app.py

import gradio as gr
from transformers import pipeline

pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")



def predict(image):
  predictions = pipeline(image)
  return {p["label"]: p["score"] for p in predictions}



gr.Interface(
    predict,
    inputs=gr.inputs.Image(label="Upload hot dog candidate", type="filepath"),
    outputs=gr.outputs.Label(num_top_classes=2),
    title = "<br>Hot dog or not?<br>",
    description = 'This is a demo of the hotdog-not-hotdog model by julien-c.<br><br>',
    css=".gradio-container {background-image: url('file=BG.png')}"
).launch()