Real-Time-Object-Detection-System

Utilizing Deep Learning for Object Recognition and Tracking in Aerial Images/Videos: A YOLO-DeepSort Approach integrated with OpenCV, Flask API & React interface.

Get started with Flask API

To run this API in http://localhost:5000/, follow these steps:

1. Clone the repository to your local machine:

   git clone https://github.com/YassineOuhadi/Real-Time-Object-Detection.git

2. Install required packages:

   pip install -U pip virtualenv pip install flask pip install ultralytics pip install opencv-python

3. Create a virtual environment:

   python -m venv venv

4. Activate the virtual environment:

   source venv/bin/activate

5. Run the Flask application:

   python -m flask --app ./app.py run

Get started with React Interface

1. Install dependencies:

   npm install

2. Install client dependencies:

   cd client npm install

3. Run the application:

   npm run dev

4. Access the application in a web browser at http://localhost:3000/.

Overview

License