Utilizing Deep Learning for Object Recognition and Tracking in Aerial Images/Videos: A YOLO-DeepSort Approach integrated with OpenCV, Flask API & React interface.
To run this API in http://localhost:5000/
, follow these steps:
-
Clone the repository to your local machine:
git clone https://github.com/YassineOuhadi/Real-Time-Object-Detection.git
-
Install required packages:
pip install -U pip virtualenv
pip install flask
pip install ultralytics
pip install opencv-python
-
Create a virtual environment:
python -m venv venv
-
Activate the virtual environment:
source venv/bin/activate
-
Run the Flask application:
python -m flask --app ./app.py run
-
Install dependencies:
npm install
-
Install client dependencies:
cd client
npm install
-
Run the application:
npm run dev
-
Access the application in a web browser at
http://localhost:3000/
.