app.py

import streamlit as st
from PIL import Image
import requests
from transformers import pipeline

# Load the pipeline
model_name = "vm24bho/net_dfm_myimg"
pipe = pipeline('image-classification', model=model_name)

st.title("Deepfake vs Real Image Detection")

uploaded_file = st.file_uploader("Choose an image...", type="jpg")
if uploaded_file is not None:
    image = Image.open(uploaded_file)
    st.image(image, caption='Uploaded Image.', use_column_width=True)
    st.write("")
    st.write("Classifying...")

    # Apply the model
    result = pipe(image)

    # Display the result
    st.write("Classification Result:")
    st.write("---------------")

    for i, res in enumerate(result):
        label = res["label"]
        score = res["score"]
        st.write(f"**{i+1}. {label}**: {score:.2f}%")

    st.write("---------------")