app.py

# Use a pipeline as a high-level helper
import gradio as gr
from transformers import pipeline


pipe = 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(
    predict,
    inputs = gr.Image(label="select hot dot candiadate", 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()