This repository focuses on Mosquito Breeding Site Detection and Segmentation using various YOLO architectures. It includes trained models for object detection and segmentation, along with visualization tools for exploring the dataset and model outputs.
Mosquito-Breeding-Sites-Detection-and-Segmentation-Using-YOLO
│
├── breeding-place-detection
│ ├── YOLOv5s
│ ├── YOLOv8n
│ └── YOLOv9s
│
├── water-surface-segmentation
│ ├── YOLOv11s-SIG
│ └── YOLOv8x-SIG
│
├── Docs
│ └── Poster-of-Mosquito-Breeding-Sites-Detection-and-Water-Surface-Segmentation-Project.pdf
│
└── 01DataVisualization.ipynb
breeding-place-detection/ contains trained YOLO models (YOLOv5s, YOLOv8n, YOLOv9s) for mosquito breeding site detection.
water-surface-segmentation/ contains YOLO segmentation models (YOLOv11s-SIG, YOLOv8x-SIG) for water surface identification.
Docs/ holds the project poster and related documentation.
01DataVisualization.ipynb is a notebook for dataset visualization, exploratory analysis, and previewing detection or segmentation outputs.
- Detection of breeding sites using multiple YOLO architectures.
- Segmentation of water surfaces in breeding environments.
- Visual exploration of bounding boxes, masks, and dataset samples.
- YOLOv5s
- YOLOv8n
- YOLOv9s
- YOLOv11s-SIG
- YOLOv8x-SIG
- Clone the repository:
git clone https://github.com/<your-username>/Mosquito-Breeding-Sites-Detection-and-Segmentation-Using-YOLO.git
- Navigate to the directory:
cd Mosquito-Breeding-Sites-Detection-and-Segmentation-Using-YOLO
- Open the visualization notebook:
jupyter notebook 01DataVisualization.ipynb
- Detection results are inside each model folder under breeding-place-detection/.
- Segmentation outputs are stored under water-surface-segmentation/.
- The notebook provides visualization of model predictions and dataset inspection.
This repository is for research and educational purposes only. Please credit appropriately when using the work.
Assad Ullah Khan
Email: assadullahkhan556@gmail.com
LinkedIn: https://www.linkedin.com/in/assadullahkhan
Made by Assad Ullah Khan
Research Assistant at DIP Lab, Islamia College Peshawar