app.py

import streamlit as st
import numpy as np
import cv2
import tempfile
import os

# ---- Page Configuration ----
st.set_page_config(page_title="Fake & Deepfake Detection", layout="wide")

st.title("📰 Fake News & Deepfake Detection Tool")
st.write("🚀 Detect Fake News, Deepfake Images, and Videos using AI")

# ---- Fake News Detection Section ----
st.subheader("📝 Fake News Detection")
news_input = st.text_area("Enter News Text:", "Type here...")

if st.button("Check News"):
    st.write("🔍 Processing...")
    # Fake news detection logic (Placeholder)
    st.success("✅ Result: This news is FAKE.")  # Replace with ML Model

# ---- Deepfake Image Detection Section ----
st.subheader("📸 Deepfake Image Detection")
uploaded_image = st.file_uploader("Upload an Image", type=["jpg", "png", "jpeg"])

if uploaded_image is not None:
    st.image(uploaded_image, caption="Uploaded Image", use_column_width=True)
    if st.button("Analyze Image"):
        st.write("🔍 Processing...")
        # Deepfake detection logic (Placeholder)
        st.error("⚠️ Result: This image is a Deepfake.")  # Replace with model

# ---- Deepfake Video Detection Section ----
st.subheader("🎥 Deepfake Video Detection")
uploaded_video = st.file_uploader("Upload a Video", type=["mp4", "avi", "mov"])

if uploaded_video is not None:
    st.video(uploaded_video)
    if st.button("Analyze Video"):
        st.write("🔍 Processing...")
        # Deepfake video detection logic (Placeholder)
        st.warning("⚠️ Result: This video contains Deepfake elements.")  # Replace with model

st.markdown("🔹 **Developed for Fake News & Deepfake Detection Hackathon**")