Online face analysis for digital signage

Summary

The project is an ad agent that analyses people's faces and predicts their age and gender to show custom ads, the agent is powered by face detection, age & gender prediction algorithms and connected to a SQL database of ads.

Dataset

The dataset used in this project is the “IMDB-WIKI” consists of 500000 images, it is the largest publicly available dataset of face images with gender and age labels for training. We provide pre-trained models for both age and gender prediction.

Model Architecture

The model that was used to perform this task of age and gender detection is Wide ResNet.

Dependencies

• Python 3.7 64bit
• Windows 10 64 bit / version 1909
• Fask web server
• MYSQL server 5.*

Recommended

Note that is better to create a new virtual environment and install requirements in it to isolate your project from your default environment and to avoid all problems that caused by version conflict.

• The first think is to install virtualenv.

• virtualenv==20.0.21
  

• Clone the project

•   cd\Online-Face-Analysis-Ad-Agent
  

  Now the folder venv is you main environment and you can name it what are every you want. and all the packages you will install it will store there.

•   virtualenv \venv
  

  To activate your virtual environment.

•   venv\Scripts\activate.bat
  

  Now you can install any python packages you want in the command line that you are activating the virtual environment and they will be isolated.

  To exit the virtual environment.

•   deactivate
  

  For more information check her.

Requirements

• Get the package from PyPi.
• All requirements that you will need with its version it's exist in requirements.txt so you need just to run this command to install it all :

  !pip install -r requirements.txt
  

Ads database

We use the mysql database to store the ads informations. create an databese named ads_agent and run the script database.sql.

Note that the database login informations is :

• host='localhost'
• database='ads_agent'
• user='root'
• password=''

Note that you have to install mysql-connector you can download it her.

How to run it

In order to run the demo first you have the download our pretrained weights her and put it in the folder ./pretrained_weights.

When you install all requirements and you make you environment ready run the main.py and check the http://localhost:5000/.

Demo

Congratulation.

The video above shown the demonstration :

Authors

• Abdelati Elasri
• Mouad Boulahdoud
• Hassn Ait Baha
• El Houcine ES SANHAJI

Thank you.