Face Attendance Maker using Streamlit & OpenCV


#python , #streamlit , #opencv , #machine-learning , #attendance-system
- ๐ Attendance tracking made smarter and seamless with Face Recognition using Streamlit and OpenCV.
๐ Introduction
Traditional attendance systems often rely on manual input, signatures, or swipe cards โ all of which are prone to manipulation or inefficiencies.
With the rise of AI and computer vision, we can now automate this process using face recognition technology. This project demonstrates how to build a Face Attendance System using Python, Streamlit, and OpenCV, offering a sleek and interactive interface.
๐ง Core Technologies Used
Python โ The programming backbone of the project.
OpenCV โ For face detection and recognition.
Streamlit โ For creating a fast and beautiful web app.
NumPy / Pandas โ For managing facial embeddings and logs.
Face Recognition Library โ Built on
dlib
, used for accurate face matching.
๐ Key Features
๐ธ Real-time webcam feed with live face recognition
๐ง Auto-mark attendance with name and timestamp
๐ Save and manage data in CSV
๐ Easy-to-use Streamlit UI
๐ฆ Option to add new faces to the database
๐ How It Works
Face Registration
Capture and encode the face of each person
Save the encoding (vector data) with their name
Face Detection & Matching
The webcam feed is continuously monitored
Faces in the frame are matched with the registered ones
If a match is found, attendance is marked with time
๏ฟฝ๏ฟฝ Project Structure
face-attendance-maker/
โโโ app.py
โโโ encode_faces.py
โโโ attendance.csv
โโโ images/
โ โโโ known_faces/
โโโ utils.py
โโโ requirements.txt
#Clone the Repo:
git clone https://github.com/anurag-panda-nshm/face-attendance-maker.git
cd face-attendance-maker
#Install Dependencies:
pip install -r requirements.txt
#Run the App:
streamlit run app.py
๐ Resources
๐ป GitHub: Face Attendance Maker
๐ Final Thoughts
This project is a great entry point into AI-powered automation using Python. With a simple UI and powerful backend logic, this face recognition attendance system can be extended into schools, offices, or events.
If you found this helpful, leave a โญ on GitHub and feel free to fork it for your own needs!
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