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")

#pipeline = pipeline("image-classification", model="dima806/facial_emotions_image_detection")




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

gr.Interface(
    predict,
    inputs = gr.Image(),
   # inputs = gr.Image(label="Upload Any room photo", type = "filepath"),
    outputs = gr.Label(num_top_classes=5),
    title="Show your face ?",
).launch(share="True")

#inputs = gr.Image(sources=["webcam"], streaming=True),
#sources=["upload", "webcam", "clipboard"]