## Description
compute confidence level based on target area in total image size and
populate classId and confidence level in Java (while building the
PhotonTrackedTarget)
## Changes
- Add new VisionTargetSim constructor for object detection
- If class ID specified but confidence = -1, estimate based on total
area
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Co-authored-by: Matt Morley <matthew.morley.ca@gmail.com>
## Description
<!-- What changed? Why? (the code + comments should speak for itself on
the "how") -->
<!-- Fun screenshots or a cool video or something are super helpful as
well. If this touches platform-specific behavior, this is where test
evidence should be collected. -->
<!-- Any issues this pull request closes or pull requests this
supersedes should be linked with `Closes #issuenumber`. -->
closes#2318closes#2319
For the 2027 game, teams might want to detect more than 10 results.
Therefore, we're increasing the limit.
We also ran into an issue with our sim, where a user can create too many
objects and cause an overflow. We implement that same limit of 50
targets here.
## 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 v2025.3.2
- [ ] 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
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.
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.
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
