diff --git a/Artificial Intelligence/Basic/Object_Detection/ObjectDetection_for_images.ipynb b/Artificial Intelligence/Basic/Object_Detection/ObjectDetection_for_images.ipynb
index 1f0aabae0..c65c47c6b 100644
--- a/Artificial Intelligence/Basic/Object_Detection/ObjectDetection_for_images.ipynb	
+++ b/Artificial Intelligence/Basic/Object_Detection/ObjectDetection_for_images.ipynb	
@@ -231,10 +231,25 @@
     }
    ],
    "source": [
-    "font_scale = 3\n",
+    "# Initialize font scale and font",
+    "font_scale = 1\n",
     "font = cv2.FONT_HERSHEY_PLAIN\n",
-    "for ClassInd,conf,boxes in zip(ClassIndex.flatten(),confidence.flatten(),bbox):\n",
-    "    cv2.rectangle(img,boxes,(255,0,0),2)\n",
+    "# Loop over detections and draw bounding boxes\n"
+    "for ClassInd, conf, boxes in zip(ClassIndex.flatten(), confidence.flatten(), bbox):\n",
+    "    # Get class label and confidence score ",
+    "class_label = classLabels[ClassInd - 1]",
+    "confidence_score = conf * 100",
+    "    # Draw bounding box",
+   " color = (0, 255, 0)  # Green color for all boxes",
+   " cv2.rectangle(img, boxes, color, 2)",
+"    # Draw class label and confidence score",
+   " cv2.putText(img, f'{class_label}: {confidence_score:.2f}%', (boxes[0] + 10, boxes[1] + 20)",
+                font, fontScale=font_scale, color=(0, 255, 0), thickness=2)
+
+# Display the final image with detections
+plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
+plt.axis('off')  # Turn off axis
+plt.show()\n",
     "    cv2.putText(img,classLabels[ClassInd - 1],(boxes[0] + 10,boxes[1] + 40),font,fontScale = font_scale,color = (0,255,0),thickness = 3)\n",
     "    print(classLabels[ClassInd - 1] + \" : \" + str(conf * 100) + \"%\")"
    ]