diff --git a/Specialization_Deep_Learning_deeplearning.ai/Course4_Convolutional Neural Networks/week3_Object detection/Autonomous+driving+application+-+Car+detection+-+v1.ipynb b/Specialization_Deep_Learning_deeplearning.ai/Course4_Convolutional Neural Networks/week3_Object detection/Autonomous+driving+application+-+Car+detection+-+v1.ipynb
index 2f979e4..44650c0 100644
--- a/Specialization_Deep_Learning_deeplearning.ai/Course4_Convolutional Neural Networks/week3_Object detection/Autonomous+driving+application+-+Car+detection+-+v1.ipynb	
+++ b/Specialization_Deep_Learning_deeplearning.ai/Course4_Convolutional Neural Networks/week3_Object detection/Autonomous+driving+application+-+Car+detection+-+v1.ipynb	
@@ -366,7 +366,9 @@
     "\n",
     "**Exercise**: Implement iou(). Some hints:\n",
     "- In this exercise only, we define a box using its two corners (upper left and lower right): (x1, y1, x2, y2) rather than the midpoint and height/width.\n",
-    "- To calculate the area of a rectangle you need to multiply its height (y2 - y1) by its width (x2 - x1)\n",
+    "- To calculate the 
+    
+    of a rectangle you need to multiply its height (y2 - y1) by its width (x2 - x1)\n",
     "- You'll also need to find the coordinates (xi1, yi1, xi2, yi2) of the intersection of two boxes. Remember that:\n",
     "    - xi1 = maximum of the x1 coordinates of the two boxes\n",
     "    - yi1 = maximum of the y1 coordinates of the two boxes\n",
@@ -400,7 +402,7 @@
     "    yi1 = np.maximum(box1[1],box2[1])\n",
     "    xi2 = np.minimum(box1[2],box2[2])\n",
     "    yi2 = np.minimum(box1[3],box2[3])\n",
-    "    inter_area = (yi1 - yi2)*(xi1 - xi2)\n",
+    "    inter_area=max(xi2-xi1,0)*max(yi2-yi1,0)",
     "    ### END CODE HERE ###    \n",
     "\n",
     "    # Calculate the Union area by using Formula: Union(A,B) = A + B - Inter(A,B)\n",