app.py

import gradio as gr
from transformers import pipeline

# Wybierz lżejszy model
model_name = "facebook/deit-tiny-patch16-224"

pipe = pipeline("image-classification", model=model_name)

def classify_image(img):
    results = pipe(img)
    return {res["label"]: float(res["score"]) for res in results}

demo = gr.Interface(
    fn=classify_image,
    inputs=gr.Image(type="filepath"),
    outputs=gr.Label(num_top_classes=5),
    title="Lekka klasyfikacja obrazów",
    description=f"Model: {model_name}"
)

demo.launch()