TED

This security application uses facial recognition to detect and send an email alert to the user of unrecognized visitors.

User Stories

• As a user, I to assign trusted visitors to be recognized by the camera.
• As a user, I want the system to take a picture and email me an image of an unrecognized visitor so I can review any potential threats.
• As a developer, I want to create a simple web application interface for a user to be able to easily add names and images of trusted visitors.
• As a developer, I want seemless automation of capturing an image of an unrecongized visitor through sending an email with the image as an attachment.
• As a developer, I want to delete any .png that are created as a result of camera training or frame capturing after processing the images in order to maintain memory space.
• As a student, I want to create a project that is unique to what we have done in the past.
• As a student, I want to deploy with AWS and Docker in keeping with standard practices of the field.

Stretch Goal

• As a developer I want to utilize a Raspberry Pi to handle the camera, facial recognition, and email scripts.

Getting Started

• Clone the repository and install the dependencies.
• In a .env file, include the following details:

# For email alerts:
FROM_ADDR= <gmail address from which to send alerts>
FROM_PASSWORD= <password for the above gmail address>
TO_ADDR= <gmail address to send alerts to>

# For Django app:
SECRET_KEY= <secret key received from Django>
ALLOWED_HOSTS= <host site (AWS EC2 instance or other)>

# For database access, fill in your information to the following fields:
DB_NAME=
DB_USER=
DB_PASSWORD=
DB_SERVICE=
DB_PORT=
DB_HOST=
DATABASE_URL=

# If deploying to AWS, add these fields with your AWS instance information:
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_S3_CUSTOM_DOMAIN=

Installing

In a virtual environment, run pipenv install --dev and pipenv run pip freeze > requirements.txt to install and apply the necessary dependencies.

Running the tests

Tests for the Django app can be run within the Docker container using the command ./manage.py test

Deployment

Deployed on AWS with Docker, utilizing RDS and S3.

Built With

• Python
• Django
• Docker
• PostgreSQL
• OpenCV
• Watchdog
• Psycopg2-binary
• Gunicorn
• NginX
• AWS
• RDS
• S3

Authors

• Tim Schoen
• Dan Le
• Evy Haan

Versioning

April 2019: Version 1.0.0

License

This project is licensed under the MIT License - see the LICENSE.md file for details