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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}")
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