Android Studio

Warning

This Tutorial is outdated due to the TensorFlow updates for the VisionPortal. We are working on updating this tutorial, please bear with us as we update it. For more information on TensorFlow for Java, see the VisionPortal TensorFlow Processor Initialization.

It is assumed that you already know how to use Android Studio. If not, be sure to check out the Android Studio Guide document before proceeding.

In Android Studio, there are three sample Opmodes to choose from. Each has its own use case. Depending on your use case choose one (or more) of the following.
- ConceptTensorFlowObjectDetection
  - This opmode is designed to use the robot controller’s internal camera, if it has one, for the input for TFOD.
- ConceptTensorFlowObjectDetectionSwitchableCameras
  - This opmode is designed to be able to switch between two different webcams for the input for TFOD.
- ConceptTensorFlowObjectDetectionEasy
  - This opmode is designed to use an external webcam as its input for TFOD
We will now have to move the sample opmode from the samples folder to the teamcode folder. To do this we will first have to go to the project view on the right. Then we will need to navigate to
- FtcRobotController -> Java -> org.firstinspires.ftc.robotcontroller -> external.samples

It should look like this:

Select the opmode that you chose earlier and drag and drop it into the following folder:
- TeamCode -> Java -> org.firstinspires.ftc.teamcode

When prompted to refactor select “refactor”. In the image below I moved all three opmodes into my teamcode folder but that is not necessary. You only need one opmode.

You will then have to open the opmode that you moved and remove the @Disabled should be near the top of the code.
The next step is to add your model (.tflite) to your assets folder. You will find this folder in your project view on the left by going to:
- FtcRobotControler -> assets.

By left- clicking on the assets folder you go to the “Open In” sub menu from which you can choose your file explorer of choice. From there you need to copy your model (.tflite) into the assets folder that you have just opened.

You will now have to modify the name of the model that the opmode uses. To do this change the TFOD_MODEL_ASSET variable such that “FreightFrenzy_BCDM.tflite” is replaced with the name and fully qualified path for the file that you uploaded earlier. The fully qualified path to where the tflite models live can be seen in the example below:

private static final String TFOD_MODEL_ASSET = "/sdcard/FIRST/tflitemodels/myCustomFreightFrenzyModel.tflite";

Tip

On some older models of phones, the upload path may be different. On some phones, like the Motorola G2 phone, the model path should instead be set to private static final String TFOD_MODEL_ASSET = "/storage/emulated/0/FIRST/tflitemodels/myCustomFreightFrenzyModel.tflite";

Next we will have to acquire a Vuforia Key. There are detailed instructions in each of the opmodes on acquiring such a key.
After following these instructions replace the following string with your key:

“ -- YOUR NEW VUFORIA KEY GOES HERE --- “

(optional) You may find it necessary to adjust the zoom. By default it is set to 2.5 but feel free to adjust this to your needs. Note that this is digital zoom not optical zoom. This means that in essence you are simply telling TFOD to ignore outer sections of the image.
If you are using ConceptTensorFlowObjectDetectionWebcam or ConceptTensorFlowObjectDetectionSwitchableCameras you will also need to update the device name of the camera. Simply change the device name to correspond with your config. In the image below the name of the webcam is “Webcam 1”.

You will next have to update the labels. To do this find the section of code shown below. This should match the order of the labels in the dataset(s) that your model is based on. There should be at least one label.

And you are all set to test. Just open the opmode as you would any other opmode and select initialize and play.