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Updated Using a TensorFlow Pretrained Model to Detect Everyday Objects (markdown)

FTC Engineering
2020-10-29 21:08:13 -04:00
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Using-a-TensorFlow-Pretrained-Model-to-Detect-Everyday-Objects.md

@ -217,6 +217,14 @@ The op mode will also display label information on the driver station (using tel
<p align="center">[[/images/Using-a-TensorFlow-Pretrained-Model-to-Detect-Everyday-Objects/tfodDS.png]]<br/>The op mode will display label information for recognized objects on the driver station using telemetry.<p>
### 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.
<p align="center">[[/images/Using-a-TensorFlow-Pretrained-Model-to-Detect-Everyday-Objects/makeListFromText.png]]<br/>A Blocks programmer would have to manually enter in the label values using the makeListFromText block.<p>
### Example Source Code
The example op mode (except for the Vuforia license key) is included below for reference:
```
/* Copyright (c) 2019 FIRST. All rights reserved.