Update app.py

app.py

@@ -3,6 +3,7 @@ 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")
@@ -23,8 +24,16 @@ if st.button("Check News"):
 st.subheader("📸 Deepfake Image Detection")
 uploaded_image = st.file_uploader("Upload an Image", type=["jpg", "png", "jpeg"])
 
+def compress_image(image, quality=30, max_size=(500, 500)):
+    img = Image.open(image).convert("RGB")
+    img.thumbnail(max_size)  # Resize while keeping aspect ratio
+    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:
-    st.image(uploaded_image, caption="Uploaded Image", use_column_width=True)
+    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...")
         # Deepfake detection logic (Placeholder)
@@ -34,11 +43,45 @@ if uploaded_image is not None:
 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')
+
+    # ✅ Reduce resolution to 480p
+    frame_width = 640  
+    frame_height = 480  
+    out = cv2.VideoWriter(temp_file.name, fourcc, 20.0, (frame_width, frame_height))
+
+    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:
-    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
+    compressed_video_path = compress_video(uploaded_video)
+    if compressed_video_path:
+        st.video(compressed_video_path)
+        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**")