Security Camera System

A comprehensive security camera system with motion detection, AI-powered object recognition, and alert management capabilities.

Project Structure

• Frontend: Flask-based web interface for camera monitoring and control
• Backend: Django REST API for alert management and media storage

Requirements

• Python 3.10+
• Dependencies listed in requirements.txt
• CUDA-compatible GPU (recommended for optimal performance)

Setup Instructions

1. Clone the repository

git clone <repository-url>
cd Security_cam

2. Set up virtual environment

python -m venv venv

Activate virtual environment

On Windows:

venv\Scripts\activate

On macOS/Linux:

source venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

4. Start the Backend (Django)

cd Backend
python manage.py migrate
python manage.py runserver

The Django backend will be available at http://127.0.0.1:8000/

5. Start the Frontend (Flask)

Open a new terminal, activate the virtual environment, and run:

cd Frontend
python app.py

The Flask frontend will be available at http://127.0.0.1:5000/

Features

• Real-time video monitoring
• Motion detection
• Object recognition using YOLO
• Video recording of security events
• Alert management system
• Web interface for monitoring and configuration

Configuration

You can modify camera settings and detection parameters in the Frontend/config.py file.

Note:

• Nivida RTX Gpu is necessary to run this project.
• After git cloning the repo first install the cuda and tensort library for your specific gpu version then pip install for requirements.txt file.
• If don't have rtx gpu use .pt file and in config.py file make the changes in code to use .pt to run this project.
• Model used in this project is used to detect person and weapon.