This repo contains an application for automated face registration using AI.
The application is made user-friendly by providing a GUI to the application.
Before running the codes, we need to install all the prerequisites.
Have made a requirements.txt for the same.
Use pip3 install -r requirements.txt to install prerequisites.
Can be executed on x86 and ARM architecture systems.
Contents
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requirements.txt - contains all the prerequisites required for the smooth functioning of the application.
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models - conatins pre-trained models for inference.
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utils - contains the all dependencies that the main code require.
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data.csv - database to store details of the people to be registered. Please update the csv according to the given format.
Usage
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Run
python3 registration.py -
You'll be encountered with 3 options (Register/Detect/Exit)
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Register: Takes input as serial number of the person and face.
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The code uses the MTCNN model for Face detection.
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Face alignment is done using dlib.
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FaceNet is used for converting the various features of a person's face into vectors (embeddings).
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Detect: To recognize a registered person.
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When a face is detected, the system checks if the person exists in the database.
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On recognition, the person's face is highlighted with a green box.
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For Embedded Linux Platforms
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Connect 2 USB/CSI cameras (as per availability) for register and detect.
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Install drivers if required using
insmod [driver location] -
Run the application in two terminals simulatneously for real time experience.
Docker Image
Install docker using sudo apt-get install docker.io and assign sudo permission to it.
You can find the readymade image that I've already built using docker pull darpanjain/ai-input
Visit My DockerHub Profile
Run the image using docker run -it --rm ai-input
You can use the provided Dockerfile to build your own image.
- Clone the repo to your system
- Build your image using
sudo docker build -t application:v1 .
Any contributions to the project are welcome :)