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Updated references to the FTC Machine Learning toolkit, including links.

Westside Robotics
2021-11-19 20:11:30 -08:00
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Using-TensorFlow-in-Freight-Frenzy.md

@ -7,9 +7,9 @@ This season's TFOD model can recognize Freight elements._
TensorFlow Object Detection (TFOD) has been integrated into the FTC control system software, to identify and track these game pieces during a match. The FTC software (SDK version 7.0) contains TFOD Sample Op Modes that can recognize the Freight elements Duck, Box (or Cube), and Cargo (or Ball).
Also, FTC teams can soon use a new tool to train their own TFOD models, to recognize their custom Team Shipping Element (TSE) and/or to improve recognition of Freight elements. This training could take into account certain conditions of distance, angle, lighting and background.
Also, FTC teams can use a new tool to train their own TFOD models, to recognize their custom Team Shipping Element (TSE) and/or to improve recognition of Freight elements. This training could take into account certain conditions of distance, angle, lighting and background.
This new tool, FTC Machine Learning Toolchain, was [announced 10/7/2021](http://firsttechchallenge.blogspot.com/2021/10/new-machine-learning-tool-beta-testing.html) for upcoming beta testing by interested FTC teams.
This new tool is the **FTC Machine Learning toolchain**, [announced 10/7/2021](http://firsttechchallenge.blogspot.com/2021/10/new-machine-learning-tool-beta-testing.html). Learn more at these links: [[forum]](https://community.ftclive.org/) [[manual]](https://storage.googleapis.com/ftc-ml-firstinspires-prod/docs/ftc-ml_manual_2021.pdf) [[source]](https://github.com/FIRST-Tech-Challenge/fmltc) [[guide]](https://github.com/FIRST-Tech-Challenge/fmltc/blob/main/doc/usage.md)
### How Might a Team Use TensorFlow in Freight Frenzy?
@ -41,7 +41,7 @@ Click on the following links to learn more about these sample Op Modes.
### Using a Custom Inference Model
Teams have the option of using a custom inference model with the FIRST Tech Challenge software. As in the past, some teams may want to use the [TensorFlow Object Detection API](https://github.com/tensorflow/models/tree/master/research/object_detection) to create an enhanced model of the Freight elements or TSE, or 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. As noted above, the **FTC Machine Learning toolchain** is a streamlined tool for training your own TFOD models. An alternate would be to use the [TensorFlow Object Detection API](https://github.com/tensorflow/models/tree/master/research/object_detection) to create an enhanced model of the Freight elements or TSE, or 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**:
@ -50,8 +50,6 @@ The FTC software includes sample op modes (Blocks and Java versions) that demons
These tutorials use examples from a previous FTC season (Skystone), but the process remains generally valid for Freight Frenzy.
As noted above, soon FTC teams will have a streamlined tool for training their own TFOD models. Watch for announcements regarding the FTC Machine Learning Toolchain, already scheduled for beta testing.
### Detecting Everyday Objects
You can use a pretrained TensorFlow Lite model to detect **everyday objects**, such as a clock, person, computer mouse, or cell phone. The following advanced tutorial shows how you can use a free, pretrained model to recognize numerous everyday objects.
@ -61,4 +59,4 @@ You can use a pretrained TensorFlow Lite model to detect **everyday objects**, s
_<p align="center">[[https://raw.githubusercontent.com/wiki/FIRST-Tech-Challenge/FtcRobotController/images/Using-a-TensorFlow-Pretrained-Model-to-Detect-Everyday-Objects/tfliteDemo.png]]<br/>TensorFlow can recognize everyday objects._
<br/>
_<p align="right">updated 10/21/21</p>_
_<p align="right">updated 11/19/21</p>_