YOLOv8 Object Detection with OpenCV and Ultralytics

This Python script uses YOLOv8 from Ultralytics for real-time object detection using OpenCV. The script initializes a camera, loads the YOLOv8 model, and processes frames from the camera, annotating detected objects with bounding boxes.

Prerequisites

Make sure you have the following libraries installed:

cv2 (OpenCV)
ultralytics
supervision

pip install opencv-python
pip install ultralytics
pip install supervision==0.3.0

Getting Started

Clone the repository:

git clone https://github.com/SYED-M-HUSSAIN/YOLOv8-Object-Detection-with-OpenCV-and-Ultralytics

Usage

Run the script:

python yolo_inference.py

Configuration

initialize_camera: Initializes the camera using OpenCV.
load_yolov8_model: Loads the YOLOv8 model from Ultralytics.
process_frame: Processes each frame from the camera using the YOLOv8 model and annotates the detected objects.
main: The main function that captures frames from the camera, processes them, and displays the annotated frames.

Customization