AI Rip Current Checker is a Python-based project that uses computer vision and deep learning (3D CNN) to analyse short beach videos and automatically detect the presence of rip currents.
Rip currents are powerful, narrow channels of fast-moving water flowing away from the shore and are a major cause of drowning incidents worldwide. This project aims to assist beach safety, research, and early warning systems by providing an AI-driven detection tool.
- 🧠 3D CNN Deep Learning Model – captures both spatial and temporal motion patterns
- 🎥 Video-based Analysis – works on short beach video clips (e.g. 5 seconds)
- ⚡ Fast Inference Pipeline – lightweight and efficient
- 🔌 Easy Integration – simple Python interface, extendable for Streamlit / web apps
- 🏖️ Designed for Coastal Safety Applications
AI-Rip-Current-Checker/ │ ├── app.py # Main application script ├── requirements.txt # Python dependencies ├── README.md # Project documentation └── models/ # (Optional) Trained model weights
- Clone the repository
git clone https://github.com/CreativeMotion26/AI-Rip-Current-Checker.git
cd AI-Rip-Current-Checker
python -m venv venv
source venv/bin/activate # Mac / Linux
venv\Scripts\activate # WindowsThis project uses a 3D Convolutional Neural Network (3D CNN) to learn:
Spatial features – wave patterns, foam, colour variation
Temporal features – water movement and flow direction over time
Unlike traditional image-only models, the 3D CNN processes sequences of frames, making it ideal for detecting dynamic ocean patterns such as rip currents.