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🌊 EcoBot – Underwater Plastic Waste Detection

License
EcoBot is an AI-powered web application for detecting and visualizing plastic waste in underwater environments. Built with YOLOv8, it enables real-time analysis of underwater images and helps raise awareness about ocean pollution. 🌱

Live Demo 🚀 | Report Issues 🛠️

📸 Screenshots

🌱 Home Page

Upload underwater images to detect plastic waste using our advanced detection system.
Home Page

🧪 Detection Results

View detailed detection results, including confidence scores, plastic level, and global impact.
Detection Results

🗺️ Global Plastic Map

Visualize plastic detection points around the globe.
Global Map

🚀 Features

✅ Detect plastic waste in underwater images using YOLOv8
✅ Summarize detections with confidence scores & plastic level
✅ Visualize detection locations on a global map (powered by Leaflet)
✅ Download processed images with annotations
✅ Responsive web UI for easy access on any device

🛠️ Tech Stack

  • Frontend: HTML, CSS, JavaScript (Tailwind CSS, React.js)
  • Backend: Python (FastAPI / Flask)
  • Deep Learning: YOLOv8 (Ultralytics)
  • Mapping: Leaflet.js, OpenStreetMap
  • Deployment: Docker, AWS EC2

📥 Installation

Clone the repository

git clone https://github.com/chetlasrijith/eco-bot.git
cd eco-bot

Install dependencies

pip install -r requirements.txt

Run the application

python app.py

Then open your browser and go to http://127.0.0.1:8000

🧑‍💻 How It Works

  1. Image Upload: Users upload underwater images via the web interface.
  2. Preprocessing: Images are resized and normalized.
  3. Detection: YOLOv8 model detects plastic objects and classifies them (e.g., bottles, bags).
  4. Visualization: Detected objects are highlighted and their coordinates mapped globally.
  5. Download Option: Users can download annotated images or view results on the global map.

🤝 Contributing

Contributions are welcome! Please follow these steps:

  1. Fork the repo
  2. Create your branch (git checkout -b feature/new-feature)
  3. Commit your changes (git commit -m 'Add new feature')
  4. Push to the branch (git push origin feature/new-feature)
  5. Open a Pull Request

📞 Contact

Created by Chetla Srijith For queries, raise an issue in the repository or connect on LinkedIn.