🦟 Mosquito Breeding Sites Detection and Segmentation Using YOLO Architectures

📘 Project Overview

This repository focuses on Mosquito Breeding Site Detection and Segmentation using different YOLO architectures.
It includes models for object detection and segmentation, along with data visualization and result analysis.

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📂 Repository Structure

Mosquito Breeding Sites Detection and Segmentation Using YOLO Architectures
│
├── Models_Trained
│   ├── breeding-place-detection
│   │   ├── YOLOv5s
│   │   ├── YOLOv8n
│   │   └── YOLOv9s
│   │
│   └── water-surface-segmentation
│       ├── Segmentation Model YOLOv11s SIG
│       └── Segmentation Model YOLOv8x SIG
│
├── Docs
│   └── Poster-of-Mosquito-Breeding-Sites-Detection-and-Water-Surface-Segmentation-Project.pdf
│
└── 01DataVisualization.ipynb

📁 Folder Descriptions

• Models_Trained/
  • breeding-place-detection/ → YOLO models for detecting mosquito breeding sites.
  • water-surface-segmentation/ → YOLO segmentation models for identifying water surfaces.
• Docs/ → Contains the project poster and documentation.
• 01DataVisualization.ipynb → Jupyter Notebook for visualizing dataset samples and model outputs.

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🚀 Key Features

• Detect mosquito breeding sites using multiple YOLO detection architectures.
• Segment water surfaces in mosquito breeding areas using YOLO-based segmentation models.
• Visualize dataset and model outputs using a Jupyter Notebook.

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🧠 YOLO Architectures Used

Detection

• YOLOv5s: Lightweight detection model, optimized for speed.
• YOLOv8n: Improved YOLO version with better detection performance.
• YOLOv9s: Advanced detection model with higher accuracy.

Segmentation

• YOLOv11s SIG: Segmentation model for extracting water surfaces.
• YOLOv8x SIG: Extended segmentation model for precise mask outputs.

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⚙️ Getting Started

1. 🔽 Clone the repository

git clone https://github.com/<your-username>/Mosquito-Breeding-Sites-Detection-and-Segmentation-Using-YOLO-Architectures.git

2. 📂 Navigate to the repository folder

cd Mosquito-Breeding-Sites-Detection-and-Segmentation-Using-YOLO-Architectures

3. 📒 Open the Jupyter Notebook

jupyter notebook 01DataVisualization.ipynb

4. 🔍 Explore detection and segmentation results in their respective folders.

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📊 Results Overview

• Detection outputs are stored inside each YOLO detection model folder under breeding-place-detection.
• Segmentation outputs are stored inside each YOLO segmentation model folder under water-surface-segmentation.
• The notebook 01DataVisualization.ipynb allows visualization of images, bounding boxes, and segmentation masks.

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🧾 License

This repository is intended for educational and research purposes only.
Please give proper credit if used in publications or related projects.

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💬 Contact

Assad Ullah Khan
📧 Email: [email protected]
🔗 LinkedIn: www.linkedin.com/in/assadullahkhan

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Made by Assad Ullah Khan
Research Assistant at DIP lab Islamia College Peshawar