from model import model
import gradio as gr
import numpy as np

def classify_image(image):
    probabilities = model.predict(image.name)  # Call prediction function
    labels = ["Category1", "Category2", "Category3", "Category4"]  # Assing labels
    top_labels = [labels[i] for i in np.argsort(probabilities)[::-1][:4]]
    top_probs = [round(float(probabilities[i]), 4) for i in np.argsort(probabilities)[::-1][:4]]

demo = gr.Interface(
    fn=classify_image,
    inputs=gr.inputs.Image(),
    outputs=gr.outputs.Label(num_top_classes=4),
    title="Image Classifier",
    description="Upload an image and get the top 4 predicted labels with probabilities.",)
demo.launch()