Update app.py

app.py

@@ -299,6 +299,10 @@ if st.button("Check News"):
             st.success(f"✅ Result: This news is **REAL**. (Confidence: {confidence:.2f})")
 
 # ---- Deepfake Image Detection Section ----
+import streamlit as st
+import tempfile
+from PIL import Image
+
 st.subheader("📸 Deepfake Image Detection")
 uploaded_image = st.file_uploader("Upload an Image", type=["jpg", "png", "jpeg"])
 
@@ -306,16 +310,19 @@ if uploaded_image is not None:
     temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg")
     img = Image.open(uploaded_image).convert("RGB")
     img.save(temp_file.name, "JPEG")
-    st.image(temp_file.name, caption="🖼️ Uploaded Image", use_column_width=True)
+    
+    # 🛠️ FIX: use_container_width=True instead of use_column_width=True
+    st.image(temp_file.name, caption="🖼️ Uploaded Image", use_container_width=True)
     
     if st.button("Analyze Image"):
         st.write("🔍 Processing...")
+        
+        # Assuming detect_deepfake_image() is a function that returns a dictionary with "label" and "score"
         result = detect_deepfake_image(temp_file.name)
         
         if result["label"] == "REAL":
-          st.success(f"✅ Result: This image is Real. (Confidence: {1 - result['score']:.2f})")
-        else: 
-            
+            st.success(f"✅ Result: This image is Real. (Confidence: {1 - result['score']:.2f})")
+        else:
             st.error(f"⚠️ Result: This image is a Deepfake. (Confidence: {result['score']:.2f})")
 
 # # ---- Deepfake Video Detection Section ----