app.py

import gradio as gr
from transformers import pipeline

classifier = pipeline(
    "image-classification",
    model="google/vit-base-patch16-224"
)

def classify_image(image):
    results = classifier(image)

    output = ""
    for item in results[:5]:
        output += f"{item['label']} : {item['score']:.2%}\n"

    return output

demo = gr.Interface(
    fn=classify_image,
    inputs=gr.Image(type="pil"),
    outputs=gr.Textbox(label="Classification Results"),
    title="Image Classification App",
    description="Upload an image and let AI identify what it contains."
)

demo.launch()