This project is a Flask web application that predicts the Iris flower class using a machine learning model. The web app provides a user-friendly interface for users to input sepal and petal measurements and get a prediction for the iris species.
- 🌺 User-friendly interface for predicting Iris flower class.
- 🌸 Utilizes a pre-trained machine learning model.
- 🌷 Built with Flask, scikit-learn, and HTML/CSS.
- Clone the repository:
git clone https://github.com/subdas374/IrisSage.git - Navigate to the project directory:
cd iris-flower-classification - Install dependencies:
pip install -r requirements.txt
- Run the Flask app:
python app.py - Open your web browser and go to:
http://localhost:5000 - Input the sepal and petal measurements and click "Predict" to get the predicted iris species.
Contributions are welcome! If you find any issues or want to improve the project, feel free to submit a pull request.
For questions or inquiries, please contact me.
This project is licensed under the MIT License.