Persuant to #1093, I added as many docstrings as I could, at least for
things I knew about. Some of the classes I just suppressed the Javadoc
warnings in because they aren't particularly useful to document. This
gets us down to less than 100 Javadoc warnings in total. Docs for core
classes on the C++ side were also added for parity.
Fix numerous places where using AutoCloseable objects without closing
them.
Changes:
- Upgrade JUnit from 5.10.0 to 5.11.4 (so `@AutoClose` can be used)
- Use `Files.copy()` to copy files
- Use try-with-resources when calling `Files.list()` or `Files.walk()`
- Use try-with-resources or `@AutoClose` to close `PhotonCamera` and
`PhotonCameraSim` objects created by tests
- Update `SQLConfigTest` to use `@TempDir`
## Meta
Merge checklist:
- [x] Pull Request title is [short, imperative
summary](https://cbea.ms/git-commit/) of proposed changes
- [x] The description documents the _what_ and _why_
- [ ] If this PR changes behavior or adds a feature, user documentation
is updated
- [ ] If this PR touches photon-serde, all messages have been
regenerated and hashes have not changed unexpectedly
- [ ] If this PR touches configuration, this is backwards compatible
with settings back to v2024.3.1
- [ ] If this PR touches pipeline settings or anything related to data
exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
Fixes#1239
Tag image corners used in `VideoSimUtil` did not match the expected
corner order returned by the detection pipeline of [BL, BR, TR, TL],
causing the tag image to appear flipped.
## Meta
Merge checklist:
- [x] Pull Request title is [short, imperative
summary](https://cbea.ms/git-commit/) of proposed changes
- [x] The description documents the _what_ and _why_
- [x] If this PR changes behavior or adds a feature, user documentation
is updated
- [ ] If this PR addresses a bug, a regression test for it is added
Force loads OpenCV before any OpenCV functions are used. `OpenCVLoader`
has all of its loading done in a static initializer field, so it's only
loaded once.
Also deprecates `OpenCVHelp.forceLoadOpenCV()`, since it's functionality
is the exact same.
Resolves#1803
# Overview
Previously if the coproc came up later, getProperty would return the
string literal "null", which made us print the BFW. Add tests to make
sure that we don't do that anymore by rebooting a sim coproc +
robot in a combination of different orders.
* Serialize all calibration data
* Run lint
* typing nit
* fix code
* move these tables around some
* Add cool formatting
* add request to get snapshots by resolution and camera
* re-enable all resolutions
* add wip so i can change computers (SQUASH ME AND KILL ME AHHHH)
* Get everything working but viewing snapshots
* Update RequestHandler.java
* Update CameraCalibrationInfoCard.vue
* Update CameraCalibrationInfoCard.vue
* add observation viewer
* round
* fix illiegal import
* Swap to PNG and serialize insolution
* move import/export buttons TO THE TOP
* Update WebsocketDataTypes.ts
* Add snapshotname to observation
* Refactor to serialize snapshot image itself
* Run lint
* Use new base64 image data in info card
* Update SettingTypes.ts
* Create calibration json -> mrcal converter script
* Update calibrationUtils.py
* Fix calibrate NPEs in teest
* Run lint
* Always run cornersubpix
* Update CameraCalibrationInfoCard.vue
Update CameraCalibrationInfoCard.vue
* Update OpenCVHelp.java
* Update OpenCVHelp.java
* Replace test mode camera JSONs
* Run wpiformat
* Revert intrinsics but keep other data
* Remove misc comments
* Rename JsonMat->JsonImageMat and add calobject_warp
* Update Server.java
* Rename cameraExtrinsics to distCoeffs
* fix typing issues
* use util methods
* Formatting fixes
* fix styling
* move to devTools
* remove unneeded or unused imports
* Remove fixed-right css
If its really that big of a deal, we can add it back later, kind of a drag to fix rn.
* Create util method
* Remove extra legacy calibration things
---------
Co-authored-by: Sriman Achanta <68172138+srimanachanta@users.noreply.github.com>
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
* 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>
- `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
