app.py

from fastai.vision.all import load_learner
import gradio as gr
from PIL import Image

# Define the missing function
def is_cat(x): 
    return x[0].isupper()

# Load the trained model
model = load_learner('model.pkl')

# Define a function to make predictions
def predict(image):
    pred, _, probs = model.predict(image)
    return f"Prediction: {pred} (Confidence: {probs.max():.2f})"

# Create the Gradio web interface
interface = gr.Interface(
    fn=predict,
    inputs=gr.inputs.Image(type="pil"),
    outputs="text",
    title="Cat vs Dog Classifier",
    description="Upload an image of a cat or dog and let the model classify it!"
)

# Launch the Gradio app
interface.launch()