app.py

import streamlit as st
import numpy as np
import cv2
import tempfile
import os
from PIL import Image

# ---- 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...")
    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"])

def compress_image(image, quality=50, max_size=(100, 100)):  # ✅ Better quality & small size
    img = Image.open(image).convert("RGB")
    img.thumbnail(max_size)  
    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg")
    img.save(temp_file.name, "JPEG", quality=quality)
    return temp_file.name

if uploaded_image is not None:
    compressed_image_path = compress_image(uploaded_image)
    st.image(compressed_image_path, caption="🖼️ Compressed Image", use_column_width=True)
    if st.button("Analyze Image"):
        st.write("🔍 Processing...")
        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"])

def compress_video(video):
    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")

    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as temp_video:
        temp_video.write(video.read())
        video_path = temp_video.name

    cap = cv2.VideoCapture(video_path)
    
    if not cap.isOpened():
        st.error("❌ Error: Unable to read video!")
        return None

    fourcc = cv2.VideoWriter_fourcc(*'mp4v')

    # ✅ Further Reduce Video Resolution
    frame_width = 200  
    frame_height = 120  
    out = cv2.VideoWriter(temp_file.name, fourcc, 12.0, (frame_width, frame_height))  # ✅ Lower FPS to 12

    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            break
        frame = cv2.resize(frame, (frame_width, frame_height))
        out.write(frame)

    cap.release()
    out.release()
    
    return temp_file.name

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

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