EOCV-Sim
EasyTensorflowAPI
EOCV-Sim | EasyTensorflowAPI | |
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9 | 3 | |
51 | 5 | |
- | - | |
7.9 | 0.0 | |
7 months ago | over 2 years ago | |
Java | Java | |
MIT License | - |
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EOCV-Sim
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EasyOpenCV Simulator now supports the new VisionPortal API !
Fixed GitHub link - https://github.com/deltacv/EOCV-Sim/releases/tag/v3.5.1
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EOCV-Sim Workarounds to Run on macOS M1 PRO
Hey, i have just made a pre release containing the fix i mentioned. You can find it here: https://github.com/deltacv/EOCV-Sim/releases/tag/Dev . Please let me know if it works so that I can make the full release !
- Webcam in autonomous
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Easy OpenCV Resource Hunt
EOCV is pretty much just a "glue layer" between OpenCV and the FTC SDK. So I'd recommend starting by gaining some familiarity with OpenCV in general. You should also look into the EOCV-Sim project (developed by Sebastian) which will let you iterate much more quickly as you develop your pipeline as compared to deploying to the phones every time.
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How to use opencv or any cv on linux
https://github.com/deltacv/EOCV-Sim :) a simple software to test opencv algorithms on Linux, macos and windows
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Help a non-software coach help the kids with EasyOpenCV
Also easy open cv sim (eocv-sim) is a really nice tool to develop pipelines without robot with you (really nice for us programmers when you mech people take too long :P) https://github.com/deltacv/EOCV-Sim
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Python REV Robotics
And if you wanna develop OpenCV pipelines fast and quick without needing s phone i recommend using (shameless plug) EOCV-Sim: https://github.com/deltacv/EOCV-Sim
EasyTensorflowAPI
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Custom TFOD model
The FTC SDK does not support Image Classification models. If you want to use the model you created with Teachable Machine, you will need something that can use the image classification model. I have not used it, but https://github.com/OutoftheBoxFTC/EasyTensorflowAPI is a library that supports image classification. Its readme says "Image Classification system is only partially tested".
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Can you edit build.dependencies.gradle on OnBotJava?
There is a library for using image classification models in the SDK here (https://github.com/OutOfTheBoxFTC/EasyTensorflowAPI), but while it technically has onbot support, it's not recommended due to it's questionable stability on onbot.
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Python REV Robotics
So basically, you want to export your Tensorflow model as a .tflite model. This model contains the "brain" of the AI. If the model is a Tensorflow Object Detection model or a Tensorflow Image Classification model you can try to write your own code or use the dev branch of EasyTensorflowAPI, if its a custom one then right now you need to write your own interface using the tensorflow lite API. Basic usage is to put the .tflite file somewhere accessible (EasyTensorflowAPI uses the assets folder of the FTCRobotController module), then load it in an interpreter and run it using that interpreter
What are some alternatives?
EasyOpenCV - Finally, a straightforward and easy way to use OpenCV on an FTC robot!
Pathfinder2 - Paths, trajectories, splines, the number 2, and a whole lot of swag.
FtcRobotController - Robot Controller implementation by Team 15173 Robotic Eagles of Milton High School
EOCV-Sim - FTC Library EasyOpenCV simulator for testing vision pipelines in a computer
photonvision - PhotonVision is the free, fast, and easy-to-use computer vision solution for the FIRST Robotics Competition.
ultimategoal - Robot code for the 2020-21 FTC game, Ultimate Goal.
PowerPlaySleeveDetection - This is a template repository, used for other teams to copy the Vision Pipeline when detecting the Signal Sleeve in the FIRST Tech Challenge 2022-2023 Game PowerPlay.
OpenCV - Open Source Computer Vision Library