app.py

import gradio as gr
from transformers import pipeline

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

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

# Set up the Gradio interface
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?"
)

# Launch the Gradio app with public link
if __name__ == "__main__":
    gradio_app.launch(share=True)