README.md

Features

• Albums management
• Sharing
  • Different access levels
  • Sharing with other users or using a link
• Face Recognition
  • Detection of faces in photos
  • Naming of detected faces

Demo

Technical details

• Written in Python using the Django framework.
• Designed with HTML and SCSS
• Running on Heroku
• PostgreSQL database hosted on AWS
• AWS S3 for storing photos
• Azure Cognitive Services for face recognition

Architecture

Installation

FaceIt requires the following environment variables:

• SECRET_KEY - The Django secret key
• EMAIL_USER - The email address of the user used to send emails (gmail)
• EMAIL_PASSWORD - The password of the user used to send emails (gmail)
• AWS_ACCESS_KEY_ID - The access key id of the user used to store photos on AWS S3
• AWS_SECRET_ACCESS_KEY - The secret access key of the user used to store photos on AWS S3
• AWS_BUCKET_NAME - The name of the bucket used to store photos on AWS S3
• AZURE_KEY - The key of the user used to detect faces on Azure Cognitive Services
• AZURE_ENDPOINT - Azure Cognitive Services endpoint
• DB_NAME - The name of the database (postgres)
• DB_USER - The name of the user used to connect to the database
• DB_PASSWORD - The password of the user used to connect to the database
• DB_HOST - The host of the database
• DB_PORT - The port of the database

If you have everything set up, you can clone the repository and install the requirements:

pip install -r requirements.txt

Now you can run the application:

python manage.py migrate
python manage.py collectstatic --noinput
python manage.py runserver 0.0.0.0:8080

Make sure to run python manage.py process_tasks to enable face recognition and email valiation.