Vision work for FTC DECODE (2025-2026): finding the green and purple balls with a camera, tracking them in field coordinates, and driving the robot to chase them like a dog.
ftc-auto-dog.pdf— design document for the auto dog: pixel to field projection, per-track Kalman filter, gating, Mahalanobis association, and pose time sync.
Desktop computer vision tests, from FTCDecodeVision.
vision.py— main AprilTag-anchored green/purple ball detection pipelinevision_fixed.py,vision_debug.py,vision2.py— variants and debug views of the pipelineballDetect.py— ball detection plus tracking with an OpenCV trackerSimpleBallTracker.py—SimpleBallTrackerclass: per-frame green/purple detection plus CSRT tracking, meant for robot integrationLuxonisTracking.py— 3D ball trajectory tracking with a Luxonis OAK-D (depthai 3.x), with CSV loggingempiricalTrajectory.py— empirical trajectory recorderremoteTestingRoom.py— saves frames and debug masks for offline analysiscapture_calib.py,calibrate.py,calib_imgs/— chessboard capture and camera intrinsics calibration (theKand distortion values the design doc's pixel to field projection needs)
On-robot Kotlin code from the tanayVision branch of FTC-SigmaCorns-22377/Decode, kept at its original TeamCode paths. These files depend on the rest of that repo and do not build on their own.
GlobalShutterVision/eyebrain.kt—EyeBrain, theVisionProcessorport ofvision.pyfor the global shutter cameraopmode/test/VisionDriveTest.kt— teleop that usesEyeBrainon theglobalShutterwebcam to turn toward and chase a ballopmode/test/ShooterExperimentTest.kt— shooter experiment teleop for camera system integrationcontrol/localization/VisionTracker.kt,constants/Limelight.kt,res/xml/teamwebcamcalibrations.xml— team localization and camera calibration code the vision work relies on (written by Sigma Corns teammates)
cd python
python -m venv .venv && source .venv/bin/activate
pip install opencv-python numpy depthai
python vision.py