel.x86_64 opencv-devel cmake.x86_64 wget https://sourceforge.net/projects/boost/files/boost/1.55.0/boost_1_55_0.tar.gz/download -O boost_1_55_0.tar.gz tar -xzvf boost_1_55_0.tar.gz -C $HOME cd boost_1_55 ./bootstrap.sh --with-libraries=log,serialization,system,date_time,filesystem,regex,timer,chrono,thread,program_options sudo ./b2 link=static install wget https://download.affectiva.com/linux/affdex-cpp-sdk-3.2-2893-centos-7-64bit.tar.gz mkdir $HOME/affdex-sdk tar -xzvf affdex-cpp-sdk-3.2-2893-centos-7-64bit.tar.gz -C $HOME/affdex-sdk export AFFDEX_DATA_DIR=$HOME/affdex-sdk/data git clone https://github.com/Affectiva/cpp-sdk-samples.git $HOME/sdk-samples mkdir $HOME/build cd $HOME/build cmake -DOpenCV_DIR=/usr/ -DBOOST_ROOT=/usr/ -DAFFDEX_DIR=$HOME/affdex-sdk $HOME/sdk-samples make export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$HOME/affdex-sdk/lib ``` OpenCV-webcam-demo (c++) ------------------ Project for demoing the [FrameDetector class](http://developer.affectiva.com/v3_2/cpp/analyze-frames/). It grabs frames from the camera, analyzes them and displays the results on screen. The following command line arguments can be used to run it: -h [ --help ] Display this help message. -d [ --data ] arg (=data) Path to the data folder -r [ --resolution ] arg (=640 480) Resolution in pixels (2-values): width height --pfps arg (=30) Processing framerate. --cfps arg (=30) Camera capture framerate. --bufferLen arg (=30) process buffer size. --cid arg (=0) Camera ID. --faceMode arg (=0) Face detector mode (large faces vs small faces). --numFaces arg (=1) Number of faces to be tracked. --draw arg (=1) Draw metrics on screen. Video-demo (c++) ---------- Project for demoing the Windows SDK [VideoDetector class](http://developer.affectiva.com/v3_2/cpp/analyze-video/) and [PhotoDetector class](http://developer.affectiva.com/v3_2/cpp/analyze-photo/). It processs video or image files, displays the emotion metrics and exports the results in a csv file. The following command line arguments can be used to run it: -h [ --help ] Display this help message. -d [ --data ] arg (=data) Path to the data folder -i [ --input ] arg Video or photo file to process. --pfps arg (=30) Processing framerate. --draw arg (=1) Draw video on screen. --faceMode arg (=1) Face detector mode (large faces vs small faces). --numFaces arg (=1) Number of faces to be tracked. --loop arg (=0) Loop over the video being processed. For an example of how to use Affdex in a C# application .. please refer to [AffdexMe](https://github.com/affectiva/affdexme-win)