app.py

## https://medium.com/@sa.pieri.98/build-your-first-hugging-face-space-with-gradio-a-beginners-guide-14bc42d66887

import gradio as gr
from transformers import pipeline

#pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
#pipeline = pipeline(task="image-classification", model="hg2001/autotrain-animals-vs-humans2-37846100283")
pipeline = pipeline("image-classification", model="lazyturtl/roomclassifier")


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

gr.Interface(
    predict,
    inputs = gr.Image(label="Upload hot dog candidate", type = "filepath"),
    outputs = gr.Label(num_top_classes=5),
    title="hot Dog? or Not ?",
).launch()