Update app.py

app.py

@@ -17,16 +17,15 @@ 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"])
 
-def compress_image(image, quality=30, max_size=(100, 100)):
+def compress_image(image, quality=25, max_size=(80, 80)):  # ⬇️ Reduce size further
     img = Image.open(image).convert("RGB")
-    img.thumbnail(max_size)  # Resize while keeping aspect ratio
+    img.thumbnail(max_size)  
     temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg")
     img.save(temp_file.name, "JPEG", quality=quality)
     return temp_file.name
@@ -36,7 +35,6 @@ if uploaded_image is not None:
     st.image(compressed_image_path, caption="🖼️ Compressed 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 ----
@@ -58,10 +56,10 @@ def compress_video(video):
 
     fourcc = cv2.VideoWriter_fourcc(*'mp4v')
 
-    # ✅ Reduce resolution to 480p
-    frame_width = 320  
-    frame_height = 140  
-    out = cv2.VideoWriter(temp_file.name, fourcc, 20.0, (frame_width, frame_height))
+    # ✅ Further Reduce Video Resolution
+    frame_width = 240  
+    frame_height = 100  
+    out = cv2.VideoWriter(temp_file.name, fourcc, 15.0, (frame_width, frame_height))  # ⬇️ Lower FPS to 15
 
     while cap.isOpened():
         ret, frame = cap.read()
@@ -81,7 +79,6 @@ if uploaded_video is not None:
         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**")