Smart Attendance System using Face Detection with Open CV

Software Engineering mini project

Libraries Used:

○ Numpy - could be a library for Python, adding support for multi-dimensional arrays and matrices, in conjunction with an enormous assortment of high-level mathematical functions to operate on these arrays.
○ Pandas - is a fast, powerful, flexible, and easy to use open-source data analysis and manipulation tool, built on top of the Python programming language.
○ Haar Cascade - is a machine learning object detection algorithm used to identify objects in an image or video and based on the concept of features proposed by Paul Viola and Michael Jones in their paper "Rapid Object Detection using a Boosted Cascade of Simple Features" in 2001.
○ Datetime - It’s a combination of date and time along with the attributes year, month, day, hour, minute, second, microsecond, and info.
○ Face_Recognition - Recognize and manipulate faces from Python or the command line with the world’s simplest face recognition library.
○ OpenCV - a library of programming functions primarily geared toward real-time computer vision.

Instructions to run:

1. First download or clone the project
2. Import the project to your favourit IDE
3. Create an python enviroment
4. Install all the packages
5. Change the mail information
6. Run the project using the command line or your IDE Run Button

Run:

1. python -m venv env
2. .\env\Scripts\activate
3. Install below libraries:

• pip install opencv-contrib-python
• pip install numpy
• pip install pandas
• pip install Pillow
• pip install pytest-shutil
• pip install python-csv
• pip install yagmail

4. py main.py

NOTE: Any modification/additional feature in this project would be appreciated.
Send a PR along with output screenshot, to get the new changes merged.