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#Sample Apps for Affdex SDK for Windows and Linux
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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 < a href = http://developer.affectiva.com/ > Affectiva's Developer Portal< / a > .
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*Build Status*
- Windows: [![Build status ](https://ci.appveyor.com/api/projects/status/pn2y9h8a3nnkiw41?svg=true )]
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(https://ci.appveyor.com/project/ahamino/win-sdk-samples)
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- Ubuntu: [![Build Status ](https://travis-ci.org/Affectiva/cpp-sdk-samples.svg?branch=master )](https://travis-ci.org/Affectiva/cpp-sdk-samples)
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Dependencies
------------
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*Windows*
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- Affdex SDK 3.4 (64 bit)
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- Visual Studio 2013 or higher
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*Linux*
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- Ubuntu 14.04 or CentOS 7
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- Affdex SDK 3.2
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- CMake 2.8 or higher
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- GCC 4.8
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*Additional dependencies*
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- OpenCV 2.4
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- Boost 1.59
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- libuuid
- libcurl
- libopenssl
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Installation
------------
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- Download Affdex SDK [from here ](http://developer.affectiva.com/downloads )
*Windows*
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- Install the SDK using MSI installer.
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- The additional dependencies get installed automatically by NuGet.
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*Ubuntu*
```bashrc
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sudo apt-get install build-essential libopencv-dev libboost1.55-all-dev libcurl-dev uuid-dev cmake
wget https://download.affectiva.com/linux/affdex-cpp-sdk-3.2-20-ubuntu-xenial-xerus-64bit.tar.gz
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mkdir $HOME/affdex-sdk
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tar -xzvf affdex-cpp-sdk-3.2-20-ubuntu-xenial-xerus-64bit.tar.gz -C $HOME/affdex-sdk
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export AFFDEX_DATA_DIR=$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 $HOME/sdk-samples
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make
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$HOME/affdex-sdk/lib
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```
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*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
```
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OpenCV-webcam-demo (c++)
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------------------
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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.
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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++)
----------
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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.
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The following command line arguments can be used to run it:
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-h [ --help ] Display this help message.
-d [ --data ] arg (=data) Path to the data folder
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-i [ --input ] arg Video or photo file to process.
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--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.
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For an example of how to use Affdex in a C# application .. please refer to [AffdexMe ](https://github.com/affectiva/affdexme-win )