Update app.py

app.py

@@ -178,22 +178,32 @@ uploaded_video = st.file_uploader("Upload a Video", type=["mp4", "avi", "mov"])
 def detect_deepfake_video(video_path):
     cap = cv2.VideoCapture(video_path)
     frame_scores = []
+    frame_count = 0
     
     while cap.isOpened():
         ret, frame = cap.read()
         if not ret:
             break
         
-        frame_path = "temp_frame.jpg"
-        cv2.imwrite(frame_path, frame)
-        result = detect_deepfake_image(frame_path)
-        frame_scores.append(result["score"])
-        os.remove(frame_path)
+        if frame_count % 10 == 0:  # ہر 10ویں فریم کا تجزیہ کریں
+            frame_path = "temp_frame.jpg"
+            cv2.imwrite(frame_path, frame)
+            result = detect_deepfake_image(frame_path)
+            frame_scores.append(result["score"])
+            os.remove(frame_path)
+        
+        frame_count += 1
     
     cap.release()
+    
+    if not frame_scores:
+        return {"label": "UNKNOWN", "score": 0.0}  # اگر کوئی فریم پراسیس نہ ہو سکے
+    
     avg_score = np.mean(frame_scores)
+    confidence = round(float(avg_score), 2)
     final_label = "FAKE" if avg_score > 0.5 else "REAL"
-    return {"label": final_label, "score": round(float(avg_score), 2)}
+    
+    return {"label": final_label, "score": confidence}
 
 if uploaded_video is not None:
     st.video(uploaded_video)
@@ -202,12 +212,14 @@ if uploaded_video is not None:
         f.write(uploaded_video.read())
     
     if st.button("Analyze Video"):
-        st.write("🔍 Processing...")
+        st.write("🔍 Processing... Please wait.")
         result = detect_deepfake_video(temp_file.name)
         
         if result["label"] == "FAKE":
-            st.warning(f"⚠️ Result: This video contains Deepfake elements. (Confidence: {result['score']:.2f})")
+            st.error(f"⚠️ Deepfake Detected! This video appears to be FAKE. (Confidence: {result['score']:.2f})")
+        elif result["label"] == "REAL":
+            st.success(f"✅ This video appears to be REAL. (Confidence: {1 - result['score']:.2f})")
         else:
-            st.success(f"✅ Result: This video is Real. (Confidence: {1 - result['score']:.2f})")
+            st.warning("⚠️ Unable to analyze the video. Please try a different file.")
 
 st.markdown("🔹 **Developed for Fake News & Deepfake Detection Hackathon**")