fixed the unpacking order to match the current pipelineresult data layout.
* fix positioning of multitarget struct in pipelineresult unpack
* fix encode order in PhotonPipelineResult.cpp
* [photon-lib java] Fix classes with protobuf support not "announcing it"
Since they didn't implement `ProtobufSerializable` this meant that most other software didn't even know protobufs were even implemented.
In AdvantageKit for example this would cause it to not work it all and crash.
* Run `spotlessJavaApply`
Allows logging software and live data view to see results. Also removes the requirement for AScope to keep up with the packet serde schema and instead just use the Protobuf descriptor.
Follows a similar system to the current Protobuf implementation that helps make code more readable and expandable. Also wraps the NT topic to be more useful. Impl stuff is hidden so it can't be extended. Optimizes AT-specific classes by only serializing data when needed, won't save on size but will on time.
closes#1003
* add classes to targeting and update gradle
* rename me
* Finish cleanup
* Formatting fixes
* just use common.gradle
* Update build.gradle
* Update config.gradle
* remove typo
* simplify
* Add Packet Headers
* move simulation classes into simulation folder
* draw in dependency
* fix
* Everything working minus tests cause im lazy
* formatting fixes
REMEMBER TO REMOVE UNUSED IMPORTS, IM JUST TOO LAZY TO CHECK RN
* move packet test to targeting
* Formatting fixes
* remove TargetCorner from c++
im not 100% sure but just doing std::pair<double, double> is sufficient and shouldnt conflict with protobuf
* think i added packet
* fix namespace issue
* organize imports in photon-targeting
* Formatting fixes
* remove ctors
* fix typo
* Add PNP and Multitag packet tests
* revert TargetCorner class
* Add Test placeholders
* remove annoying print
* Reorganize build and publish process
channeling inner Thad
* add targeting as flag
* Update config.gradle
* fix issue with platform binaries not building
* Update photonlib.json.in
casing still needs to be checked
* add minimum level back
* add back UTF-8 encoding of javadoc
* simplify publish model for photon-lib
* fix windows symbol generation
* formatting fixes
* move task from main gradle to config
* Update config.gradle
* 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
---------
Co-authored-by: amquake <noleetarrr@gmail.com>
### 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
