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🌊 Underwater Trash Plastic Detection 🛢️

Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Output
  5. License
  6. Acknowledgments

🌟 About The Project

We have developed an underwater trash plastic detection project using YOLOv5 and YOLOv8 by training custom datasets. This project includes two models: one based on YOLOv5 for object detection and another using YOLOv8 for instance segmentation.

Built With

  • YOLOv5
  • YOLOv8

🚀 Getting Started

We utilized Google Colab with GPU support to run our YOLOv5 model.

Prerequisites

  • Python

Installation for YOLOv5 object detection

  1. Clone the repository
    !git clone https://github.com/ultralytics/yolov5.git
  2. Install required dependencies
    !pip install -r requirements.txt
  3. Run the YOLOv5 object detection model
    !python detect.py --weights bestpla.pt --source path/to/folder/orImage

Installation for YOLOv8 instance segmentation

  1. Install ultralytics
    !pip install ultralytics
  2. Install required dependencies
    !pip install -r requirements.txt
  3. Run the YOLOv5 object detection model
    !yolo predict model='runs/segment/yolov8n-seg/weights/best.pt' source='detection source file' name='folder_name'

🎯 Usage

This project serves to detect underwater garbage, including items like plastic bags. It can contribute to ocean cleanup efforts and environmental monitoring. To run the project, consider Google Colab.

📊 Output

The images above depict the output of our underwater trash plastic detection models. The model successfully identifies and outlines plastic waste items, such as plastic bags, cups, metal_can and cups, contributing to efforts to clean up our oceans.

Underwater waste detection image Underwater waste detection image Underwater waste detection image Underwater waste detection image Underwater waste detection image Underwater waste detection image

📜 License

Distributed under the MIT License. See LICENSE for more information.

🙏 Acknowledgments

Thanks to Ultralytics for their awesome framework!