https://github.com/iam-salma/face-recognition-attendance-system

AI-based face recognition attendance system using OpenCV and Streamlit. Mark, view, and manage attendance with real-time webcam capture.
https://github.com/iam-salma/face-recognition-attendance-system

attendance-system face-recognition haarcascade opencv opencv-python python streamlit

Last synced: 2 months ago
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AI-based face recognition attendance system using OpenCV and Streamlit. Mark, view, and manage attendance with real-time webcam capture.

• Host: GitHub
• URL: https://github.com/iam-salma/face-recognition-attendance-system
• Owner: iam-salma
• License: mit
• Created: 2025-07-19T16:55:56.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2025-07-19T16:56:49.000Z (11 months ago)
• Last Synced: 2025-07-19T20:26:03.836Z (11 months ago)
• Topics: attendance-system, face-recognition, haarcascade, opencv, opencv-python, python, streamlit
• Language: Python
• Homepage:
• Size: 290 KB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          


  





  Face Recognition Based Attendance System





  

    

  

  

    

  

  

    

  

  

    

  

  



A real-time face recognition-based attendance system built using **Streamlit** for the user interface, **OpenCV** for face detection and recognition, and **Haar Cascade classifiers** for facial feature extraction. This system allows you to register students, train a face recognition model, and take or view attendance with ease.

---

## 🚀 Features

- 🧑‍🎓 Register students with facial image capture

- 🧠 Train model using OpenCV and Haar Cascades

- 🤖 Automatic attendance using webcam and face recognition

- ✍️ Manual attendance entry

- 📅 View attendance records by subject and date + percentage

- 🗑️ Delete student data from the system

- 🔈 Text-to-speech for better accessibility

---

## 🛠️ Tech Stack

- **Python 3.8+**

- **Streamlit** – GUI and user interactions

- **OpenCV** – Image processing and recognition

- **Haar Cascades** – Face detection

- **CSV** – Storage of student details and attendance logs

---

## 📁 Project Structure

```

📦face-recognition-attendance/

├── app.py                         # Main Streamlit app

├── takeImage.py                   # Capture and save student face

├── trainImage.py                  # Train recognition model

├── automaticAttendance.py         # Detect and mark attendance

├── takemanually.py                # Manual attendance input

├── view_attendance.py             # Display attendance by subject/date

├── delete.py                      # Delete student and retrain

├── db.py                          # CSV-based student DB utilities

├── TrainingImage/                 # Folder storing face images

├── TrainingImageLabel/            # Trained model file (e.g., .yml)

├── StudentDetails/                # CSV file for student info

├── Attendance/                    # Attendance records

├── HaarCascade/haarcascade_frontalface_default.xml

```

---

## ▶️ How to Run

1. **Install dependencies**

```bash

pip install -r requirements.txt

```

2. **Run the app**

```bash

streamlit run app.py

```

3. **Use Interface**

- Register students

- Train model

- Take automatic or manual attendance

- View or delete records

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## ✅ Requirements

- Webcam-enabled system

- Python 3.8 or higher

---

## 📌 Notes

- Make sure the `haarcascade_frontalface_default.xml` file is available in the correct path.

- After deleting a student, the model is retrained automatically.

- CSV files are used for storage – you can upgrade to a database like PostgreSQL if needed.

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If you found this project helpful or interesting, please consider giving it a ⭐️ on GitHub — it motivates and helps others discover it! ✌️

ENJOY! 🎉