| --- |
| license: mit |
| python-version: 3.11 |
| sdk: streamlit |
| emoji: 🚀 |
| colorFrom: indigo |
| colorTo: green |
| pinned: false |
| sdk_version: 1.39.0 |
| --- |
| |
|
|
| # 🌺 Iris Flower Classifier and Visualization App 🌺 |
|
|
| This Streamlit app helps you predict the species of an Iris flower 💐 based on its measurements! 📏 |
|
|
| ## Features ✨ |
|
|
| * **Easy to Use Interface:** Input flower measurements with simple sliders 🎚️. |
| * **Accurate Predictions:** Powered by a trained machine learning model 🧠 for reliable results. |
| * **Clear Results:** See the predicted species along with your input measurements 📊. |
|
|
| ## Demo App |
|
|
| - [Demo App](https://huggingface.co/spaces/danhtran8mind/streamlit-iris-inference-visualization) |
| - [GitHub Source code](https://github.com/danhtran8mind/iris-inference-visualization) |
|
|
| ## How to Run 🚀 |
|
|
| 1. **Install the Dependencies:** |
| ```bash |
| pip install -r reqiurments.txt |
| ``` |
|
|
| 2. **Start the App:** |
| ```bash |
| streamlit run app.py |
| ``` |
|
|
| ## Usage |
|
|
| 1. Open the app in your web browser 🌐. |
| 2. Adjust the sliders to enter the sepal and petal measurements. |
| 3. Click "Predict" to see the magic! 🪄 |
| 4. The predicted Iris species will be displayed. |
|
|
| ## Built With 🛠️ |
|
|
| * **Streamlit:** For building the interactive web app ✨. |
| * **Scikit-learn:** For training the machine learning model 🧠. |
| * **Pandas:** For handling the Iris dataset 📊. |
|
|
| ## Contributing 🤝 |
|
|
| Want to help improve the app? Feel free to open an issue or submit a pull request! 🎉 |
|
|
