diff --git a/Blocks-Sample-TensorFlow-Object-Detection-Op-Mode.md b/Blocks-Sample-TensorFlow-Object-Detection-Op-Mode.md
index 786dd8c..3069e5d 100644
--- a/Blocks-Sample-TensorFlow-Object-Detection-Op-Mode.md
+++ b/Blocks-Sample-TensorFlow-Object-Detection-Op-Mode.md
@@ -73,7 +73,7 @@ Note that in this example, since the op mode iterates through the list of recogn
 
 Save the op mode and re-run it.  The op mode should display the target zone based on the label of the last recognized object in its list of recognized objects.  Note that if you test this op mode with multiple ring stacks, the order of the detected objects can change with each iteration of your op mode.
 
-<p align="center">[[/images/Blocks-Sample-TensorFlow-Object-Detection-Op-Mode/modifiedBlocksExample.png]]<br/>The modified op mode should indicate target zone based on label of last recognized object in its list.<p> 
+<p align="center">[[/images/Blocks-Sample-TensorFlow-Object-Detection-Op-Mode/modifiedBlocksExample.png]]<br/>The modified op mode should indicate target zone based on the label of last recognized object in its list.<p> 
 ### Important Note Regarding Image Orientation
 The system interprets images based on the phone's orientation (Portrait or Landscape) at the time that the TensorFlow object detector was created and initialized. In our example, if you execute the TensorFlowObjectDetection.initialize block while the phone is in Portrait mode, then the images will be processed in Portrait mode.