This is the official repository for CobaltCV the new computer vision library for FTC! Inspired by past vision libraries including DogeCV and EasyOpenCV, this is a field-ready computer vision library with game support starting at Ultimate Goal 2020-2021. Designed for beginner programmers and on, there is finally no intense java expierience required to use computer vision on your robot! We take the sweat out of vision with sample vision programs and premade pipelines along with compatibility for using a phone camera, control hub, and external webcams! Written based off of EasyOpenCV, code is highly functional and established off of a reliable source. To get started, follow the steps below.
To get started with using CobaltCV, you have two options:
- Option 1: Download repository
- Copy the link of the repository then using Git bash in the folder where you want your repository, type in
git clone https://github.com/AlessioToniolo/FTC-EOCV-Ultimate-Goal - Open the folder in android studio, then navigate to the teamcode folder and you should find two folders with files inside them: vision and drive
- Once you have seen this, you are all set! You can add any other code files for your robot as needed
- Option 2: Add to an existing repository
- Open your team's sdk project, and navigate to build.common.gradle
- Add the code
jcenter()torepositories - Navigate to build.gradle for teamcode and add
implementation 'org.openftc:easyopencv:1.4.1to dependencies - From there add the vision files to your project
- Use as needed! If you would like to use our vision samples, download them from drive in teamcode
- You are finished!
In order to use OpenCV, you must download this file and add it to your robot controller files underneath the usb folder, whether that would be a control hub or robot phone. https://github.com/AlessioToniolo/FTC-EOCV-Ultimate-Goal/blob/master/libOpenCvNative.so
For more in depth documentation and configurations, visit these two links:
If you would like to contribute to CobaltCV, join our discord server!