Update README.md

README.md

@@ -8,4 +8,59 @@ pinned: false
 license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Iris Flower Detection Web Application
+
+This is a simple Flask web application that uses a machine learning model to predict the species of iris flowers based on measurements.
+
+## Files and Structure
+
+- `app.py` - The main Flask application
+- `iris_model.pkl` / `new_iris_model.pkl` - The trained machine learning model
+- `templates/` - Folder containing HTML templates
+  - `form.html` - Input form for flower measurements
+  - `result.html` - Page showing prediction results
+- `create_new_model.py` - Script to create a fresh model if needed
+- `test_app.py` - Script to test the application functionality
+- `run_app.bat` - Windows batch file to easily run the application
+
+## How to Run
+
+1. Double-click on `run_app.bat` or run `python app.py` in your terminal
+2. Open your web browser and go to http://127.0.0.1:5000
+3. Enter the flower measurements and click "Predict Flower Species"
+
+## Sample Measurements
+
+### Iris Setosa
+
+- Sepal Length: 5.1 cm
+- Sepal Width: 3.5 cm
+- Petal Length: 1.4 cm
+- Petal Width: 0.2 cm
+
+### Iris Versicolor
+
+- Sepal Length: 6.0 cm
+- Sepal Width: 2.7 cm
+- Petal Length: 4.2 cm
+- Petal Width: 1.3 cm
+
+### Iris Virginica
+
+- Sepal Length: 6.8 cm
+- Sepal Width: 3.0 cm
+- Petal Length: 5.5 cm
+- Petal Width: 2.1 cm
+
+## Troubleshooting
+
+If you encounter issues:
+
+1. Run `python test_app.py` to verify the model is working correctly
+2. Check that you have all the required Python packages installed:
+   - Flask
+   - scikit-learn
+   - joblib
+   - numpy
+3. Try generating a new model with `python create_new_model.py`
+