> there is a problem if the found tags are a valid one plus an invalid tag, so eg it sees a tag but finds noise on the wall, and so lists tags 2 and 15. Lines 90-99 will ignore tag 15, and put 4 corners into the list. It will get past the test on line 100 (there are 4 corners). BUT then at line 106, there are 2 entries in visTags, so it will go to the "else" and try to use solvePNP_SQPNP().
* fix an issue where the fov isnt reset on error
* Fix issue with incorrectly reading fov on update
* Properly handle NPE in case of error
* Fix issue with vuetify comps not converting strings to numbers
* Formatting fixes
- `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
This reverts commit 013ff5e, which caused crashes with libcamera cameras.
More testing required to root-cause and fix this PR, but rolling back for testing for now.
### 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
Serializes settings using a sqlite database instead of just putting them on the filesystem. Ideally since sqlite deals with filesystem robustness stuff this should work a lot better
Merging this now so we have lots of time to stabilize pre-beta
