audience_engagement_analysis's Introduction

Audience Behaviour Analysis

Run using following command

python face_recog_track.py
How long you wanna capture video for:12
Press Enter when you are ready

Video is captured
Generating AU files
AU calculation started

------------------------Output--------------------------
FEAR 5.661862734615385
------------------------Output--------------------------
ANGER
2.9991877153846156
CONTEMPT
3.5831033076923076
SADNESS
1.7732346538461536
FEAR
5.661862734615385
DISGUST
1.2367517692307692
HAPPINESS
3.7495196538461535
SURPRISE
3.0184412461538455

Project TEAM

Amit
Anchal
Chanuwas
Juan
Manal

Installation

Windows

face_recognition

Download and install scipy and numpy packages . Remember to grab correct version based on your current Python version.
Download Boost library source code for your current MSVC from this link.
- Extract the Boost source files into C:\local\boost_1_65_1
- Create a system variable with these parameters:
  - Name: VS140COMNTOOLS
  - Value: C:\Program Files (x86)\Microsoft Visual Studio 14.0\Common7\Tools\
- Open Developer Command Prompt for Visual Studio and go to the current directory of Boost extracted and try these commands to compile Boost:
  - bootstrap
  - b2 -a --with-python address-model=64 toolset=msvc runtime-link=static
- If you successfully compile Boost, it should create compiled files in stage directory.
Grab latest version of dlib from this repo and extract it. Go to dlib directory and open cmd and follow these commands to build dlib:

        set BOOST_ROOT=C:\local\boost_1_65_1
        set BOOST_LIBRARYDIR=C:\local\boost_1_65_1\stage\lib
        python setup.py install --yes USE_AVX_INSTRUCTIONS`