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Updated Blocks Sample TensorFlow Object Detection Op Mode (markdown)

FTC Engineering
2020-10-20 14:34:33 -04:00
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Blocks-Sample-TensorFlow-Object-Detection-Op-Mode.md

@ -15,15 +15,15 @@ Your new Op Mode should appear in the editing pane of the Blocks Development Too
### Initializing the System
Let's take a look at the initial blocks in the Op Mode. The first block in the op mode (excluding the comment blocks) initializes the Vuforia library on the Android Robot Controller. This is needed because the TensorFlow Lite library will receive image data from the Vuforia library. In this example, the enableCameraMonitoring option is set to false. This means that there will not be a Vuforia preview window on the Robot Controller screen. Also, in the screenshot below, the Vuforia system will use an externally connected webcam named "Webcam 1" (which should match the camera name in your robot's configuration file).
Note that you can initialize both the Vuforia and the TensorFlow libraries in the same op mode. This is useful, for example, if you would like to use the TensorFlow library to determine the ring stack and then use the Vuforia library to help the robot autonomously navigate on the game field to navigate to the appropriate target zone from its starting position.
<p align="center">[[/images/Blocks-Sample-TensorFlow-Object-Detection-Op-Mode/blocksInit.png]]<br/>Initialize the Vuforia and TensorFlow libraries.<p>
The Op Mode then initializes the TensorFlow library and it enables a camera monitoring window so that the user can see on the Robot Controller activity an image with TensorFlow data (including bounding boxes for detected objects) overlayed.
Note that you can initialize both the Vuforia and the TensorFlow libraries in the same op mode. This is useful, for example, if you would like to use the TensorFlow library to determine the ring stack and then use the Vuforia library to help the robot autonomously navigate on the game field to navigate to the appropriate target zone from its starting position.
Also note that this sample Op Mode disables the camera monitoring window on the Robot Controller. If you are using a REV Robotics Control Hub as your Robot Controller (which lacks a touch screen) you normally want to disable the camera monitoring window and use the Camera Stream function instead (described later on in this tutorial) to view the output of the webcam.
Note that in this example the ObjectTracker parameter is set to true for this block, so an _object tracker_ will be used, in addition to the TensorFlow interpreter, to keep track of the locations of detected objects. The object tracker _interpolates_ object recognitions so that results are smoother than they would be if the system were to solely rely on the TensorFlow interpreter.
Also note that the Confidence level is set to 40%. This means that the TensorFlow library needs to have a confidence level of 40% or higher in order to consider an object as being detected in its field of view. You can adjust this parameter to a higher value if you would like the system to be more selective in identifying an object.
Also note that the Minimum Confidence level is set to 70%. This means that the TensorFlow library needs to have a confidence level of 70% or higher in order to consider an object as being detected in its field of view. You can adjust this parameter to a higher value if you would like the system to be more selective in identifying an object.
If a camera monitor window is enabled for the TensorFlow library, then the confidence level for a detected target will be displayed near the bounding box of the identified object (when the object tracker is enabled). For example, a value of "0.92" indicates a 92% confidence that the object has been identified correctly.