https://github.com/hercules45/realtime-object-detection-yolo

Easy-to-use Jupyter Notebook for live object detection with YOLOv8 and OpenCV. Requires minimal setup.
https://github.com/hercules45/realtime-object-detection-yolo

object-detection opencv real-time ultralytics webcam yolo yolov8

Last synced: 9 months ago
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Easy-to-use Jupyter Notebook for live object detection with YOLOv8 and OpenCV. Requires minimal setup.

• Host: GitHub
• URL: https://github.com/hercules45/realtime-object-detection-yolo
• Owner: Hercules45
• Created: 2025-02-17T07:00:30.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-02-19T09:32:14.000Z (over 1 year ago)
• Last Synced: 2025-03-06T03:18:31.487Z (over 1 year ago)
• Topics: object-detection, opencv, real-time, ultralytics, webcam, yolo, yolov8
• Language: Jupyter Notebook
• Homepage:
• Size: 13.7 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Live Object Detection with YOLO (Jupyter Notebook)

This Jupyter Notebook (`object_detection.ipynb`) performs live object detection using a pre-trained YOLOv8 model and OpenCV. It captures video from your webcam, detects objects, and displays the results.

## Usage

1.  **Open `object_detection.ipynb` in Jupyter Notebook or JupyterLab.**

2.  **Run the cells sequentially.**  The notebook will:

    *   Install `ultralytics` (if not already installed).

    *   Download the `yolov8n.pt` model weights (if needed) into a `weights` subdirectory.

    *   Start capturing video from your webcam.

    *   Display the live video with object detections.

3.  **Press 'q' to quit.**