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FTC Neural Net Demo 1.0.1

73.5 MB / 1+ Downloads / Rating 5.0 - 1 reviews


See previous versions

FTC Neural Net Demo, developed and published by Justin Kerr, has released its latest version, 1.0.1, on 2017-07-03. This app falls under the Education category on the Google Play Store and has achieved over 100 installs. It currently holds an overall rating of 5.0, based on 1 reviews.

FTC Neural Net Demo APK available on this page is compatible with all Android devices that meet the required specifications (Android 4.4+). It can also be installed on PC and Mac using an Android emulator such as Bluestacks, LDPlayer, and others.

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App Screenshot

App Screenshot

App Details

Package name: com.justin.ftcnndemo

Updated: 8 years ago

Developer Name: Justin Kerr

Category: Education

New features: Show more

App Permissions: Show more

Installation Instructions

This article outlines two straightforward methods for installing FTC Neural Net Demo on PC Windows and Mac.

Using BlueStacks

  1. Download the APK/XAPK file from this page.
  2. Install BlueStacks by visiting http://bluestacks.com.
  3. Open the APK/XAPK file by double-clicking it. This action will launch BlueStacks and begin the application's installation. If the APK file does not automatically open with BlueStacks, right-click on it and select 'Open with...', then navigate to BlueStacks. Alternatively, you can drag-and-drop the APK file onto the BlueStacks home screen.
  4. Wait a few seconds for the installation to complete. Once done, the installed app will appear on the BlueStacks home screen. Click its icon to start using the application.

Using LDPlayer

  1. Download and install LDPlayer from https://www.ldplayer.net.
  2. Drag the APK/XAPK file directly into LDPlayer.

If you have any questions, please don't hesitate to contact us.

Previous Versions

FTC Neural Net Demo 1.0.1
2017-07-03 / 73.5 MB / Android 4.4+

About this app

This app demonstrates what a trained neural net can do by detecting FTC game elements and robots. It is fully open-source at http://github.com/kerrj/yoloexampleapp with more extensive documentation of how to use this during the season at http://github.com/kerrj/yoloparser.

To use, enable the camera permission and point the camera at one (or multiple) of the three objects the app is trained to detect:
1. FTC Robot
2. Red wiffle ball (Velocity Vortex)
3. Blue wiffle ball (Velocity Vortex)

The app will draw boxes around detected objects with their name, and percent confidence. The app has a threshold of 20% confidence, so anything below that will not show up.

New features

**1.0.1**
Addressed a bug on android 5.0 where the camera stream displayed green.
Added keeping the screen awake while running.

App Permissions

Required to be able to access the camera device.
Allows using PowerManager WakeLocks to keep processor from sleeping or screen from dimming.
Allows an application to write to external storage.
Allows read only access to phone state, including the phone number of the device, current cellular network information, the status of any ongoing calls, and a list of any PhoneAccounts registered on the device.
Allows an application to read from external storage.