To integrate a .h5 (Keras) model into your Flutter app, you’ll need to expose the model’s functionality through a backend service—since Flutter (written in Dart) cannot directly run Python code or load .h5 files.

Create a Python Backend Use a Python web framework like Flask or Django to:

• Load your .h5 model using TensorFlow or Keras.

• Set up REST API endpoints that accept input data (e.g., JSON).

• Run the model prediction and return the output

Run this Flask app locally for testing or deploy it to a cloud service like Heroku, AWS, or Render for production. In your Flutter app, use http package to send data to the Python API and receive the prediction.