b38fd876b2
* SDK-664: Updating the sample apps with x64 * Adding the yml for configuration * Updating the travis yml * Updating the project files to remove duplicate entries of x64 * Updating the configurations * Updating the yml to publish the Artifacts and rebasing master * Updating the verbosity of yml * Fix enum definition of ethinicity to the latest build changes * Adding the new AU's * Updating the README to indicate that the app supports x64 * Update linux SDK link to 3.1-396
95 lines
4 KiB
Markdown
95 lines
4 KiB
Markdown
#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 SDK 3.1 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*
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- Windows: []
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(https://ci.appveyor.com/project/ahamino/win-sdk-samples)
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- Ubuntu: [](https://travis-ci.org/Affectiva/cpp-sdk-samples)
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Dependencies
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------------
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*Windows*
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- Affdex SDK 3.1 (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 or higher
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- Affdex SDK 3.0
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- CMake 2.8 or higher
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- GCC 4.8 or higher
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*Additional dependencies*
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- OpenCV 3.1
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- Boost 1.59
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Installation
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------------
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- Download Affdex SDK [from here](http://developer.affectiva.com/downloads)
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- Sign up for an evaluation license [by submitting this form](http://www.affectiva.com/45-day-free-trial/)
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*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*
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```bashrc
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sudo apt-get install build-essential libopencv-dev libboost1.55-all-dev cmake
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wget https://download.affectiva.com/linux/affdex-cpp-sdk-3.0-298-linux-64bit.tar.gz
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mkdir $HOME/affdex-sdk
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tar -xzvf affdex-cpp-sdk-3.0-linux-64bit.tar.gz -C $HOME/affdex-sdk
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export AFFDEX_DATA_DIR=$HOME/affdex-sdk/data
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git clone https://github.com/Affectiva/cpp-sdk-samples.git $HOME/sdk-samples
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mkdir $HOME/build
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cd $HOME/build
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cmake -DOpenCV_DIR=/usr/ -DBOOST_ROOT=/usr/ -DAFFDEX_DIR=$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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OpenCV-webcam-demo (c++)
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------------------
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Project for demoing the [FrameDetector class](http://developer.affectiva.com/v3/windows/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:
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-h [ --help ] Display this help message.
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-d [ --data ] arg (=data) Path to the data folder
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-l [ --license ] arg (=test.license) License file.
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-r [ --resolution ] arg (=640 480) Resolution in pixels (2-values): width
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height
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--pfps arg (=30) Processing framerate.
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--cfps arg (=30) Camera capture framerate.
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--bufferLen arg (=30) process buffer size.
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--cid arg (=0) Camera ID.
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--faceMode arg (=0) Face detector mode (large faces vs small
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faces).
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--numFaces arg (=1) Number of faces to be tracked.
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--draw arg (=1) Draw metrics on screen.
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Video-demo (c++)
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----------
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Project for demoing the Windows SDK [VideoDetector class](http://developer.affectiva.com/v3/windows/analyze-video/) and [PhotoDetector class](http://developer.affectiva.com/v3/windows/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.
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-d [ --data ] arg (=data) Path to the data folder
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-l [ --license ] arg (=test.license) License file.
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-i [ --input ] arg Video or photo file to process.
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--pfps arg (=30) Processing framerate.
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--draw arg (=1) Draw video on screen.
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--faceMode arg (=1) Face detector mode (large faces vs small
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faces).
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--numFaces arg (=1) Number of faces to be tracked.
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--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)
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