* Make MultiTagPNPResult and PNPResult singular
* add java tests
* Formatting fixes
* bring in the rest of the little stuff
* final things
* Formatting fixes
* add multisubscriber back
* Formatting fixes
* make comments better about x and y relationship
- Aruco pipeline now infers tag width from tag family like the AprilTag pipeline
- Removes unused Aruco and 200mm AprilTag models
- `VisionEstimation.estimateCamPosePNP()` now requires a target model instead of assuming 16h5
- Multitarget pipeline similarly infers target model of tag family now
- `PhotonPoseEstimator` can have target model set for on-rio multitarget
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Co-authored-by: amquake <noleetarrr@gmail.com>
- `PNPResults` can now be empty (`isPresent` = false)
- solvePNP methods actually handle errors and return empty `PNPResults`
- This reveals an odd error where some inputs to `solvePNP_SQUARE()` resulted in an estimated transform with NaN values, and attempts to handle it
- Overwrites java changes from #817 since #742 had duplicate fixes
- Minor bugfixes
### What does this do?
- Deprecates previous sim classes
- Has a `CameraProperties` class for describing a camera's basic/calibration info, and performance values for simulation. Calibration values can be loaded from the `config.json` in the settings exported by photonvision.
- `OpenCVHelp` provides convenience functions for using opencv methods with wpilib/photonvision classes, mainly to project 3d points to a camera's 2d image and perform solvePnP with the above camera calibration info.
- `TargetModel`s describe the 3d shape of a target, both for projecting into the camera's 2d image and use in solvePnP.
- `PhotonCameraSim` uses camera properties to simulate how 3d targets would appear in its view, and has simulated noise, latency, and FPS. For apriltags, the best/alternate camera-to-target transform is also estimated with solvePnP.
- `VideoSimUtil` has helper functions for drawing apriltags to a simulated raw and processed MJPEG stream for each camera using the projected tag corners.
- `VisionSystemSim` stores `VisionTargetSim`s and `PhotonCameraSim`s, and is periodically updated with the robot's simulated pose. When updating, camera sims are automatically processed and published with their visible targets from their respective poses with proper latency.
### What's still not working?
- Mac Arm builds are broken
- More examples
- Update website/docs
* Add pose caching to Java
* Refactor strategy fallthrough
* Hopefully add pose caching to C++
* Make Java switch same order as enum and C++ switch
* C++ absolute value in timestamp check
* Fix Java NPE
* Use `units::second_t` in timestamp
Co-authored-by: Matt <matthew.morley.ca@gmail.com>
* Expand Java unit test
* Copy comments into C++
* Add tests to C++
* Run format
* Update PhotonCamera.cpp
* Probably fix bad access exception
* a
* init timestamp
* Remove prints
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Co-authored-by: Matt <matthew.morley.ca@gmail.com>
Co-authored-by: Joseph Eng <joseng2358@gmail.com>
* Use List for RobotPoseEstimator constructor
* Update `RobotPoseEstimator` constructor to accept wpilib `AprilTagFieldLayout` java
* Initial cpp changes
* Java return optional from update
* Fix java test
* Clean up strategy switch
* small lint
* Actually link to vision_shared
* Fix auto optimized imports
* format
* report error
* small method changes
* format and clean up
Co-authored-by: Matt <matthew.morley.ca@gmail.com>
RobotPoseEstimator can pick the most likely pose for the robot given a number of possible poses, using a number of different strategies. Examples are still WIP.
* WIP updating sim stuff for 2023 and pose3d's
* vision system build fixups, but test not yet passing.
* WIP Sim fixups and working on testcases
* Still doesn't work, but closer
* tests pass
* removed C++ sim support
* formatting update
* adjusted target height above ground per review
* Turns out its unused
* missed example removal
