Face Recognition

This program uses OpenCV to detect faces in real-time using the webcam. When a face is detected, the program displays a rectangle around the face and counts the number of faces in the frame. The program also draws a line at the top of the frame and displays a warning message when a face crosses the line. The program saves a cropped image of the detected face with a timestamp on it to a folder named "saved". The program can also display the saved images in a new window.

Demonstration Video

Requirements

OpenCV
NumPy
datetime
os
threading

Files

intruder_det.py: The main Python script that runs the face recognition with intruder detection.
whatsapp_message.py: A Python script that sends a WhatsApp message to a specified number.
haarcascade_frontalface_default.xml: A pre-trained Haar Cascade classifier for face detection.

Notes

The program uses the Haar Cascade Classifier to detect faces. The classifier XML file is stored in the "XML_Files" folder.
The program displays a warning message when a face crosses the line. The line is drawn at 200 pixels from the top of the frame and can be changed by modifying the line_y variable.
The program saves the detected faces to a folder named "saved". The folder can be changed by modifying the saveImage() function.
The problem of the video feed lagging behind the face detection is solved by using a separate thread to send the WhatsApp message. The thread is created in the ThreadSendMessage() function.

How to Contribute

Fork the repository
Clone the repository to your local machine
```
git clone <url>
```
Create a python virtual environment
```
python -m venv .venv
```
Activate the virtual environment
```
 .venv\Scripts\activate
```

Install the requirements

pip install -r requirements.txt

To see the program execution:

cd Main
python intruder_det.py

Create a new branch
```
 git checkout -b <branch-name>
```
Make your changes

Commit and push your changes

git add .
git commit -m "<message>"
git push origin <branch-name>