| ## Overview | |
| # Precision Aquaculture: An Integrated Computer Vision and IoT Approach for Optimized Tilapia Feeding | |
| This repository contains a YOLOv8-based model for precise Tilapia feeding in aquaculture, combining computer vision and IoT technologies. Our system uses real-time IoT sensors to monitor water quality and computer vision to analyze fish size and count, determining optimal feed amounts. We achieved 94% precision in keypoint detection on a dataset of 3,500 annotated Tilapia images, enabling accurate weight estimation from fish length. The system includes a mobile app for remote monitoring and control. Our approach significantly improves aquaculture efficiency, with preliminary estimates suggesting a potential increase in production of up to 58 times compared to traditional farming methods. This repository includes our trained models, code, and a curated open-source dataset of annotated Tilapia images. | |
| [Rest of the README content remains the same] | |
| ## How to use | |
| Please download the model weights first | |
| [Counting Model](https://huggingface.co/Raniahossam33/Fish-Counting/blob/main/Fish-Counting-yolov8.pt) | |
| [Keypoint Detection Model](https://huggingface.co/Raniahossam33/Fish-Counting/blob/main/KeyPoint-Detction-Yolov8.pt) | |
| [Paper](https://arxiv.org/abs/2409.08695) | |
| ```python | |
| from ultralytics import YOLO | |
| from PIL import Image | |
| img = Image.open('<image-path>') | |
| model = YOLO('<weights-path>') | |
| results = model(img) | |
| ``` | |
| ## Results | |
| <p align="center"> | |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/6402324afa1acad60064c742/mEDhKQRfaTZbZnYwUDZLD.png" width="800" ></img> | |
| </p> | |
| <p align="center"> | |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/6402324afa1acad60064c742/6ZRl0O7T6P67usVdMFlpo.png" width="900" ></img> | |
| </p> | |
| ## Applications | |
| This fish counting model can be useful in various scenarios, including: | |
| - Monitoring fish populations in aquariums or fish farms | |
| - Ecological studies in natural water bodies | |
| - Automated fish stock assessment | |
| ## Citation | |
| If you use this model in your research, please cite: | |
| ```bibtex | |
| @article{hossam2024precision, | |
| title={Precision Aquaculture: An Integrated Computer Vision and IoT Approach for Optimized Tilapia Feeding}, | |
| author={Hossam, Rania and Heakl, Ahmed and Gomaa, Walid}, | |
| journal={arXiv preprint arXiv:2409.08695}, | |
| year={2024}, | |
| doi={10.48550/arXiv.2409.08695} | |
| } | |
| ``` | |