app.py

import gradio as gr
from transformers import pipeline

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

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

gradio_app = gr.Interface(
    fn=predict,
    inputs=gr.Image(label="Select Hot Dog Candidate", sources=['upload','webcam'],type="pil"),  
    outputs=[gr.Image(label="Processed Image"), gr.Label(label="Result",num_top_classes=2)],  
    title="Hot Dog? Or Not?"
)

if __name__=="__main__":
  gradio_app.launch()