Create app.py

app.py

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+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**")