Face Attendance System Development by Krishnansh VasaniyaFace Attendance System Development by Krishnansh Vasaniya

Face Attendance System Development

Krishnansh Vasaniya

Completed work

Web Developer

Python

Streamlit

Electronics

Like this project

Completed work

Posted Jun 6, 2025

Developed a facial recognition attendance system using DeepFace and Streamlit.

Likes

Views

Resources

Hire Freelancers

Explore all Top independents Design Engineering Marketing Music & audio Social media Video & animation Product Business consulting & HR Other

Contact

Contact support

Company

Mission Careers Terms & conditions Privacy policy Cookie policy

Face Attendance System Development

Krishnansh Vasaniya

Completed work

Web Developer

Python

Streamlit

Electronics

🧑‍🏫 Face Attendance System (DeepFace + Streamlit)

A simple yet powerful web app that uses facial recognition to mark attendance automatically using the DeepFace library. Built with Python and deployed using Streamlit Cloud.

Image.png

🔥 Features

🔐 Register new faces (with name & image)

🧠 Face verification using DeepFace

📸 Upload an image to detect and mark attendance

✅ Auto-prevents duplicate entries for the same day

📄 Attendance log with download as CSV

🌙 Dark UI theme (customizable)

🚀 Live Demo

👉 Click to try the live app

📦 Installation (Local)

# Clone the repo
git clone https://github.com/krishnanshvasaniya/face_attendance_streamlit.git
cd face_attendance_streamlit

# Create a virtual environment (Python 3.10 recommended)
python -m venv venv
source venv/bin/activate  # or venv\Scripts\activate on Windows

# Install dependencies
pip install -r requirements.txt

# Run the app
streamlit run app.py

Like this project

Completed work

Posted Jun 6, 2025

Developed a facial recognition attendance system using DeepFace and Streamlit.

Likes

Views

Join 50k+ companies and 1M+ independents

Hire creatives Get hired

For independents

Contra Pro Manage freelance projects Get verified as an expert Find jobs Get discovered Sign contracts Send invoices Commission-free payments

For companies

For companies Manage team projects Share hiring workspace Post jobs Discover contractors Sign contracts Approve invoices Global payments & tax compliance

Use Cases

For companies For freelancers For creator tools For agencies For VCs

Resources

Hire Freelancers

Explore all Top independents Design Engineering Marketing Music & audio Social media Video & animation Product Business consulting & HR Other

Company

Mission Careers Terms & conditions Privacy policy Cookie policy

Contact

Contact support

For independents

Contra Pro Manage freelance projects Get verified as an expert Find jobs Get discovered Sign contracts Send invoices Commission-free payments

For companies

For companies Manage team projects Share hiring workspace Post jobs Discover contractors Sign contracts Approve invoices Global payments & tax compliance

Use Cases

For companies For freelancers For creator tools For agencies For VCs

Resources

Hire Freelancers

Explore all Top independents Design Engineering Marketing Music & audio Social media Video & animation Product Business consulting & HR Other

Contact

Contact support

Company

Mission Careers Terms & conditions Privacy policy Cookie policy

🧑‍🏫 Face Attendance System (DeepFace + Streamlit)

A simple yet powerful web app that uses facial recognition to mark attendance automatically using the DeepFace library. Built with Python and deployed using Streamlit Cloud.

Image.png

🔥 Features

🔐 Register new faces (with name & image)

🧠 Face verification using DeepFace

📸 Upload an image to detect and mark attendance

✅ Auto-prevents duplicate entries for the same day

📄 Attendance log with download as CSV

🌙 Dark UI theme (customizable)

🚀 Live Demo

👉 Click to try the live app

📦 Installation (Local)

# Clone the repo
git clone https://github.com/krishnanshvasaniya/face_attendance_streamlit.git
cd face_attendance_streamlit

# Create a virtual environment (Python 3.10 recommended)
python -m venv venv
source venv/bin/activate  # or venv\Scripts\activate on Windows

# Install dependencies
pip install -r requirements.txt

# Run the app
streamlit run app.py