This project presents a real-time face recognition system using OpenCV and Firebase as the database. Faces are detected and recognized in real-time and attendance is tracked and updated in the database. The system uses Firebase for real-time data tracking, storage, and retrieval. This repository is complete with a .yml
file to easily set up a new environment.
- Real-time face detection and recognition using
face_recognition
andcv2
- Attendance is tracked and updated in real-time on Firebase
- Student information and image are retrieved from Firebase
The system captures images from the webcam, detects faces, and recognizes them. If the recognized face matches a known student, their attendance information is retrieved and updated in the Firebase database.
It will also show a live feed of the webcam with the recognized faces highlighted and labeled, with all their respective information displayed along with customized background graphics.
-
Firstly, clone the repository to your local machine:
https://github.com/felixggj/face-recognition-app.git
-
To create a new environment using the
.yml
file, navigate to the directory where theenvironment.yml
file is located and use the following command:
conda env create -f environment.yml
- Activate the environment using:
conda activate face-recognition
Before running the project, you will need to replace serviceAccountKey.json
with your own Firebase project's service account key file and replace the databaseURL and storageBucket in the Firebase configuration.
To run the main script, navigate to the project's directory and use the following command:
python main.py