From ce64010dba763aed964bafd8827fdb3d673ed13f Mon Sep 17 00:00:00 2001 From: FTC Engineering Date: Wed, 21 Oct 2020 18:12:50 -0400 Subject: [PATCH] Updated Using TensorFlow Lite for the Ultimate Goal Challenge (markdown) --- Using-TensorFlow-Lite-for-the-Ultimate-Goal-Challenge.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/Using-TensorFlow-Lite-for-the-Ultimate-Goal-Challenge.md b/Using-TensorFlow-Lite-for-the-Ultimate-Goal-Challenge.md index f3d1cee..a3df4c3 100644 --- a/Using-TensorFlow-Lite-for-the-Ultimate-Goal-Challenge.md +++ b/Using-TensorFlow-Lite-for-the-Ultimate-Goal-Challenge.md @@ -1,6 +1,8 @@ ### What is a TensorFlow Lite? [TensorFlow Lite](https://www.tensorflow.org/lite/) is a lightweight version of Google's [TensorFlow](https://www.tensorflow.org/) machine learning technology that is designed to run on mobile devices such as an Android smartphone. A _trained TensorFlow model_ was developed to recognize game elements for the 2020-2021 Ultimate Goal presented by QualComm challenge. This TensorFlow model has been integrated into the FIRST Tech Challenge Control System software and can be used to identify and track these game pieces during a match. +

[[/images/Blocks-Sample-TensorFlow-Object-Detection-Op-Mode/quadAndSingle.png]]
Create an Op Mode with ConceptTensorFlowObjectDetection as its template.

+ For this season's challenge, the inference model was trained to recognize a single Ultimate Goal ring. The model was also trained to recognize a stack of four rings. This was done since it is easier to train a model to distinguish between a single and quadruple ring stack, rather than training a model that can reliably distinguish the individual rings of a multi-ring stack. ### How Might a Team Use TensorFlow in the Ultimate Goal Challenge?