From 1a7ca1f64f4989a908d0f5f9863f27489accde32 Mon Sep 17 00:00:00 2001 From: FTC Engineering Date: Wed, 28 Oct 2020 12:47:49 -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, 1 insertion(+), 1 deletion(-) diff --git a/Using-TensorFlow-Lite-for-the-Ultimate-Goal-Challenge.md b/Using-TensorFlow-Lite-for-the-Ultimate-Goal-Challenge.md index 265ca23..f2b5e16 100644 --- a/Using-TensorFlow-Lite-for-the-Ultimate-Goal-Challenge.md +++ b/Using-TensorFlow-Lite-for-the-Ultimate-Goal-Challenge.md @@ -24,7 +24,7 @@ Click on the following links to learn more about these sample Op Modes. * [Java Tensor Flow Object Detection Example](Java-Sample-TensorFlow-Object-Detection-Op-Mode) ### Using a Custom Inference Model -Teams have the option of using a customer inference model with the FIRST Tech Challenge software. For example, some teams prefer to use the [TensorFlow Object Detection API](https://github.com/tensorflow/models/tree/master/research/object_detection) to create an enhanced model of the game elements, or they might want to create a custom model to detect other entirely different objects. Other teams might also want to use an available pre-trained model to build a robot that can detect common everyday objects (for demo or outreach purposes, for example). +Teams have the option of using a custom inference model with the FIRST Tech Challenge software. For example, some teams prefer to use the [TensorFlow Object Detection API](https://github.com/tensorflow/models/tree/master/research/object_detection) to create an enhanced model of the game elements, or they might want to create a custom model to detect other entirely different objects. Other teams might also want to use an available pre-trained model to build a robot that can detect common everyday objects (for demo or outreach purposes, for example). The FTC software includes sample op modes (Blocks and Java versions) that demonstrate how to use a custom inference model: