/empty_space_shelf_yolov8

Primary LanguagePython

Empty Space in a shelf or an aisle Detection with YOLOv8

Empty Space Detection with YOLOv8 is a computer vision project that aims to detect falls using the YOLOv8 object detection model. This project provides a real-time Empty Space detection solution by analyzing video streams.

Features

  • Utilizes the YOLOv8 object detection model for accurate fall detection
  • Real-time detection and immediate alert using visual cues
  • With accurate identification of vacant areas, businesses can enhance their restocking processes, improve customer experience, and maximize shelf utilization.
  • Built with efficiency and ease-of-use in mind

Requirements

  • Python 3.x
  • OpenCV
  • Ultralytics YOLOv8

Getting Started

  1. Clone the repository:
https://github.com/alijawad07/empty_space_shelf_yolov8
  1. Install the required dependencies:
pip install -r requirements.txt

  1. Update the configuration file with the appropriate paths and parameters.

  2. Run the empty_shelf script:

python3 empty_shelf.py --data --source --output --weights

  • --data => .yaml file with dataset and class details

  • --source => Path to directory containing video

  • --output => Path to save the detection results

  • --weights => Path to yolov8 weights file

Acknowledgments

  • Thanks to Roboflow for providing the comprehensive fall detection dataset used in training the YOLOv8 model.
  • Special appreciation to Ultralytics for developing the YOLOv8 model and its integration with the project.

References