app.py

import streamlit as st # type: ignore
import numpy as np # type: ignore
from tensorflow.keras.models import load_model # type: ignore
from PIL import Image # type: ignore

import os
os.system("pip install tensorflow")

from tensorflow.keras.models import load_model  # type: ignore # Now TensorFlow is installed before importing

# Model Load
model = load_model("xception_deepfake_image.h5")

# Title
st.title("DeepFake Image Detector")

# Upload Image
uploaded_file = st.file_uploader("Upload an image...", type=["jpg", "png", "jpeg"])

if uploaded_file is not None:
    image = Image.open(uploaded_file)
    st.image(image, caption="Uploaded Image", use_column_width=True)
    
    # Preprocessing
    image = image.resize((256, 256))
    image = np.array(image) / 255.0
    image = np.expand_dims(image, axis=0)

    # Prediction
    prediction = model.predict(image)
    result = "FAKE" if prediction > 0.5 else "REAL"
    
    st.write(f"**Prediction:** {result}")