EasyOpenCV VS OpenCV

you can record from the robot's POV with openCV: https://github.com/OpenFTC/EasyOpenCV/blob/master/examples/src/main/java/org/firstinspires/ftc/teamcode/PipelineRecordingExample.java

The SDK provides a UVC driver for webcams; it does not provide anything for phone cameras. If you'd really like to write your own implementation, you can use parts of https://github.com/OpenFTC/EasyOpenCV/blob/master/easyopencv/src/main/java/org/openftc/easyopencv/OpenCvWebcamImpl.java as a reference (which uses the SDK UVC driver), but do note that writing your own implementation means you need to write your own code for a live view, as well as handle threading etc.

getting basic computer vision working is pretty easy with EasyOpenCV and the AprilTag extension.

Apriltags, yes. You just upload the aar files using the OnBot interface. You can get them from the OpenFTC project: https://github.com/OpenFTC/EasyOpenCV/releases/tag/v1.5.2 https://github.com/OpenFTC/EOCV-AprilTag-Plugin/issues/4

Note: https://github.com/OpenFTC/EasyOpenCV/issues/58

We used the example for https://github.com/OpenFTC/EasyOpenCV/releases. Our fork is from the official FTCRobotcontroller repository with extensive slipstreaming. You are welcome to view our repository at baqwas and provide feedback to our programmers who are continuously learning new techniques. I'm sure that they will learn something from your feedback too.

This seems really odd to me, although someone else opened an issue about it: https://github.com/OpenFTC/EasyOpenCV/issues/55

EasyOpenCV

Referenceshttps https://www.kaggle.com/datasets/riyaelizashaju/skin-disease-image-dataset-balanced?fbclid=IwAR3wbTp8l5yo_5fx6HAX8Vd2-9cca3khAc8EiBGFObaALfdVid29IuB_rYE https://keras.io/api/applications/vgg/ https://www.tensorflow.org/tutorials/images/cnn?hl=th https://opencv.org/

Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.

You'll need to plot the predictions. There are a few open source tools to do that, supervision is one you can use (https://github.com/roboflow/supervision) and opencv is another common option (https://github.com/opencv/opencv)

You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/).

The OpenCV4NodeJs A.I. library provides an interface for calling OpenCV routines in NodeJS.