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Multi-Face Attendance System using Deep Learning

Description

A deep learning–based system that detects and recognizes multiple faces simultaneously from images or video streams to automate attendance marking. Designed as a modular backend that can be integrated with external web or mobile applications.

Libraries Used

  • Python 3.x
  • Ultralytics (YOLO)
  • OpenCV
  • TensorFlow / Keras
  • NumPy
  • OS / Pathlib

Base Path Configuration

The project uses a base path for accessing models, datasets, and outputs.
After cloning the repository, update the base path according to your local machine. You may use os.getcwd() python function.

Example (Windows):

BASE_DIR = r"C:\Users\yanko\OneDrive\Desktop\Desktop Files\present-me\colleges"

README files for each script are there in docs folder

About

Multi-Face Attendance System using Deep Learning that automatically detects and recognizes multiple individuals simultaneously from images or video streams. The system uses deep learning–based face embeddings to mark attendance accurately and is designed for easy integration with external web or mobile applications.

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