diff --git a/Using-a-TensorFlow-Pretrained-Model-to-Detect-Everyday-Objects.md b/Using-a-TensorFlow-Pretrained-Model-to-Detect-Everyday-Objects.md index ea4e474..86d2536 100644 --- a/Using-a-TensorFlow-Pretrained-Model-to-Detect-Everyday-Objects.md +++ b/Using-a-TensorFlow-Pretrained-Model-to-Detect-Everyday-Objects.md @@ -220,7 +220,7 @@ The op mode will also display label information on the driver station (using tel ### Using Android Studio or the Blocks Development Tool You can also use Android Studio to build and deploy this example op mode if you prefer. The same op mode you would use for OnBot Java can be built using Android Studio. -Note that it is also possible to use this mobilenet .tflite model to detect common objects using a Blocks op mode. The one limitation of the Blocks development tool is that it does not currently have support for reading in the labels from the label map file. Instead, a blocks programmer would have to specify the labels in a list using the "makeListFromText" programming block. +Note that it is also possible to use this mobilenet .tflite model to detect common objects using a Blocks op mode. The one limitation of the Blocks development tool is that it does not currently have support for reading in the labels from the label map file. Instead, a Blocks programmer would have to specify the labels in a list using the "makeListFromText" programming block.

[[/images/Using-a-TensorFlow-Pretrained-Model-to-Detect-Everyday-Objects/makeListFromText.png]]
A Blocks programmer would have to manually enter in the label values using the makeListFromText block.