app.py

# Import the necessary libraries
from fastai.vision.all import *
import gradio as gr

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

# Get the labels from the model's dataloader
labels = learn.dls.vocab

# Function to classify an image using the model
def classify_image(img):
    pred,pred_idx,probs = learn.predict(img)
    return dict(zip(labels, probs))


# Create the Gradio interface
image_input = gr.components.Image()
label_output = gr.components.Label()

examples = [f"assets/{fn}" for fn in ["bergen.jpg", "oslo.jpg", "newyork.jpg"]]

iface = gr.Interface(
    fn=classify_image, 
    inputs=image_input, 
    outputs=label_output, 
    examples=examples
    )

iface.launch(inline=False)