Security-System-with-Object-Detection-and-Notification

Human Face Detection and Notification System

Introduction

This project implements a human face detection system using Python's OpenCV library. When a human face is detected by a live camera feed, the system sends a notification to a Telegram bot. It serves as an IoT-based project designed to demonstrate integration between image processing and real-time notifications.

Components Required

• A computer with Python installed (for development and running the code)
• USB or built-in webcam
• Telegram bot account for sending notifications

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Setting Up the Telegram Bot

1. Create a new Telegram bot using BotFather.
2. Save the bot token provided by BotFather.
3. Obtain the chat_id using Telegram API by sending a message to the bot and retrieving updates.

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Image Processing

• The Haar Cascade Classifier is used for detecting faces in a live video feed.
• Real-time detection is implemented using OpenCV's cv2.CascadeClassifier.

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Sending Notifications

• A notification is sent to the Telegram bot when a face is detected.
• The system ensures a delay of 5 seconds before sending another notification.

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Integration and Main Script

The project integrates image processing and Telegram bot notifications into a unified system.

Conclusion

The project demonstrates the effective integration of real-time image processing and IoT notification systems. It highlights the potential of combining OpenCV and Telegram for practical applications.

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Libraries Used

• OpenCV
• Requests

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How to Run

1. Install the required libraries:

   pip install opencv-python requests
   

2. Replace YOUR_BOT_TOKEN and YOUR_CHAT_ID in the code with your Telegram bot details.
3. Run the image_processing.py script.
4. Ensure the webcam is connected and functioning.
5. Monitor the Telegram bot for notifications.