import gradio as gr
import numpy as np

# Load a pre-trained image classification model
learn = load_learner('models/model.pth')

# Function to make predictions from an image
def classify_image(image):
    # Make a prediction
    # Decode the prediction and get the class name
    name = learn.predict(image)
    return name[0]

# Sample images for user to choose from
sample_images = ["AcuraTLType-S2008.jpg", "AudiR8Coupe2012.jpg", "DodgeMagnumWagon2008.jpg"]

iface = gr.Interface(
    fn=classify_image,
    inputs=gr.Image(label="Select an image", type="filepath"),
    outputs="text",
    live=True,
    title="Car image classifier",
    description="Upload a car image or select one of the examples below"
    examples=sample_images
)


iface.launch()