🌦️ ArabWeatherTask: Where Data Meets Weather Magic 🌦️

Welcome to ArabWeatherTask, a delightful journey into the world of data and weather! 🚀

Prject Overview:

ArabWeatherTask is more than just a project; it's an adventure in data science and meteorology. We've blended the power of Tabular and Image data to bring you insights into weather like never befor

How to Get Started:

1. Get the Code:

• Clone the repo to your local machine:

git clone https://github.com/Omaralsaabi/ArabWeatherTask.git

2. Set Up Your Environment:

• Enter the repo directory:

cd ArabWeatherTask

• Create a virtual environment:

python3 -m venv venv

• Activate the virtual environment:

source venv/bin/activate

• Install the requirements

pip install -r requirements.txt

Tabular Model

1. Explore the Data:

• Enter the data directory:

cd WeatherTabular

• Dive into the training notebook train.ipynb and the prediction notebook predict.ipynb.

Image Model

1. Visualize Weather:

• Enter the image directory:

cd WeatherCV

• Immerse yourself in the CNN training notebook CVWeather-CNN.ipynb and the ResNet training notebook CVWeather-ResNet-Finetuned.ipynb.
• Ready for some real magic? Run the server:

python3 manage.py runserver

• Open your browser and journey to http://localhost:8000/predict. Upload an image and let the weather predictions begin!

Docker Magic:

Want to make things even simpler? We've got you covered!

1. Dockerize Your Experience:

• Pull the docker image:

docker pull omaralsaabi/weathercv

• Launch the Docker container:

docker run -p 8000:8000 omaralsaabi/weathercv

• Explore weather insights at http://localhost:8000/predict.

For any questions, ideas, reach out to me at : prof.omaralsaabi@gmail.com.