diff --git a/object_detection/yolo5saveobjects.py b/object_detection/yolo5saveobjects.py
index 753526d..9dd2c43 100755
--- a/object_detection/yolo5saveobjects.py
+++ b/object_detection/yolo5saveobjects.py
@@ -94,7 +94,7 @@ def generate_frames():
         detections = results.pandas().xyxy[0]  # Convert detections to Pandas DataFrame
 
         if detections.empty:
-            print("🚫 No objects detected.")
+            print("No objects detected.")
         else:
             print(f"✅ Detected {len(detections)} objects!")
 
@@ -111,7 +111,7 @@ def generate_frames():
                     cv2.putText(frame, f"{label} ({confidence:.2f})", (x1, y1 - 10),
                                 cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
 
-        # Encode and yield the frame as JPEG
+        # Encode and present the frame as JPEG
         _, buffer = cv2.imencode('.jpg', frame)
         yield (b'--frame\r\n'
                b'Content-Type: image/jpeg\r\n\r\n' + buffer.tobytes() + b'\r\n')
@@ -123,6 +123,6 @@ def video_feed():
     return Response(generate_frames(), mimetype='multipart/x-mixed-replace; boundary=frame')
 
 if __name__ == '__main__':
-    print("🚀 Server running at http://localhost:5000/video")
+    print("Running at http://localhost:5000/video")
     app.run(host='0.0.0.0', port=5000, debug=True, threaded=True)
 
diff --git a/object_detection/yolo5showobjects.py b/object_detection/yolo5showobjects.py
index af383d3..2787488 100755
--- a/object_detection/yolo5showobjects.py
+++ b/object_detection/yolo5showobjects.py
@@ -10,18 +10,18 @@ import numpy as np
 import warnings
 
 
-warnings.simplefilter("ignore", category=FutureWarning)
+warnings.simplefilter("ignore", category=FutureWarning)  #ignore torch warnings
 
 app = Flask(__name__)
 
-YOUTUBE_URL = "https://www.youtube.com/watch?v=i3w7qZVSAsY"  # Stream URL
+YOUTUBE_URL = "https://www.youtube.com/watch?v=i3w7qZVSAsY"  # Stream URL example
 CONFIDENCE_THRESHOLD = 0.25  # Confidence threshold for object detection
 MODEL = "yolov5s"  # YOLO model version (yolov5s, yolov5m, etc.)
 
-# Load YOLOv5 model
-print("🔄 Loading YOLOv5 model...")
+# Load YOLO5 model
+print("Loading YOLOv5 model...")
 model = torch.hub.load("ultralytics/yolov5", "custom", path=MODEL, force_reload=True)
-print("✅ YOLOv5 loaded successfully!")
+print("YOLOv5 loaded successfully!")
 
 def get_stream_url():
     """Fetch fresh 720p YouTube stream URL using yt-dlp."""
@@ -57,7 +57,7 @@ def generate_frames():
         detections = results.pandas().xyxy[0]  # Convert detections to Pandas DataFrame
 
         if detections.empty:
-            print("🚫 No objects detected in this frame.")
+            print("No objects detected in this frame.")
         else:
             print(f"✅ Detected {len(detections)} objects!")
             print(detections[["name", "confidence"]])  # Print detected object names and confidence
@@ -85,6 +85,6 @@ def video_feed():
     return Response(generate_frames(), mimetype='multipart/x-mixed-replace; boundary=frame')
 
 if __name__ == '__main__':
-    print("🚀 Server running at http://localhost:5000/video")
+    print("Running at http://localhost:5000/video")
     app.run(host='0.0.0.0', port=5000, debug=True, threaded=True)