## Description
This fixes up and renables the python examples builds.
Main fixes
- Test shell script just straight up didn't do what it was intended to
do
- Replace analog imus (and half refactored sims) with OnboardIMU
- Fixes swerve velocities function signature
- "regenerates" the default robotpy test
## Meta
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is updated
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---------
Co-authored-by: Matt Morley <matthew.morley.ca@gmail.com>
Co-authored-by: David Vo <auscompgeek@users.noreply.github.com>
## Description
Previously, we only published if `github.ref == 'refs/heads/main'`. But
we want to publish PhotonLib on tags, too
## Meta
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that led to this PR
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is updated
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Co-authored-by: Matthew Morley <mmorley@blueorigin.com>
## Description
WPILib switched from FasterXML Jackson to Avaje Jsonb for speed reasons
in https://github.com/wpilibsuite/allwpilib/pull/8721. This does the
same for PhotonVision. Some temporary Jackson adapters are present to
allow compatibility with alpha-4 ahead of updating Photon's WPILib
version. A few old backwards compatibility migrations were also dropped
if they were difficult to port to Avaje Jsonb or otherwise complicated
the code.
## Meta
Merge checklist:
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summary](https://cbea.ms/git-commit/) of proposed changes
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that led to this PR
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is updated
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(seasons end after champs ends)
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compatibility and steps taken to follow it
---------
Co-authored-by: samfreund <samf.236@proton.me>
Co-authored-by: Matt Morley <matthew.morley.ca@gmail.com>
Fixes failure in #2481. The pnpm version was unpinned, so it quietly moved to pnpm 11, which introduced several breaking changes including one with approved builds (specifically, strictDepBuilds). Since we're on pnpm 11 anyways, use their new system for approving postinstalls for certain dependencies.
We recently had an error that would've been caught by type checking in the frontend (see #2393). This PR implements type checking so that future errors will be caught.
Additionally, this PR contains miscellaneous frontend cleanup that's tangentially related to type-checking.
Add a command to lint the website to package.json, and update the
workflow. Updates docs for linting as well.
---------
Co-authored-by: Jade Turner <spacey-sooty@proton.me>
Adds ./gradlew buildAndCopyUI instruction to the documentation on building Photonvision, to clarify that this step must be ran to properly build the UI
Closes#2452
Add a command to lint the website to package.json, and update the
workflow. Updates docs for linting as well.
---------
Co-authored-by: Jade Turner <spacey-sooty@proton.me>
This PR updates everything for 2027. This includes removing GradleRIO, simplifying our wpilib version defintion, updating APIs, updating to Java 21, and more.
Note that photonlibpy is failing because robotpy has not been fully updated yet. Examples are omitted because they need to be updated for our new PhotonPoseEstimator API and still need some changes from WPILIB. photonlib windows build is failing because we're waiting for some upstream changes. Finally, images are failing since they don't have Java 21 yet.
## Description
Added systemcore to a couple of build files in order for `./gradlew
publishToMavenLocal` to generate systemcore-compatible dependencies.
Needed to support deploying photonlib to systemcore.
## Meta
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---------
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
On a Luma P1, autoexposure on first boot was getting overridden with the manual exposure setting. This was traced back to #1814, where the order of setting auto exposure and raw exposure was flipped. This flips it back.
## Description
Leadership team identified gaps in how we introduce new developers to
the community.
Additional docs for onboarding new developers, helping clarify roles and
what counts as a "good" PR.
## Meta
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I assume based off discord comments a PR won't be accepted for a
shell.nix or equivalent flake solution so we should gitignore this so
people don't accidentally add them to PRs
The current method for checking light vs. dark mode is to compare the
name of the theme against a hardcoded string. This PR uses a dark mode
boolean. This change is for verbosity and so that we're not reliant on
theme name. Additionally, we change some references to colors to the
global theme, instead of indexing the list of themes.
As a precursor to #2394, add a bunch of linting rules to try and catch
more mistakes/potential code errors/unnecessary code. Add a bunch of
rules from https://eslint.vuejs.org/rules/ in the "uncategorized"
section that seem useful to have.
## 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
---------
Co-authored-by: Matt Morley <matthew.morley.ca@gmail.com>
## Description
Back in
https://github.com/PhotonVision/photonvision/pull/467#issuecomment-1280964529
and
https://discord.com/channels/725836368059826228/725846784131203222/974498049609056266
we added code to poke our NT client every 5 seconds to "clicking the
save button in the settings window makes Photon show up again over
networktables". Total hack, but it seemed to work. We didn't at the time
dig any deeper in Wireshark or debug-level NT logs.
<img width="1373" height="679" alt="image"
src="https://github.com/user-attachments/assets/8cb2102e-0bae-4bfd-b9ac-55d31f8421b6"
/>
Now, it's 2026. 4 years on from the OG bug. And this code seems linked
to these issues
-
https://www.chiefdelphi.com/t/photonvision-coprocessor-not-sending-data-can-t-change-networking/516356/5
-
https://www.chiefdelphi.com/t/photonvision-network-tables-known-issue/515966
Craig collected these log files as well:
[craig-nt-never-connects.zip](https://github.com/user-attachments/files/26001809/craig-nt-never-connects.zip)
The code path that handles TCP re-connection was also changed entirely
since we first added this workaround. Regardless this hack was not
removed as part of the NT3 to NT4 upgrade:
- pre-NT4, reconnection was handled by `TCPConnector::connect_parallel`
which delegates to `TCPConnector`. This uses raw socket APIs
- post-NT4, reconnect is handled by `ParallelTcpConnector`. This uses
libuv exclusively
@crschardt did some really great debugging with a rio and radio in the
loop with a luma p1. In this test setup, removing this code improves
stability markedly. I'd still like to get this more on robot time, as
well as try to understand from Peter why we might have needed this code
in the first place.
## Changes
- Remove periodic stop/restart of NetworkTables client every 5 seconds
if `NetworkTablesInstance::isConnected` returns false.
## Meta
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---------
Co-authored-by: Craig Schardt <crschardt@fastem.com>
Fixes a bug where offline update did not start after confirming the
dev-version warning dialog.
The confirm action was using an incorrect file reference in template
context, so the selected JAR was not passed correctly to the upload
handler. The dialog closed, but no upload request was sent.
This change corrects the confirm handler so the selected file is passed
properly and the upload/install flow starts as expected.
We've had a couple people who didn't find it clear that multiple
coprocessors required different static IP addresses, so this PR aims to
clarify that point in the docs.
## Description
What changed? Why? (the code + comments should speak for itself on the
"how")
Added section on low-resource vision simulation with Photonvision,
including configuration details and use cases for low-spec machines.
Closes#2358
---------
Co-authored-by: Chris Gerth <gerth2@users.noreply.github.com>
This PR adds documentation for using usbtop, a program for monitoring
USB bus bandwidth. Many teams have been having issues with USB bus
bandwidth, and including a tool with the PhotonVision image that allows
them to monitor said bandwidth will likely prove beneficial.
This PR also documents lsusb, which can be used to get the max bandwidth
on USB buses. This is helpful as it gives us a basline for debugging
with usbtop.
## Description
Closes#1902
**What changed? Why? (the code + comments should speak for itself on the
"how")**
The amount of UI windows that contributors have open (and then proceed
to frantically close) increases exponentially with every passing build
season [(Munroe 2009)](https://xkcd.com/605/).
This PR adds headless (no-UI) test instructions, moves all of the test
related build documentation to its own subsection (and reorders it
roughly in the order we prefer they be used in), and makes the "Example"
sections their own independent H2.
## Meta
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that led to this PR
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is updated
---------
Co-authored-by: Matt M <matthew.morley.ca@gmail.com>
## Description
We've hit a problem where the `CombinedRuntimeLoader` extracts native
files, but gets interrupted in the middle. This is bad, cause all
`CombinedRuntimeLoader` used to check a file was its existence. This
change uses the hash of the file to verify that it's correct. This will
be checked at runtime, everytime, if the file is extant. If this check
fails, we will delete the extant file and attempt to reextract. We also
check a newly extracted file, if that hash does not match we error.
Note that this is reliant on
https://github.com/PhotonVision/wpilib-tool-plugin/pull/8 and should
follow #2367
## Meta
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---------
Co-authored-by: Matt M <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`. -->
Pursuant to PhotonVision/rubik_jni#21 modify the neuralnetworkresult and related code to use a rotatedrect. This is scaffolding for implementing OBB -- overall this shouldn't change behavior of existing normal object detection models. This PR also bumps the rubik_jni version.
## Meta
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Co-authored-by: Matt Morley <matthew.morley.ca@gmail.com>
Given that WPILib is nuking their Java tooling, it becomes necessary to
pull said tooling into PV itself. This migrates the
CombinedRuntimeLoader into PV, which should finalize all of the tooling
migration.
There have been recent updates to the QCL which mean it's now necessary
to select a checkbox to flash USB firmware. We've been having some
people miss this step, so we're now including it in the docs.
## Description
Presently, any tests using our old configs happen in place. This is
problematic, as it changes the files themselves. This means that anyone
running the tests will cause unintentional modifications, which stand a
chance of being committed and merged into main. We want these old
database files to remain untouched, thus we copy them to a temp
directory prior to running our tests.
## Meta
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## Description
Previously, when attempting to load a model that did not follow the old
naming pattern that was in the models directory, we caused PV to crash
due to a missing early return (reproducable on this branch with the
extra bonus ML model and missing label file):
```
[2026-02-01 17:35:15] [Config - NeuralNetworkModelManager] [ERROR] Model properties are null. This could mean the config for model /home/matth/photonvision/test-resources/old_configs/2025.3.1-old-nnmm/models/iCauseProblems.rknn was unable to be found in the database. Trying legacy...
[2026-02-01 17:35:15] [Config - NeuralNetworkModelManager] [ERROR] Failed to translate legacy model filename to properties: /home/matth/photonvision/test-resources/old_configs/2025.3.1-old-nnmm/models/iCauseProblems.rknn: /home/matth/photonvision/test-resources/old_configs/2025.3.1-old-nnmm/models/iCauseProblems-labels.txt
SQLConfigTest > testLoadNewNNMM() FAILED
java.lang.NullPointerException: Cannot invoke "org.photonvision.common.configuration.NeuralNetworkModelsSettings$ModelProperties.toString()" because "properties" is null
at org.photonvision.common.configuration.NeuralNetworkModelManager.loadModel(NeuralNetworkModelManager.java:342)
at java.base/java.util.stream.ForEachOps$ForEachOp$OfRef.accept(ForEachOps.java:183)
```
This PR fixes it by adding the missing early-return, and adding unit
tests to make sure we handle this.
## Meta
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---------
Co-authored-by: Matt M <matthew.morley.ca@gmail.com>
## Description
#2255 introduced a new, cross-platform method for monitoring hardware
and removed the custom shell commands that had been used previously.
This PR updates the documentation to reflect the removal of those
commands from hardwareConfig.json.
## Meta
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---------
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
## Description
FRC Team 6413 ran into problems trying to write the 2026.1.1 image using
the Raspberry Pi Imager tool. After some investigation we discovered a
bug was introduced in v2.0.2 of the imager tool which prevents it from
writing the PhotonVision images to any SD card on any Windows 10 or
Windows 11 computer.
Attempting to write a custom image (.img and .img.xz) results in the
following error dialog appearing as soon as the write action is
confirmed:
<img width="684" height="483" alt="photonvisionBurnFailure202"
src="https://github.com/user-attachments/assets/5c802ef0-75f9-4056-ac1f-760dcd3605bf"
/>
Versions 2.0.0 and earlier will successfully write the image files to
the selected SD card.
## Meta
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The RubikPi collab notebook included a device for creating a quantized
model that was deprecated by the Qualcomm team. I've included a separate
cell with a command to check available devices and updated the command
to a known working state.
## Description
In https://github.com/PhotonVision/photonvision/issues/1771, we
discovered that the OV9281 on Linux seems to sometimes ignore our
exposure requests on first boot if we're in manual mode. Cycling the
camera's auto exposure with pauses in-between seems to fix it, which is
what this PR does.
Tested by [Team 2881 on
Discord](https://discord.com/channels/725836368059826228/725846784131203222/1465098110765105456);
thanks for helping us test this fix out!
## Meta
Closes https://github.com/PhotonVision/photonvision/issues/1771
Merge checklist:
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---------
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.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:
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summary](https://cbea.ms/git-commit/) of proposed changes
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## Description
Clarifies when estimate methods return an empty optional. This also
fixes some parity issues with Constrained SolvePnP not checking the
optional returned by the heading buffer.
Resolves#2322.
## Meta
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## Description
Added specific details to the wiring section of the photonvision docs
for two wiring methods for connecting a power regulator to a
coprocessor. This aims to help prevent any possible misunderstandings of
how to wire a regulator to a coprocessor.
## Meta
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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`. -->
This PR adjusts how model modification is handled. Any updates to
metadata, or deletion is handled in the frontend after sending data to
the backend. Any creation of models occurs in the backend, and we push
an update to the frontend.
This PR also fixes a typo in PhotonUtils which meant we hit the wrong
endpoint when an IP was passed into the status check.
## Meta
Merge checklist:
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summary](https://cbea.ms/git-commit/) of proposed changes
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## Description
On main, this pop-up lists the wrong resolution. The index in the state
is getting updated out from underneath us. The easiest solution I have
is to just cache this number.
<img width="739" height="1051" alt="image"
src="https://github.com/user-attachments/assets/a4383ea0-aa1b-4446-87f1-ece8c5ea9ad5"
/>
<img width="873" height="1116" alt="image"
src="https://github.com/user-attachments/assets/7da4cd60-f8a6-4ac6-8bc6-9f0d5c165fee"
/>
Not sure of a great way to test this, since it requires the backend
taking calibration snapshots
## Meta
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_Test what you build, deploy what you test._
This refactors the Python CI workflow to wait for _all_ tests to pass
before publishing photonlibpy to PyPI.
- build-python-examples reuses the built wheel, removes redundant builds
- Simplify run.sh to not rebuild wheel since it's already installed
## Description
Find-and-replace 2026.1.1 -> 2026.2.1. This gets us 2026 field layouts
[among other
things](https://github.com/wpilibsuite/allwpilib/releases/tag/v2026.2.1)
<!-- What changed? Why? (the code + comments should speak for itself on
the "how") -->
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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.
## Description
Monitoring CPU Temperature on Windows is challenging because most
vendors don't publish this data to WMI. As a work-around, OSHI tries to
use
[LibreHardwareMonitor](https://github.com/LibreHardwareMonitor/LibreHardwareMonitor)
via
[jLibreHardwareMonitor](https://github.com/pandalxb/jLibreHardwareMonitor).
If the temperature isn't found in WMI and jLibreHardwareMonitor isn't
present, OSHI issues warnings every time `getCpuTemperature()` is
called. This clogs the console with useless information when running on
Windows and makes testing difficult.
We could include jLibreHardwareMonitor as a dependency for our Windows
jar, but LibreHardwareMonitor installs Winring0.sys, which is a kernel
level driver with an unfixed severe vulnerability. Windows defender
flags Winring0 as a vulnuratble driver and blocks it from installing.
Rather than messing with it, this PR prevents Windows systems from
calling the `getCpuTemperature()` method in OSHI.
Fixes#2280
## Meta
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---------
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
## Description
This bumps our actions to versions that use Node 24, instead of 20. Node
20 [enters EOL in April 2026](https://endoflife.date/nodejs).
This PR also includes various cleanups that should speed up CI, and make
it less complicated. This includes removing the architecture field from
setup-java, as it detects the native architecture.
We also upload our Gradle dependencies for charting in GitHub, this
helps us keep track of what we're using, and if we need to upgrade.
Finally, we bump the version of our image, to fix issues with the Rubik
Pi fan among other reasons.
continuation of #2194
supercedes #2276
## Meta
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## Description
Forces a reload after restarting PhotonVision, restarting the
coprocessor, performing an offline update, or nuking the install. We
wait until we are reconnected to the coprocessor to reload, this is
accomplished by the addition of a status API endpoint.
This is being implemented due to issues experienced when the webpage is
not updated (particularly during offline updates).
---
Using the same statusCheck, we also wait until a new IP is available,
then change to it, after changing our static IP.
---
closes#2169closes#903
## Meta
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## Description
By hitting WPIlib's Artifactory Maven Central mirror instead of Maven
Central, we should reduce the number of 403 flakes we see during
workflow runs. This also removes jogamp from the repository list, as
jogamp dependencies were removed in #1926.
## Meta
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---------
Co-authored-by: samfreund <samf.236@proton.me>
## Description
Update to use our fork of the WPILib tool plugin. WPILib has indicated
that it won't be maintained past 2026, so we're forking it under our
org. We also fixed a bug that results in native libraries for multiple
platforms being included in a jar when only the native libraries for the
platform being built should be included.
## Meta
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---------
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
Co-authored-by: samfreund <samf.236@proton.me>
## Description
Fixed in https://github.com/robotpy/mostrobotpy/pull/191. Closes#1968.
## Meta
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Instead of building photon-lib for our examples, wait until it's built
elsewhere then use that to run the examples. This means we don't have to
build photon-lib twice.
The opengraph embed requires the image to be accessible at the linked
location. As you can see by clicking on this link,
https://photonvision.org/images/PhotonVision-Icon-BG_2.png, it is not
accessible. This is because we need to configure a public directory when
we publish with vite, as the subfolders will not inherently be
published.
This PR adds a public directory and moves all our images there. I also
moved the video to a video directory rather than it being in images.
Bumps various versions in actions, as well as ensuring consistency
across workflows wrt versions used. One of the key reasons is ensuring
that we're up to date and consistent (previously having used 22.04 and
24.04), also since 3.11 is EOL.
## Description
[OSHI](https://github.com/oshi/oshi) is a free (MIT license) JNA-based
library for accessing hardware and system performance information. This
PR includes a re-write of the metrics monitoring code to be based on
OSHI. The original intent was to gain access to data about network
traffic for addition to the Settings tab. An additional benefit is that
collecting the data is now around two orders of magnitude (or more)
faster!
## Meta
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---------
Co-authored-by: samfreund <samf.236@proton.me>
## Description
We currently log some things with ERROR status and include stack traces
for events that are typical behavior. This pollutes the logs and makes
it harder to track down real errors.
This PR changes the way that some events are logged:
* missing configs in the database are logged as [INFO] without the
exception stack trace.
* skip parsing NPU usage when the command is blank so that it doesn't
throw a NumberFormatException.
* log warn instead of error for unsupported NN backends (added by
@samfreund)
* skip warn when we don't add a model, only debug when we add it (added
by @samfreund)
Before:
```
Oct 22 20:56:26 photonvision java[831]: [2024-10-22 20:56:26] [Config - SqlConfigProvider] [ERROR] Could not deserialize apriltag layout! Loading defaults: Provided empty string for class edu.wpi.first.apriltag.AprilTagFieldLayout
Oct 22 20:56:26 photonvision java[831]: [2024-10-22 20:56:26] [Config - SqlConfigProvider] [ERROR] org.eclipse.jetty.io.EofException: Provided empty string for class edu.wpi.first.apriltag.AprilTagFieldLayout
Oct 22 20:56:26 photonvision java[831]: at org.photonvision.common.util.file.JacksonUtils.deserialize(JacksonUtils.java:136)
Oct 22 20:56:26 photonvision java[831]: at org.photonvision.common.configuration.SqlConfigProvider.load(SqlConfigProvider.java:298)
Oct 22 20:56:26 photonvision java[831]: at org.photonvision.common.configuration.ConfigManager.load(ConfigManager.java:198)
Oct 22 20:56:26 photonvision java[831]: at org.photonvision.Main.main(Main.java:290)
```
After:
```
Dec 15 22:29:09 photonvision java[662]: [2025-12-15 22:29:09] [Config - SqlConfigProvider] [INFO] Missing AprilTag Field Layout in database. Loading defaults
```
## Meta
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---------
Co-authored-by: samfreund <samf.236@proton.me>
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
## Description
On the RubikPi3, PhotonVision starts before NetworkManager has fully
initialized. This causes it to fail to identify the network interfaces
available on the board, which leads to problems with configuring and
controling networking from the UI. The failure can be detected by the
call to `nmcli` returning an [exit status of
8](https://networkmanager.dev/docs/api/latest/nmcli.html#exit_status),
which means "NetworkManager is not running."
This PR retries the call to nmcli every 0.5 seconds until the exit
status does not equal 8, or a maximum of 10 attempts have been made. The
retry only occurs the first time `getAllInterfaces()` is called.
Subsequent calls to this method will only make one attempt to avoid
locking up the program if networking isn't responding as expected.
In my testing on the RubikPi3, the code has to retry for less than 2
seconds in order to get a valid response from NetworkManager.
The need for this is greatly reduced by
https://github.com/PhotonVision/photon-image-modifier/pull/114, but this
code adds an additional layer of robustness against slow network
startup.
Closes#2212
## Meta
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---------
Co-authored-by: samfreund <samf.236@proton.me>
## Description
On boot, the interface might not be fully configured yet, and the
returned NetworkInterface will be null. This would cause an NPE to be
thrown when attempting to get the MAC address from the interface. This
checks if the interface is null and silently returns an empty string if
it is, which is okay if the networking is being managed because if that
interface is broken, there's bigger problems. Fixes#2244.
## Meta
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## Description
As per the linked issue, raw NT APIs are old and mostly obsolete, this
PR adds user-facing notifications of that.
Closes#1828
## Meta
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Runs the smoketest on each image after we build it in CI. This helps
ensure that we check every image that we build has the requisite JNI
libraries, and that they can be loaded. This is needed cause we've been
breaking that, and our current smoketests don't actually test all our
libraries since some are gated behind platform checks.
## Description
This updates RobotPy and our Python examples to the 2026 beta.
## Meta
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I have all sorts of weird adapters from npcap and Hyper-V that don't
have MAC addresses, so I'm simplifying the logic down so that it always
tries to find _any_ adapter with a MAC address, but attempts to see if
it can find what adapter is in use right now and use the MAC address
from that. This also unpublishes old MAC address topics, which wasn't
done before.
## 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. -->
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Bump to wpilib 2026 beta. This does not bump our pythonlib, as robotpy
hasn't come out yet.
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---------
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
The old GPIO abstraction was replaced with
[`diozero`](https://www.diozero.com), which supports most hardware
running Linux due to its use of GPIO character devices provided by the
Linux kernel. `diozero` also supports [alternate
providers](https://www.diozero.com/concepts/providers.html#providers) if
for some reason the character device API is insufficient. Certain
capabilities outside of the character device API is also implemented for
common hardware.
Custom GPIO commands are implemented via a custom `diozero` provider.
The configuration for custom GPIO will need manually updated according
to the Hardware Config documentation page.
The status LED class was also reworked to support additional statuses or
LED indication types, although none have been added yet.
This was tested on a RPi 5 with LL3 illumination LEDs and an RGB status
led attached. All capabilities worked as expected. All 8 status LED
colors were tested and functional via modifying the code. Basic
functionality of custom GPIO was tested with dummy commands.
## Description
#2224 removed the custom deserializers for `Path`, but we still need one
to be able to deserialize the `Path` key in
`NeuralNetworkPropertyManager`. Additionally, Jackson seems to
auto-convert the `Path` key to a `String` using `toString` instead of
its own serializers, so a custom key serializer is also needed to
consistently use the same format for paths. This also removes unused
serde methods in `JacksonUtils` to minimize potential future churn, and
tacks an `@JsonIgnore` on `getModels` to prevent Jackson from
serializing a `ModelProperty` array into the database.
## Meta
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## Description
PhotonJNICommon is just our implementation of combined runtime loader,
which we don't really need. This removes it and just uses
CombinedRuntimeLoader directly. This also fixes the issues introduced in
#2219, which lead to some of our JNIs not loading.
## Meta
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---------
Co-authored-by: Matt M <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. -->
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This cherry-picks the bug fix from #2225, but not the tests as we're
having issues with those. #2225 will remain open for the tests.
https://github.com/PhotonVision/photonvision/pull/2204 fixed the
off-by-one error on the frontend, but again, because enums are
serialized with ordinal(), DataSocketHandler needed to be updated to
account for the indices shifting by one.
## Meta
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Deferred
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
## Description
<img width="1918" height="1030" alt="image"
src="https://github.com/user-attachments/assets/5af1a5ee-012d-461d-9162-2d4de6ad0c62"
/>
A wireshark dissector can be handy for quickly visualizing time sync
messages. See the docs for how to use this!
Full disclosure -- this dissector was generated by Claude 4.5, and I
spot-checked all the numbers for correctness. This seems like idiomatic
Lua to me, but I don't know Lua at all. I don't see a nice QOL thing
nobody else will use as being a tech debt concern.
## Meta
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## Description
This PR switches image building from `pguyot/arm-runner-action` to
`PhotonVision/photon-image-runner`. The new runner uses native arm
runners on GitHub and is much faster than the emulation used by the
pguyot version.
Images from
a95914ca36
tested and working on:
- [x] RaspberryPi4b
- [x] OrangePi5
- [x] OrangePi5pro
- [x] RubikPi3
Closes#2191
<!-- Any issues this pull request closes or pull requests this
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## Description
#1900 updated how the value was handled in pv-slider, and
unintentionally removed bounds protection. This restores bounds
protection.
Unfortunately, there is an edge case that might be rather difficult to
solve. If the slider is already at the min/max, you can enter a number
through the text field, and while the value won't actually update, the
text field keeps the entered value, likely because the model value
didn't change, and therefore, a rerender isn't triggered. However, this
is an edge case that I doubt many people will actually encounter, so we
should still ship this.
Fixes#2221.
## Meta
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## Description
#2137 made it so `TestUtils.loadLibraries()` loads both WPILib and
photon-targeting, which is used in Main.java to load libraries, but it
left the separate photon-targeting load in Main. This removes the extra
library load, since it's covered by `TestUtils.loadLibraries()`.
## Meta
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is updated
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regenerated and hashes have not changed unexpectedly
- [ ] If this PR touches configuration, this is backwards compatible
with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
We can avoid copying files by chunks just using `Files.copy`. This
should be NFC, just makes the code cleaner
<!-- 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`. -->
## Meta
Merge checklist:
- [x] Pull Request title is [short, imperative
summary](https://cbea.ms/git-commit/) of proposed changes
- [ ] 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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
Updating to take advantage of the now independent mrcal-java (no longer
need to install SuiteSparse and friends!)
## Meta
Merge checklist:
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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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
---------
Co-authored-by: Matt Morley <matthew.morley.ca@gmail.com>
## Description
Removes the checkbox for linting because it's easily invalidated by
later pushes. Also prints a link to the linting docs on CI failure.
## 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_
- [ ] This PR has been
[linted](https://docs.photonvision.org/en/latest/docs/contributing/linting.html).
- [ ] 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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
In the UI, the title for this card is `Global Settings`. This more
closely follows the UI.
## 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_
- [ ] This PR has been
[linted](https://docs.photonvision.org/en/latest/docs/contributing/linting.html).
- [ ] 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
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
#2180 added an additional value to PipelineType.java. Enums are
serialized with `ordinal()`, and the frontend wasn't updated to account
for this, causing an off-by-one error where the UI thought the pipeline
was actually the next pipeline over. This resyncs the enum on the
frontend to the backend and adjusts the mapping from PipelineType to
WebsocketPipelineType to make everything match.
Fixes#2201.
closes#2202
## 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] This PR has been
[linted](https://docs.photonvision.org/en/latest/docs/contributing/linting.html).
- [ ] 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
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with settings back to v2025.3.2
- [x] 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
<!-- 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`. -->
This adds a template modal that can be used for confirming that the user
wants to delete something. The main goal is to reduce complication and
duplicated code, and standardize the way we handle deletion.
closes#2175
## 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] This PR has been
[linted](https://docs.photonvision.org/en/latest/docs/contributing/linting.html).
- [ ] 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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
---------
Co-authored-by: Devolian <devondoyle@outlook.com>
## Description
Camera focus tool pipeline using a Laplacian and finding the variance.
Similar to Limelight.
closes#1597
## 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] This PR has been
[linted](https://docs.photonvision.org/en/latest/docs/contributing/linting.html).
- [x] 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
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with settings back to v2025.3.2
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## Description
Looks like this is the convention from a quick Google search.
## 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_
- [ ] This PR has been
[linted](https://docs.photonvision.org/en/latest/docs/contributing/linting.html).
- [ ] 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
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
Revision of #2164. Instead of only running headless tests during a
build, now only the images are disabled. To reenable showing images, the
`enableTestUi` project property needs to be passed to gradle.
```bash
./gradlew test -PenableTestUi
```
## 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] This PR has been
[linted](https://docs.photonvision.org/en/latest/docs/contributing/linting.html).
- [x] 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
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
Adds the ability to remove old calibrations. This might be helpful if
you have a bad calibration.
closes#1262
## 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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
---------
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
## Description
`.` is a special regex character, which means we weren't actually
matching the `.` in the string, but rather the character before it. This
resulted in the last letter in a model nickname getting cut off on
import. This fix resolves that issue.
## 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] This PR has been
[linted](https://docs.photonvision.org/en/latest/docs/contributing/linting.html).
- [ ] 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
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
Switch default tag family used in AprilTag pipeline. We already
functionally changed the default in
https://github.com/PhotonVision/photonvision/pull/1333 but since 2024
FIRST appears to have been using 36h11 so switching here seems to make
sense as well.
## Meta
Merge checklist:
- [ ] 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 touches photon-serde, all messages have been
regenerated and hashes have not changed unexpectedly
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
---------
Signed-off-by: Jade Turner <spacey-sooty@proton.me>
## Description
This adds documentation for how to lint PhotonVision, as it is not
available elsewhere and people have historically needed to figure it out
for themselves. It also adds an alias for linting PV.
## 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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
<img width="3840" height="2160" alt="image"
src="https://github.com/user-attachments/assets/c0289923-a6c8-48b9-84c1-ce92c7acbc9d"
/>
<img width="3840" height="2160" alt="image"
src="https://github.com/user-attachments/assets/3b58c7d0-e12e-45d6-b328-c3061949349a"
/>
closes#871
## Meta
Merge checklist:
- [x] Pull Request title is [short, imperative
summary](https://cbea.ms/git-commit/) of proposed changes
- [ ] 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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
This replaces boilerplate that checks whether we've successfully sent
the request, whether there was an error, etc.
closes#2151
## Meta
Merge checklist:
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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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
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## Description
This fixes a few problems with the Gradle `build` task and subtasks.
1. Spotless was being run on `node_modules`, resulting in errors for
out-of-source files. This is now disabled.
2. All tests were running from the `build` task, resulting in unexpected
windows popping up. Now only headless tests are run.
3. Headless tests were updated to run from the same root directory as
the other tests.
## 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
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
added a merch store link
## Meta
Merge checklist:
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summary](https://cbea.ms/git-commit/) of proposed changes
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is updated
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regenerated and hashes have not changed unexpectedly
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
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## Description
Detects if a camera mismatch is present in any camera and displays a
banner in the dashboard for better visibility to the user. All detection
occurs in the backend, and is sent to the frontend via use of a mismatch
boolean included in each vision module.
<img width="1235" alt="image"
src="https://github.com/user-attachments/assets/19219a56-c366-4c56-8c4b-cb5a36fe4a04"
/>
Closes#1920
## 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
- [x] If this PR touches configuration, this is backwards compatible
with settings back to v2024.3.1
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
---------
Co-authored-by: Sam Freund <techguy763@gmail.com>
Co-authored-by: samfreund <samf.236@proton.me>
Co-authored-by: Matt Morley <matthew.morley.ca@gmail.com>
## Description
Simple typo fix:
s/Specifc/Specific
## Meta
Merge checklist:
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summary](https://cbea.ms/git-commit/) of proposed changes
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- [x] If this PR changes behavior or adds a feature, user documentation
is updated
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regenerated and hashes have not changed unexpectedly
- [x] If this PR touches configuration, this is backwards compatible
with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [x] If this PR addresses a bug, a regression test for it is added
## Description
When we tagged `v2026.0.0-alpha-1`, we broke the versioning-helper
logic. It doesn't expect `alpha` in the version string. This PR adds
matching for lowercase alphanumeric to the versioning helper, which
resolves that issue.
Also turns out `getProviders()` is now broken as a gradle method. Sad.
## 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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
This allows photon-targeting to be loaded using the same mechanism as
the rest of the WPILib libraries, fixing issues with libraries not being
able to find and load their dependent libraries.
## Meta
Merge checklist:
- [x] Pull Request title is [short, imperative
summary](https://cbea.ms/git-commit/) of proposed changes
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- [x] If this PR changes behavior or adds a feature, user documentation
is updated
- [ ] If this PR touches photon-serde, all messages have been
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with settings back to v2025.3.2
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## Description
There isn't anything that 3D mode adds for OD, and the results are
typically messed up. Thus, we disable 3D mode when we're using an OD
pipeline.
## Meta
Merge checklist:
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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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
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This adds the two missing pose strategies from the java version of
photonlib (Constrained PNP and the Trig solve), to C++ photonlib
---------
Co-authored-by: Matthew Morley <matthew.morley.ca@gmail.com>
## Description
See https://github.com/photonvision/photon-image-modifier/pull/77
## 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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
There was a recent occurance of journalctl logs saying something like
`[66B blob data]`. We don't log anything binary, so journalctl might be
hiding some lines, thinking they're actually binary data when they're
actually plain text. Use `-a` to always log everything. If it's binary
data anyways, we'll want to know what it is anyways. Use `--output cat`
because we output our own timestamps and we don't want journalctl's own
timestamping. Filter the output through `sed` to remove ANSI color codes
to make reading logs easier.
## 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 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
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
#2023 changed how file uploads were handled to use `Files.copy`, but
incorrectly didn't specify the `REPLACE_EXISTING` copy option, causing
file uploads to fail if the file already existed.
## 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
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with settings back to v2025.3.2
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
If there are more than 10 queued results,
PhotonCamera.getAllUnreadResults() would resize two arrays at least once
each.
## 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
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
The version of settings that needs to be compatible is last years, in
this case 2025.
## Meta
Merge checklist:
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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
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with settings back to v2024.3.1
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
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
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with settings back to v2024.3.1
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
It's unused and fails when run, so I'm removing it.
## Meta
Merge checklist:
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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
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with settings back to v2024.3.1
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exchange, the frontend typing is updated
- [ ] If this PR addresses a bug, a regression test for it is added
## Description
After #1991, the program state was always resent in an attempt to
simplify logic, but this had the side effect of causing the settings UI
to reset periodically when the hostname check was performed. This
restores the original logic in #1791 to check for differences in the
conflict state, and to only send the program state if it's changed.
## 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
This prevents jobs from failing on forks of the repo.
Closes#1975.
## Meta
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## Description
Previously, NetworkManager would happily go asking for networkmanager to
do things even if it wasn't installed. This should never be the case,
but we should bail out early if it is regardless IMO. This prevents logs
and the UI from looking suspiciously "working", if you ignore the exit
code. Up for debate if we actually need this feature.
## Meta
Merge checklist:
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---------
Co-authored-by: Craig Schardt <crschardt@fastem.com>
## Description
See #2026 for the previous iteration of this PR.
This adds the RKNN model trained on the COCO dataset as one of the
models shipped with PV. This model is fairly general, and has been
trained to identify a number of objects, including people, animals,
cars, and more. This model is meant for teams to test object detection,
particularly for teams who might not have access to the game elements
that our other models are trained on.
It additionally acknowledges Ultralytics for the model, and includes the
AGPL copyleft license.
## Meta
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## Description
It's nice to be able to filter PRs by what components they've modified.
The 5 labels that have been selected are `frontend`, `backend`,
`documentation`, `photonlib`, and `website`, since those are the primary
components in the monorepo.
## Meta
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This reverts commit 753123844b.
## Description
The COCO dataset contains images that use the NC and/or ND variants of
the CC license, and distributing a model based on that dataset is most
likely a violation of licenses. Additionally, the model is licensed under AGPL,
which might be a concern for PhotonVision, and at a minimum, there's no
license file bundled with the model right now.
## Meta
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## Description
This adds the RKNN model trained on the COCO dataset as one of the
models shipped with PV. This model is fairly general, and has been
trained to identify a number of objects, including people, animals,
cars, and more. This model is meant for teams to test object detection,
particularly for teams who might not have access to the game elements
that our other models are trained on.
## Meta
Merge checklist:
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This adds support for PNP_DISTANCE_TRIG_SOLVE in the the python
PhotonPoseEstimator, mirroring the implementation in the Java
PhotonPoseEstimator.
Changes:
- Add PoseStrategy.PNP_DISTANCE_TRIG_SOLVE
- Add addHeadingData() and resetHeadingData() to PhotonPoseEstimator
- Fix PhotonCameraSim.process() to set ntReceiveTimestampMicros in the
result
- Minor readability improvements to PhotonPipelineResult
- Minor test improvements to PhotonPoseEstimatorTest
- Add .vscode/settings.json (to make running python tests in VSCode
easier)
Merge checklist:
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---------
Co-authored-by: Sam948-byte <samf.236@proton.me>
## Description
Per
https://github.com/PhotonVision/photonvision/pull/1972#issuecomment-3066574742,
camera calibration got broken because I accidently hid the entire
contents of the camera calibration card in #1972. Now, v-show is only
applied to the calibration table so that only the calibration table is
hidden during calibration.
## Meta
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## Description
Fixed the error in the OpenCV/WPILib version checking crash and
clarified it, since it's not PhotonVision that needs updating, but
rather WPILib.
Reported on chief
https://www.chiefdelphi.com/t/opencv-is-version-4-6-0-and-needs-to-be-4-10-0/501751/7
## Meta
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---------
Signed-off-by: Jade Turner <spacey-sooty@proton.me>
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
Publishes metrics to NT using a protobuf under
`photonvision/coprocessors/metrics` using the device host name as the
key.
Refactors metrics to use numbers where possible, instead of strings.
Removes GPU mem display from metrics card when it can't be determined.
Updates UI metrics periodically.
Resolves#1988Closes#830
---------
Co-authored-by: Matt <matthew.morley.ca@gmail.com>
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
## Description
Fixes the amount of cameras and pose estimators reported by usage reporting.
## Meta
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---------
Signed-off-by: Jade Turner <spacey-sooty@proton.me>
fixes#1977
Previously, the logic was checking for the camera object to be the same
as the placeholder camera object. Logic has been changed to check only
the name of the camera object.
## Description
CI will now run whenever a branch is pushed or a PR is opened. Fixes
2027 behaviour and allows running CI on forks
## Meta
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Signed-off-by: Jade Turner <spacey-sooty@proton.me>
## Description
Disable the Alerts test in PhotonCameraTest because it's consistently
failing on Linux.
## Meta
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## Description
Upgrades to Vue 3 and necessary associated dependencies. Also fixes some
issues with the layout and adds validation for object detection models.
Closes#885, closes#1943, closes#1449.
## Meta
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---------
Co-authored-by: Matt M <matthew.morley.ca@gmail.com>
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
Co-authored-by: samfreund <techguy763@gmail.com>
## Description
A common question is the way that people are powering their coprocs when
we're trying to help debug. Therefore, it would be useful to know when
people open a bug report.
## Meta
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---------
Co-authored-by: Matt Morley <matthew.morley.ca@gmail.com>
## Description
closes#1941
Rewrite the API to use the payload method , and use records in the
``RequestHandler``. There's a couple places where this isn't the place,
that's where the front end is making a get request, and so a payload
doesn't make sense.
This is meant to encourage more static typing.
Additionally, fix some typos in params in ``CameraSettingsStore``
## Meta
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- [x] Everything changed got tested
---------
Co-authored-by: Matt Morley <matthew.morley.ca@gmail.com>
## 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
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## Description
Added a warning about non-quantized custom models not being supported,
and a note about not being able to delete models from the GUI once
they're uploaded to the coprocessor.
---------
Co-authored-by: Sam Freund <techguy763@gmail.com>
## Description
WAS: Logs did not have a leading zero, meaning that alphabetical and
temporal sort were not the same
IS: Logs now have leading zeros added. This means that alphabetical sort
works properly.
## Meta
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---------
Co-authored-by: Craig Schardt <crschardt@fastem.com>
This reverts commit a4295275ed.
## Description
This commit broke the FPS counter because I forgot to start the timer. I
could just use `restart`, and then it would only be wrong for the very
first pipeline run, but that's a hack, and frankly, the old way was
fine.
## Meta
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## Description
Adds docs about the new logging added in 1923
## Meta
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QuirkyCamera was refactored to use EnumMap, since that seems to be more efficient. This also enables more concise copying of QuirkyCamera in getQuirkyCamera by just passing in the Map of the QuirkyCamera. Also, putAll was used instead of manually copying quirks in updateQuirks for conciseness.
In places like pipelines or DataSocketHandler, objects were being instantiated and assigned to a variable, but were then passed into a method, never to be used again. For pipelines especially, that style of code wasn't always consistently used, and other pipelines skipped assignment and instantiated objects in the method call. Make everything consistent by always instantiating in the method call. GenericUSBCameraSettables also had an unnecessary assignment, and that was cleaned up too for readability.
Matt says this was for mmal, and we use libcamera now, so this is unnecessary now. Also, the filtering logic that used blacklistedResIndices was completely broken.
## Description
Updates the PhotonPoseEstimator programming documentation page to
reflect the new PhotonPoseEstimator. and add a more comprehensive
step-by-step tutorial using code from the PV Pose Estimation examples.
Updates various code examples to ensure they are matching the latest
documentation or example code on GitHub.
This PR is a successor of, and therefore closes#1765.
This PR is blocked by #1706, as the linked PR updates examples.
Closes#1757 and closes#1800 and closes#1632 and closes#1773 and
closes#1465.
## Meta
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---------
Co-authored-by: Kevin Reas <76408202+PaarkG@users.noreply.github.com>
Co-authored-by: Matt Morley <matthew.morley.ca@gmail.com>
## Description
Updates best practices in the documentation. Include more information on
how to get a camera stream into a driver dashboard.
## Meta
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## Description
Adds documentation for driver mode because it currently isn't
documented.
Closes#1824
## Meta
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---------
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
Co-authored-by: Sam Freund <techguy763@gmail.com>
## Description
Fixed a bug where rotated camera distortion coefficient arrays and
rotated camera intrensic arrays were 8x bigger than they were supposed
to be. The root cause was because of how the data from JsonMatOfDouble
was being handled. A Mat was pulled out, then modified, then a new
JsonMatOfDouble was made from the Mat. This required a conversion from a
Mat to a Java array. The array was incorrectly sized as `elements *
bytes`, when it should've just been `elements`. Due to some uncertainty
as to the types of Mats passed into JsonMatOfDouble.fromMat, the
expected Mat type has been explicitly documented. The added regression
test rotates the calibration data 4 times, equivalent to not rotating at
all. This should mean the arrays are equal, and that is what we check.
Additionally fixes a bug when rotating 180 degrees that flipped width
and height
## Meta
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---------
Co-authored-by: Matt <matthew.morley.ca@gmail.com>
## Description
https://github.com/PhotonVision/photonvision/pull/884 says that PRs that
update pipeline settings or anything related to data exchange should
update the typing in the frontend as well, but that's not on the
checklist. Add it to ensure we don't miss it.
## Meta
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There was a minor spelling mistake in the calibration documentation
"Ensure your the images" changed to be "ensure the images"
## Meta
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## Description
Rename some of the workflows and the steps within the workflows to
provide further clarity as to what they affect. Additionally, rename the
RtD workflow file to differentiate it from the javadocs/doxygen
workflow.
closes#1880
## Meta
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closes#1825
The new radio has four ethernet ports, and one dedicated port for the
DS. There's no reason for teams to tether to the roborio via USB-B, and
tethering via radio will provide more realistic match conditions.
Therefore, recommend tethering via radio.
Merge checklist:
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## Description
We forgot to go to the correct directory prior to running ``npm ci``, so
now I'm adding it.
PROOF: see the passing website test
## Meta
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---------
Co-authored-by: Gold856 <117957790+Gold856@users.noreply.github.com>
## Description
Monorepos the [landing website](https://photonvision.org)
## Meta
Merge checklist:
- [x] @mcm001 migrates all the secrets over to this repo
- [x] Add label for website stuff
- [ ] Archive the old website repo
- [x] Website gets cleaned up
## Description
Balena Etcher has historically had issues like bootlooping. Recommend
Raspberry Pi Imager instead and warn about using Balena Etcher.
Closes#1856.
## Meta
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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 addresses a bug, a regression test for it is added
closes#1720
Many teams have issues with their Arducams randomly disconnecting, so
we're adding some documentation on how to try and resolve that.
## 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
- [X] If this PR touches photon-serde, all messages have been
regenerated and hashes have not changed unexpectedly
- [X] If this PR touches configuration, this is backwards compatible
with settings back to v2024.3.1
- [X] If this PR addresses a bug, a regression test for it is added
## Description
Added paranoia checks to satisfy @Gold872
## 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
- [x] If this PR addresses a bug, a regression test for it is added
## Description
Switches a dead link to VividHosting's page about passive PoE to one
that actually works.
Fixes#1842.
## 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 addresses a bug, a regression test for it is added
## Description
instead of using camera calibration, the CasADi problem formulation now
expect the caller to provide "normalized pixel coordinates". This
reduces the number of floating point operations we need to perform (and
reduces total LOC by 6%). `casadi_wrapper.cpp` now converts from (u, v)
coordinates to normalized (x'', y'') coordinates with:
x'' = (u - c_x) / f_x
y'' = (u - c_y) / f_y
Which is the inverse of this (from [opencv
docs](https://docs.opencv.org/4.x/d9/d0c/group__calib3d.html), and
assuming no distortion):

In my testing, this is ~16% faster on my x86 laptop. Would love some rio
benchmarks.
## 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 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
Fixes#1472. TTF fonts were included as part of the FontAwesome kit, but
I opted to not add them because basically every browser won't use them
and it just pollutes the repo.
Everything under the `photon-lib` directory is intended to all be
licensed under MIT:
e40c8fbca0/photon-lib/.styleguide-license (L2)
Presumably we don't want to force teams to release their robot code
under GPL.
Somebody wanted a description, so here I am.
This PR fixes an error which caused the discoverModels function to be
rerun after each upload of a new model, but without clearing the list of
available models. This causes any models that were on the list prior to
the import to be duplicated. This PR also makes it so that uploading a
model automatically updates the list of available models.
---------
Co-authored-by: Matt Morley <matthew.morley.ca@gmail.com>
Co-authored-by: Chris Gerth <gerth2@users.noreply.github.com>
The following deprecation warnings have been fixed:
- `SwerveModuleState.optimize(desiredState, currentRotation);`, which is
now an instance method
- `AprilTagFields.kDefaultField.loadAprilTagLayoutField();`, which is
now `AprilTagFieldLayout.loadField(AprilTagFields.kDefaultField);`
WIP:
- [x] C++
- [x] Python
This PR implements several refinements to the way that NetworkManager
controls the network interface.
- The monitor detects and logs changes to the network address
- The monitor detects and logs changes to the connection and will
reinitialize the connection if needed
- Remove NetworkInterface.java class, which wasn't used anywhere
- Use java.net.NetworkInterface to get IP addresses for any interface
(device)
- Adds a metric for the current IP address (address on the currently
selected interface)
This PR changes the text input fields to allow a user to type in a value and press enter (or click away) before the UI registers the updated value. It makes text input behave in a more expected manner. The spin buttons are no longer shown for the text box. Instead, there are up and down buttons on either side of the slider.
The only thing that I can't figure out is a way to make the up and down buttons continuously increment (decrement) the value if you click and hold. I'm not sure that this is required, but if someone wants to propose a solution, please add it to this PR.
In softprops/action-gh-release, when using an glob pattern to exclude files, all of the files to exclude must be specified on one line. Splitting them to multiple lines causes all files to match one of the two lines.
To combine on one line, use `|` between the patterns.
Selective builds breaks my ability to require that checks pass before
merging. It's not worth the bite for very few docs-only PRs, given
github limitations on needing to skip INDIVIDUAL JOB STEPS on required
CI jobs.
Maybe we should move to gitlab 💀
This fixes a bug introduced in #1592 that caused the Manage Device
Networking toggle to be disabled for systems where PhotonVision is
managing the network.
There is still a problem with the toggle defaulting to "off" and not
staying in the "on" position after settings are saved. I need help from
someone who understands the frontend to figure out why it keeps getting
set back to "off".
---------
Co-authored-by: Matt <matthew.morley.ca@gmail.com>
Co-authored-by: Cameron (3539) <theforgelover@gmail.com>
If the exposure property for the generic USB camera settable was not
valid for one camera in the list, then the thread would crash/hang and
no cameras would show up in the list
It wasn't hard to not notice or skip over the recommendation, or just
not take it seriously. So I added some banners to direct people to read
the quick start guide, and a banner to heavily suggest using an
industrial SD card, since they're just the best thing available right
now.
Occasionally, the sim projects are capable of simulating current draw of
over 600A, which triggers a condition in
`BatterySim::calculateDefaultBatteryLoadedVoltage` that limits the
minimum measured battery voltage to 0V (to prevent it from going
negative).
When battery voltage measures 0, this causes NaN values to propagate
through the drivetrain model, making sim inoperable. Specifically, [this
is the
line](https://github.com/PhotonVision/photonvision/blob/master/photonlib-java-examples/aimandrange/src/main/java/frc/robot/subsystems/drivetrain/SwerveDriveSim.java#L452)
that causes the initial NaN values in simulation.
This PR is posed as a patch to ensure that simulation doesn't break.
This fixes mostly formatting issues so there is no longer any diff with
things after rerunning the generation script. Yes, most of this can be
fixed by running wpiformat but that doesn't exist as a pre-commit hook
atm, so I think this is nicer.
It also removes any reference to the java encode/decode within the
python message gen
WAS: we used raw hash-maps to encode program state
S/B: we use Jackson to do this encoding for us for free. We have
Objects, and we should use them to represent structured data.
---------
Co-authored-by: Craig Schardt <crschardt@fastem.com>
Fixes#1564. Also copies vendordep JSONs to the examples as advised by
Thad. Removes unused shared/javacpp/setupBuild.gradle. Also removes
unnecessary `chmod +x gradlew` from CI workflows.
Provide instructions for installing the PhotonVision version that is
compatible with WPILibPi 2023.4.2, which is the newest version available
for the Romi.
The older text is hidden in a comment so that it can be restored when
there is a newer version of WPILibPi that is compatible with newer
versions of PhotonVision.
What it says on the tin. This is all stuff from our initial effort to
port the sim things. Right now it is coupled to #1557 because this fixes
things up in that. Lets merge that one before dealing with this one
This uses the version of libcamera-gl-driver that was built using our
image. This assumes
the correct update path of the pi image version to libcamera to
photonvision.
I tasked my team with updating our upcoming Reefscape codebase to target
2025 packages, only to realise we have created an unsolvable dependency
nightmare with these things being neglected...
Signal/noise ratio is too low with this enabled. When dealing with #1567
I got ~46000 lines of errors going around in a circle rather than just
an import failure at the scope of each failed test
about: Something needs to be documented/updated in the documentation
title: ''
labels: documentation
assignees: ''
---
**Are you requesting documentation for a new feature, or updated documentation for an old feature?**
Put the feature you are requesting documentation for here, along with whether the documentation is stale and needs to be updated, or whether the documentation does not exist, and needs to be created.
**Where is it?**
Put the location of the documentation that needs to be updated here. If you're requesting documenation for a new feature, put where you think it should go.
**Additional context**
Add any other context or screenshots about the feature request here.
What changed? Why? (the code + comments should speak for itself on the "how")
Include fun testing screenshots or a cool video, to collect test evidence in a place where we can later reference it. Including proof this change was tested makes reviewing easier, helps us make sure we tested all our edge cases, and helps provide context for the future.
Any issues this pull request closes or pull requests this supersedes should be linked with `Closes #issuenumber`.
## Meta
Merge checklist:
- [ ] Pull Request title is [short, imperative summary](https://cbea.ms/git-commit/) of proposed changes
- [ ] The description documents the _what_ and _why_, including events that led to this PR
- [ ] 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 all settings going back to the previous seasons's last release (seasons end after champs ends)
- [ ] 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
- [ ] If this PR adds a dependency, the license has been checked for compatibility and steps taken to follow it
PhotonVision is the free, fast, and easy-to-use computer vision solution for the *FIRST* Robotics Competition. You can read an overview of our features [on our website](https://photonvision.org). You can find our comprehensive documentation [here](https://docs.photonvision.org).
@@ -8,22 +8,22 @@ The latest release of platform-specific jars and images is found [here](https://
If you are interested in contributing code or documentation to the project, please [read our getting started page for contributors](https://docs.photonvision.org/en/latest/docs/contributing/index.html) and **[join the Discord](https://discord.gg/wYxTwym) to introduce yourself!** We hope to provide a welcoming community to anyone who is interested in helping.
## Documentation
- Our main documentation page: [docs.photonvision.org](https://docs.photonvision.org)
- C++ Doxygen [cppdocs.photonvision.org](https://cppdocs.photonvision.org) (or [manual link](https://photonvision.github.io/photonvision/built-docs/doxygen/html/))
## Building
Gradle is used for all C++ and Java code, and NPM is used for the web UI. Instructions to compile PhotonVision yourself can be found [in our docs](https://docs.photonvision.org/en/latest/docs/contributing/building-photon.html#compiling-instructions).
Gradle is used for all C++ and Java code, and pnpm is used for the web UI. Instructions to compile PhotonVision yourself can be found [in our docs](https://docs.photonvision.org/en/latest/docs/contributing/building-photon.html#compiling-instructions).
You can run one of the many built in examples straight from the command line, too! They contain a fully featured robot project, and some include simulation support. The projects can be found inside the [`photonlib-java-examples`](photonlib-java-examples) and [`photonlib-cpp-examples`](photonlib-cpp-examples) subdirectories, respectively. Instructions for running these examples directly from the repo are found [in the docs](https://docs.photonvision.org/en/latest/docs/contributing/building-photon.html#running-examples).
@@ -32,50 +32,47 @@ You can run one of the many built in examples straight from the command line, to
Note that these are case sensitive!
*`-PArchOverride=foobar`: builds for a target system other than your current architecture. [Valid overrides](https://github.com/wpilibsuite/wpilib-tool-plugin/blob/main/src/main/java/edu/wpi/first/tools/NativePlatforms.java) are:
* winx32
* winx64
* winx86-64
* winarm64
* macx64
* macx86-64
* macarm64
* linuxx64
* linuxx86-64
* linuxarm64
* linuxathena
-`-PtgtIP`: Specifies where `./gradlew deploy` should try to copy the fat JAR to
-`-PtgtUser`: Specifies custom username for `./gradlew deploy` to SSH into
-`-PtgtPw`: Specifies custom password for `./gradlew deploy` to SSH into
-`-Pprofile`: enables JVM profiling
-`-PwithSanitizers`: On Linux, enables `-fsanitize=address,undefined,leak`
If you're cross-compiling, you'll need the wpilib toolchain installed. This can be done via Gradle: for example `./gradlew installArm64Toolchain` or `./gradlew installRoboRioToolchain`
If you're cross-compiling, you'll need the WPILib toolchain installed. This must be done via Gradle: for example `./gradlew installArm64Toolchain` or `./gradlew installSystemCoreToolchain`
## Out-of-Source Dependencies
PhotonVision uses the following additional out-of-source repositories for building code.
- Base system images for Raspberry Pi & Orange Pi: https://github.com/PhotonVision/photon-image-modifier
- Base system images for supported coprocessors: https://github.com/PhotonVision/photon-image-modifier
- C++ driver for Raspberry Pi CSI cameras: https://github.com/PhotonVision/photon-libcamera-gl-driver
- JNI code for [mrcal](https://mrcal.secretsauce.net/): https://github.com/PhotonVision/mrcal-java
-Custom build of OpenCV with GStreamer/Protobuf/other custom flags: https://github.com/PhotonVision/thirdparty-opencv
- JNI code for aruco-nano: https://github.com/PhotonVision/aruconano-jni
## Additional packages
For now, using mrcal requires installing these additional packages on Linux systems:
-JNI code for RKNN: https://github.com/PhotonVision/rknn_jni
- JNI code for Rubik Pi NPU: https://github.com/PhotonVision/rubik_jni
## Acknowledgments
PhotonVision was forked from [Chameleon Vision](https://github.com/Chameleon-Vision/chameleon-vision/). Thank you to everyone who worked on the original project.
* [WPILib](https://github.com/wpilibsuite) - Specifically [cscore](https://github.com/wpilibsuite/allwpilib/tree/master/cscore), [CameraServer](https://github.com/wpilibsuite/allwpilib/tree/master/cameraserver), [NTCore](https://github.com/wpilibsuite/allwpilib/tree/master/ntcore), and [OpenCV](https://github.com/wpilibsuite/thirdparty-opencv).
* [Apache Commons](https://commons.apache.org/) - Specifically [Commons Math](https://commons.apache.org/proper/commons-math/), and [Commons Lang](https://commons.apache.org/proper/commons-lang/)
* [WPILib](https://github.com/wpilibsuite) - Specifically [allwpilib](https://github.com/wpilibsuite/allwpilib) and [their build of OpenCV](https://github.com/wpilibsuite/thirdparty-opencv).
* [Apache Commons](https://commons.apache.org/) - Specifically [Commons IO](https://commons.apache.org/proper/commons-io/), and [Commons CLI](https://commons.apache.org/proper/commons-cli/)
- Ensure you have spares of the relevant electronics if you can afford it (switch, coprocessor, cameras, etc.).
-Download the latest release .jar onto your computer and update your Pi if necessary (only update if the release is labeled "critical" or similar, we do not recommend updating right before an event in case there are unforeseen bugs).
-Test out PhotonVision at your home setup.
-Ensure that you have set up SmartDashboard / Shuffleboard to view your camera streams during matches.
-Follow all the recommendations under the Networking section in installation (network switch and static IP).
-Use high quality ethernet cables that have been rigorously tested.
-Set up port forwarding using the guide in the Networking section in installation.
-Stay on the latest version of PhotonVision until you have tested your full robot system to be functional.
-Some time before the competition, lock down the version you are using and do not upgrade unless you encounter a critical bug.
-Have a copy of the installation image for the version you are using on your programming laptop, in case re-imaging (without internet) is needed.
-Extensively test at your home setup. Practice tuning from scratch under different lighting conditions.
-Confirm you have followed all the recommendations under the {ref}`Networking<docs/quick-start/networking:Networking>` documentation (network switch and static IP).
-Only use high quality ethernet cables that have been rigorously tested.
## Camera Streaming
- All camera streams are published under the NetworkTables table `CameraPublisher`.
- The only subtable under `CameraPublisher` that will work for viewing a driver mode camera stream is the one that contains `Output` in the name.
- To view a camera stream in a dashboard, drag the correct subtable from the NetworkTables tree into your dashboard.
- Use the latest driver dashboard recommended by [WPILib](https://docs.wpilib.org/en/stable/docs/software/dashboards/dashboard-intro.html) on your driver station laptop.
## During the Competition
-Make sure you take advantage of the field calibration time given at the start of the event:
- Bring your robot to the field at the allotted time.
-Turn on your robot and pull up the dashboard on your driver station.
-Point your robot at the AprilTags(s) and ensure you get a consistent tracking (you hold one AprilTag consistently, the ceiling lights aren't detected, etc.).
-If you have problems with your pipeline, go to the pipeline tuning section and retune the pipeline using the guide there.
-Move the robot close, far, angled, and around the field to ensure no extra AprilTags are found.
-Go to a practice match to ensure everything is working correctly.
-Use the field calibration time given at the start of the event:
- Bring your robot to the field at the allotted time.
-Make sure the field has match-accurate lighting conditions active.
-Turn on your robot and pull up the dashboard on your driver station.
-Point your robot at the targets and ensure you get a consistent tracking (you hold one targets consistently, the ceiling lights aren't detected, etc.).
-If you have problems with your pipeline, retune the pipeline following the {ref}`camera tuning <docs/pipelines/input:Camera Tuning / Input>` documentation.
-Move the robot close, far, angled, and around the field to ensure no extra targets are found.
- Monitor camera feeds during a practice match to ensure everything is working correctly.
- After field calibration, use the "Export Settings" button in the "Settings" page to create a backup.
- Do this for each coprocessor on your robot that runs PhotonVision, and name your exports with meaningful names.
- This will contain camera information/calibration, pipeline information, network settings, etc.
- In the event of software/hardware failures (IE lost SD Card, broken device), you can then use the "Import Settings" button and select "All Settings" to restore your settings.
- This effectively works as a snapshot of your PhotonVision data that can be restored at any point.
- Before every match, check the ethernet connection going into your coprocessor and that it is seated fully.
-Ensure that exposure is as low as possible and that you don't have the dashboard up when you don't need it to reduce bandwidth.
- Do this for each coprocessor on your robot that runs PhotonVision, and name your exports with meaningful names.
- This will contain camera information/calibration, pipeline information, network settings, etc.
- In the event of software/hardware failures (IE lost SD Card, broken device), you can then use the "Import Settings" button and select "All Settings" to restore your settings.
- This effectively works as a snapshot of your PhotonVision data that can be restored at any point.
- Before every match:
-Check the ethernet and USB connectors are seated fully.
- Close streaming dashboards when you don't need them to reduce bandwidth.
- Stream at as low of a resolution as possible while still detecting AprilTags to stay within field bandwidth limits.
PhotonVision stores and loads settings in the {code}`photonvision_config` directory, in the same folder as the PhotonVision JAR is stored. On the Pi image as well as the Gloworm, this is in the {code}`/opt/photonvision` directory. The contents of this directory can be exported as a zip archive from the settings page of the interface, under "export settings". This export will contain everything detailed below. These settings can later be uploaded using "import settings", to restore configurations from previous backups.
PhotonVision stores and loads settings in the {code}`photonvision_config` directory, in the same folder as the PhotonVision JAR is stored. On supported hardware, this is in the {code}`/opt/photonvision` directory. The contents of this directory can be exported as a zip archive from the settings page of the interface, under "export settings". This export will contain everything detailed below. These settings can later be uploaded using "import settings", to restore configurations from previous backups.
## Directory Structure
@@ -12,20 +12,20 @@ The directory structure is outlined below.
```
- calibImgs
- Images saved from the last run of the calibration routine
- Images saved from the last run of the calibration routine
- cameras
- Contains a subfolder for each camera. This folder contains the following files:
- pipelines folder, which contains a {code}`json` file for each user-created pipeline.
- config.json, which contains all camera-specific configuration. This includes FOV, pitch, current pipeline index, and calibration data
- drivermode.json, which contains settings for the driver mode pipeline
- Contains a subfolder for each camera. This folder contains the following files:
- pipelines folder, which contains a {code}`json` file for each user-created pipeline.
- config.json, which contains all camera-specific configuration. This includes FOV, pitch, current pipeline index, and calibration data
- drivermode.json, which contains settings for the driver mode pipeline
- imgSaves
- Contains images saved with the input/output save commands.
- Contains images saved with the input/output save commands.
- logs
- Contains timestamped logs in the format {code}`photonvision-YYYY-MM-D_HH-MM-SS.log`. Note that on Pi or Gloworm these timestamps will likely be significantly behind the real time.
- Contains timestamped logs in the format {code}`photonvision-YYYY-MM-D_HH-MM-SS.log`. These timestamps will likely be significantly behind the real time. Coprocessors on the robot have no way to get current time.
- hardwareSettings.json
- Contains hardware settings. Currently this includes only the LED brightness.
- Contains hardware settings. Currently this includes only the LED brightness.
- networkSettings.json
- Contains network settings, including team number (or remote network tables address), static/dynamic settings, and hostname.
- Contains network settings, including team number (or remote network tables address), static/dynamic settings, and hostname.
## Importing and Exporting Settings
@@ -41,10 +41,13 @@ The entire settings directory can be exported as a ZIP archive from the settings
A variety of files can be imported back into PhotonVision:
- ZIP Archive ({code}`.zip`)
- Useful for restoring a full configuration from a different PhotonVision instance.
- Useful for restoring a full configuration from a different PhotonVision instance.
- Single Config File
- Currently-supported Files
- {code}`hardwareConfig.json`
- {code}`hardwareSettings.json`
- {code}`networkSettings.json`
- Useful for simple hardware or network configuration tasks without overwriting all settings.
- Currently-supported Files
- {code}`hardwareConfig.json`
- {code}`hardwareSettings.json`
- {code}`networkSettings.json`
- Useful for simple hardware or network configuration tasks without overwriting all settings.
PhotonVision interfaces with PhotonLib, our vendor dependency, using NetworkTables. If you are running PhotonVision on a robot (ie. with a RoboRIO), you should **turn the NetworkTables server switch (in the settings tab) off** in order to get PhotonLib to work. Also ensure that you set your team number. The NetworkTables server should only be enabled if you know what you're doing!
PhotonVision's NetworkTables API is not designed for robot consumption, only internal at-a-glance debugging.**
:::
**Use PhotonLib instead, as the NetworkTables API is not supported for robot consumption.**
## API
:::{warning}
NetworkTables is not a supported setup/viable option when using PhotonVision as we only send one target at a time (this is problematic when using AprilTags, which will return data from multiple tags at once). We recommend using PhotonLib.
:::
The tables below contain the the name of the key for each entry that PhotonVision sends over the network and a short description of the key. The entries should be extracted from a subtable with your camera's nickname (visible in the PhotonVision UI) under the main `photonvision` table.
### Getting Target Information
@@ -62,9 +62,3 @@ These entries are global, meaning that they should be called on the main `photon
| `ledMode` | `int` | Sets the LED Mode (-1: default, 0: off, 1: on, 2: blink) |
:::{warning}
Setting the LED mode to -1 (default) when `multiple` cameras are connected may result in unexpected behavior. {ref}`This is a known limitation of PhotonVision. <docs/troubleshooting/common-errors:LED Control>`
Single camera operation should work without issue.
This page will help you install PhotonVision on your coprocessor, wire it, and properly setup the networking in order to start tracking targets.
This page will help you install PhotonVision on non-supported coprocessor.
## Step 1: Software Install
@@ -14,25 +14,5 @@ You only need to install PhotonVision on the coprocessor/device that is being us
:maxdepth: 3
sw_install/index
updating
```
## Step 2: Wiring
This section will walk you through how to wire your coprocessor to get power.
```{toctree}
:maxdepth: 1
wiring
```
## Step 3: Networking
This section will walk you though how to connect your coprocessor to a network. This section is very important (and easy to get wrong), so we recommend you read it thoroughly.
Pre-release/development version of PhotonVision can be tested by installing/downloading artifacts from Github Actions (see below), which are built automatically on commits to open pull requests and to PhotonVision's `main` branch, or by {ref}`compiling PhotonVision locally <docs/contributing/building-photon:Build Instructions>`.
:::{warning}
If testing a pre-release version of PhotonVision with a robot, PhotonLib must be updated to match the version downloaded! If not, packet schema definitions may not match and unexpected things will occur. To update PhotonLib, refer to {ref}`installing specific version of PhotonLib<docs/programming/photonlib/adding-vendordep:Install Specific Version - Java/C++>`.
:::
GitHub Actions builds pre-release version of PhotonVision automatically on PRs and on each commit merged to main. To test a particular commit to main, navigate to the [PhotonVision commit list](https://github.com/PhotonVision/photonvision/commits/main/) and click on the check mark (below). Scroll to "Build / Build fat JAR - PLATFORM", click details, and then summary. From here, JAR and image files can be downloaded to be flashed or uploaded using "Offline Update".
```{image} images/gh_actions_1.png
:alt: Github Actions Badge
```
```{image} images/gh_actions_2.png
:alt: Github Actions artifact list
```
Built JAR files (but not image files) can also be downloaded from PRs before they are merged. Navigate to the PR in GitHub, and select Checks at the top. Click on "Build" to display the same artifact list as above.
@@ -8,14 +8,14 @@ You do not need to install PhotonVision on a Windows PC in order to access the w
## Installing Java
PhotonVision requires a JDK installed and on the system path. JDK 11 is needed (different versions will not work). If you don't have JDK 11 already, run the following to install it:
PhotonVision requires a JDK installed and on the system path. JDK 17 is needed (different versions will not work). If you don't have JDK 17 already, run the following to install it:
```
$ sudo apt-get install openjdk-11-jdk
$ sudo apt-get install openjdk-17-jdk
```
:::{warning}
Using a JDK other than JDK11 will cause issues when running PhotonVision and is not supported.
Using a JDK other than JDK17 will cause issues when running PhotonVision and is not supported.
:::
## Downloading the Latest Stable Release of PhotonVision
@@ -25,7 +25,7 @@ Go to the [GitHub releases page](https://github.com/PhotonVision/photonvision/re
:::{note}
If your coprocessor has a 64 bit ARM based CPU architecture (OrangePi, Raspberry Pi, etc.), download the LinuxArm64.jar file.
If your coprocessor has an 64 bit x86 based CPU architecture (Mini PC, laptop, etc.), download the Linuxx64.jar file.
If your coprocessor has an 64 bit x86 based CPU architecture (Mini PC, laptop, etc.), download the Linuxx86-64.jar file.
Your co-processor will require an Internet connection for this process to work correctly.
:::
For installation on any other co-processors, we recommend reading the {ref}`advanced command line documentation <docs/installation/sw_install/advanced-cmd:Advanced Command Line Usage>`.
For installation on any other co-processors, we recommend reading the {ref}`advanced command line documentation <docs/advanced-installation/sw_install/advanced-cmd:Advanced Command Line Usage>`.
## Updating PhotonVision
PhotonVision can be updated by downloading the latest jar file, copying it onto the processor, and restarting the service.
For example, from another computer, run the following commands. Substitute the correct username for "\[user\]" (e.g. Raspberry Pi uses "pi", Orange Pi uses "orangepi".)
For example, from another computer, run the following commands. Substitute the correct username for "\[user\]" ( Provided images use username "pi")
The [Romi](https://docs.wpilib.org/en/latest/docs/romi-robot/index.html) is a small robot that can be controlled with the WPILib software. The main controller is a Raspberry Pi that must be imaged with [WPILibPi](https://docs.wpilib.org/en/latest/docs/romi-robot/imaging-romi.html) .
## Installation
The WPILibPi image includes FRCVision, which reserves USB cameras; to use PhotonVision, we need to edit the `/home/pi/runCamera` script to disable it. First we will need to make the file system writeable; the easiest way to do this is to go to `10.0.0.2` and choose "Writable" at the top.
SSH into the Raspberry Pi (using Windows command line, or a tool like [Putty](https://www.chiark.greenend.org.uk/~sgtatham/putty/) ) at the Romi's default address `10.0.0.2`. The default user is `pi`, and the password is `raspberry`.
:::.. The following paragraph can be restored when WPILibPi becomes compatible with the current version of PhotonVision.
:::.. Follow the process for installing PhotonVision on {ref}`"Other Debian-Based Co-Processor Installation" <docs/advanced-installation/sw_install/other-coprocessors:Other Debian-Based Co-Processor Installation>`. As it mentions, this will require an internet connection so connecting the Raspberry Pi to an internet-connected router via an Ethernet cable will be the easiest solution. The pi must remain writable while you are following these steps!
:::..Temporary instructions explaining how to install the older version of PhotonVision on a Romi. Remove when no longer needed.
:::{attention}
The version of WPILibPi for the Romi is 2023.2.1, which is not compatible with the current version of PhotonVision. **If you are using WPILibPi 2023.2.1 on your Romi, you must install PhotonVision v2023.4.2 or earlier!**
To install a compatible version of PhotonVision, enter these commands in the SSH terminal connected to the Raspberry Pi. This will download and run the install script, which will install PhotonVision on your Raspberry Pi and configure it to run at startup.
```bash
$ wget https://git.io/JJrEP -O install.sh
$ sudo chmod +x install.sh
$ sudo ./install.sh -v v2023.4.2
```
The install script requires an internet connection, so connecting the Raspberry Pi to an internet-connected router via an Ethernet cable will be the easiest solution. The pi must remain writable while you are following these steps!
:::
:::..End of temporary instructions.
Next, from the SSH terminal, run `sudo nano /home/pi/runCamera` then arrow down to the start of the exec line and press "Enter" to add a new line. Then add `#` before the exec command to comment it out. Then, arrow up to the new line and type `sleep 10000`. Hit "Ctrl + O" and then "Enter" to save the file. Finally press "Ctrl + X" to exit nano. Now, reboot the Romi by typing `sudo reboot now`.
```{image} images/nano.png
```
After the Romi reboots, you should be able to open the PhotonVision UI at: [`http://10.0.0.2:5800/`](http://10.0.0.2:5800/). From here, you can adjust settings and configure {ref}`Pipelines <docs/pipelines/index:Pipelines>`.
:::{warning}
In order for settings, logs, etc. to be saved / take effect, ensure that PhotonVision is in writable mode.
:::
:::{attention}
When using an older version of PhotonVision, the user interface and features may be different than what appears in the online documentation. The [Documentation](http://10.0.0.2:5800/#/docs) link in the User Interface will open a bundled version of the documentation that matches the PhotonVision version running on your coprocessor.
@@ -12,15 +12,11 @@ Bonjour provides more stable networking when using Windows PCs. Install [Bonjour
## Installing Java
PhotonVision requires a JDK installed and on the system path. **JDK 11 is needed** (different versions will not work). You may already have this if you have installed WPILib, but ensure that running `java -version` shows JDK 11. If not, [download and install it from here](https://adoptium.net/temurin/releases?version=11) and ensure that the new JDK is being used.
:::{warning}
Using a JDK other than JDK11 will cause issues when running PhotonVision and is not supported.
:::
PhotonVision requires a JDK installed and on the system path. **JDK 17 is needed.** You may already have it if you installed WPILib, but ensure that running `java -version` shows JDK 17. You will likely have to add WPILib's JDK to JAVA_HOME and the JDK's `bin` directory to PATH. If you do not have a JDK 17 install, [download and install it from here.](https://adoptium.net/temurin/releases?version=17)
## Downloading the Latest Stable Release of PhotonVision
Go to the [GitHub releases page](https://github.com/PhotonVision/photonvision/releases) and download the winx64.jar file.
Go to the [GitHub releases page](https://github.com/PhotonVision/photonvision/releases) and download the winx86-64.jar file.
Before you get started tracking AprilTags, ensure that you have followed the previous sections on installation, wiring and networking. Next, open the Web UI, go to the top right card, and switch to the "AprilTag" or "Aruco" type. You should see a screen similar to the one below.
Before you get started tracking AprilTags, ensure that you have followed the previous sections on installation, wiring and networking. Next, open the Web UI, go to the top right card, and switch to the "AprilTag" or "ArUco" type. You should see a screen similar to the one below.
```{image} images/apriltag.png
:align: center
@@ -12,7 +12,7 @@ You are now able to detect and track AprilTags in 2D (yaw, pitch, roll, etc.). I
## Tuning AprilTags
AprilTag pipelines come with reasonable defaults to get you up and running with tracking. However, in order to optimize your performance and accuracy, you must tune your AprilTag pipeline using the settings below. Note that the settings below are different between the AprilTag and Aruco detectors but the concepts are the same.
AprilTag pipelines come with reasonable defaults to get you up and running with tracking. However, in order to optimize your performance and accuracy, you must tune your AprilTag pipeline using the settings below. Note that the settings below are different between the AprilTag and ArUco detectors but the concepts are the same.
```{image} images/apriltag-tune.png
:align: center
@@ -21,7 +21,9 @@ AprilTag pipelines come with reasonable defaults to get you up and running with
### Target Family
Target families are defined by two numbers (before and after the h). The first number is the number of bits the tag is able to encode (which means more tags are available in the respective family) and the second is the hamming distance. Hamming distance describes the ability for error correction while identifying tag ids. A high hamming distance generally means that it will be easier for a tag to be identified even if there are errors. However, as hamming distance increases, the number of available tags decreases. The 2024 FRC game will be using 36h11 tags, which can be found [here](https://github.com/AprilRobotics/apriltag-imgs/tree/master/tag36h11).
Target families are defined by two numbers (before and after the h). The first number is the number of bits the tag is able to encode (which means more tags are available in the respective family) and the second is the hamming distance. Hamming distance describes the ability for error correction while identifying tag ids. A high hamming distance generally means that it will be easier for a tag to be identified even if there are errors. However, as hamming distance increases, the number of available tags decreases.
The 2026 FRC game will be using 36h11 tags, which can be found [here](https://github.com/AprilRobotics/apriltag-imgs/tree/2bc821edb4eb7b408d13c6a590d326d8a9ec98f3/tag36h11).
3D AprilTag tracking will allow you to track the real-world position and rotation of a tag relative to the camera's image sensor. This is useful for robot pose estimation and other applications like autonomous scoring. In order to use 3D tracking, you must first {ref}`calibrate your camera <docs/calibration/calibration:Calibrating Your Camera>`. Once you have, you need to enable 3D mode in the UI and you will now be able to get 3D pose information from the tag! For information on getting and using this information in your code, see {ref}`the programming reference. <docs/programming/index:Programming Reference>`.
3D AprilTag tracking will allow you to track the real-world position and rotation of a tag relative to the camera's image sensor. This is useful for robot pose estimation and other applications like autonomous scoring. In order to use 3D tracking, you must first {ref}`calibrate your camera <docs/calibration/calibration:Calibrating Your Camera>`. Once you have, you need to enable 3D mode in the UI and you will now be able to get 3D pose information from the tag! For information on getting and using this information in your code, see {ref}`the programming reference <docs/programming/index:Programming Reference>`.
## Ambiguity
Translating from 2D to 3D using data from the calibration and the four tag corners can lead to "pose ambiguity", where it appears that the AprilTag pose is flipping between two different poses. You can read more about this issue `here. <https://docs.wpilib.org/en/stable/docs/software/vision-processing/apriltag/apriltag-intro.html#d-to-3d-ambiguity>` Ambiguity is calculated as the ratio of reprojection errors between two pose solutions (if they exist), where reprojection error is the error corresponding to the image distance between where the apriltag's corners are detected vs where we expect to see them based on the tag's estimated camera relative pose.
Translating from 2D to 3D using data from the calibration and the four tag corners can lead to "pose ambiguity", where it appears that the AprilTag pose is flipping between two different poses. You can read more about this issue [here](https://docs.wpilib.org/en/stable/docs/software/vision-processing/apriltag/apriltag-intro.html#d-to-3d-ambiguity). Ambiguity is calculated as the ratio of reprojection errors between two pose solutions (if they exist), where reprojection error is the error corresponding to the image distance between where the apriltag's corners are detected vs where we expect to see them based on the tag's estimated camera relative pose.
There are a few steps you can take to resolve/mitigate this issue:
@@ -10,5 +10,5 @@ AprilTags are a common type of visual fiducial marker. Visual fiducial markers a
A more technical explanation can be found in the [WPILib documentation](https://docs.wpilib.org/en/latest/docs/software/vision-processing/apriltag/apriltag-intro.html).
:::{note}
You can get FIRST's [official PDF of the targets used in 2024 here](https://firstfrc.blob.core.windows.net/frc2024/FieldAssets/Apriltag_Images_and_User_Guide.pdf).
You can get FIRST's [official PDF of the targets used in 2026 here](https://firstfrc.blob.core.windows.net/frc2026/FieldAssets/2026-apriltag-images-user-guide.pdf).
@@ -8,8 +8,8 @@ Note that both of these pipeline types detect AprilTag markers and are just two
## AprilTag
The AprilTag pipeline type is based on the [AprilTag](https://april.eecs.umich.edu/software/apriltag.html) library from the University of Michigan and we recommend it for most use cases. It is (to our understanding) most accurate pipeline type, but is also ~2x slower than AruCo. This was the pipeline type used by teams in the 2023 season and is well tested.
The AprilTag pipeline type is based on the [AprilTag](https://april.eecs.umich.edu/software/apriltag.html) library from the University of Michigan and we recommend it for most use cases. It is (to our understanding) most accurate pipeline type, but is also ~2x slower than ArUco. This was the pipeline type used by teams in the 2023 season and is well tested.
## AruCo
## ArUco
The AruCo pipeline is based on the [AruCo](https://docs.opencv.org/4.8.0/d9/d6a/group__aruco.html) library implementation from OpenCV. It is ~2x higher fps and ~2x lower latency than the AprilTag pipeline type, but is less accurate. We recommend this pipeline type for teams that need to run at a higher framerate or have a lower powered device. This pipeline type is new for the 2024 season and is not as well tested as AprilTag.
The ArUco pipeline is based on the [ArUco](https://docs.opencv.org/4.8.0/d9/d6a/group__aruco.html) library implementation from OpenCV. It is ~2x higher fps and ~2x lower latency than the AprilTag pipeline type, but is less accurate. We recommend this pipeline type for teams that need to run at a higher framerate or have a lower powered device. This pipeline type was new for the 2024 season.
@@ -6,6 +6,10 @@ PhotonVision can combine AprilTag detections from multiple simultaneously observ
MultiTag requires an accurate field layout JSON to be uploaded! Differences between this layout and the tags' physical location will drive error in the estimated pose output.
:::
:::{warning}
For the 2026 Rebuilt Season, there are two different field layouts. The first is the [welded field layout](https://github.com/wpilibsuite/allwpilib/blob/main/apriltag/src/main/native/resources/edu/wpi/first/apriltag/2026-rebuilt-welded.json), which photonvision ships with. The second is the [Andymark field layout](https://github.com/wpilibsuite/allwpilib/blob/main/apriltag/src/main/native/resources/edu/wpi/first/apriltag/2026-rebuilt-andymark.json). It is very important to ensure that you use the correct field layout, both in the [PhotonPoseEstimator](https://docs.photonvision.org/en/latest/docs/programming/photonlib/robot-pose-estimator.html#apriltags-and-photonposeestimator) and on the [coprocessor](https://docs.photonvision.org/en/latest/docs/apriltag-pipelines/multitag.html#updating-the-field-layout).
:::
## Enabling MultiTag
Ensure that your camera is calibrated and 3D mode is enabled. Navigate to the Output tab and enable "Do Multi-Target Estimation". This enables MultiTag to use the uploaded field layout JSON to calculate your camera's pose in the field. This 3D transform will be shown as an additional table in the "targets" tab, along with the IDs of AprilTags used to compute this transform.
@@ -19,30 +23,41 @@ Ensure that your camera is calibrated and 3D mode is enabled. Navigate to the Ou
By default, enabling multi-target will disable calculating camera-to-target transforms for each observed AprilTag target to increase performance; the X/Y/angle numbers shown in the target table of the UI are instead calculated using the tag's expected location (per the field layout JSON) and the field-to-camera transform calculated using MultiTag. If you additionally want the individual camera-to-target transform calculated using SolvePNP for each target, enable "Always Do Single-Target Estimation".
:::
This multi-target pose estimate can be accessed using PhotonLib. We suggest using {ref}`the PhotonPoseEstimator class <docs/programming/photonlib/robot-pose-estimator:AprilTags and PhotonPoseEstimator>` with the `MULTI_TAG_PNP_ON_COPROCESSOR` strategy to simplify code, but the transform can be directly accessed using `getMultiTagResult`/`MultiTagResult()` (Java/C++).
This multi-target pose estimate can be accessed using PhotonLib. We suggest using {ref}`the PhotonPoseEstimator class <docs/programming/photonlib/robot-pose-estimator:AprilTags and PhotonPoseEstimator>` and calling `estimateCoprocMultiTagPose` (with an optional fallback like `estimateLowestAmbiguityPose`) to simplify code, but the transform can be directly accessed using `getMultiTagResult`/`MultiTagResult()`/`multitagResult` (Java/C++/Python).
```{eval-rst}
.. tab-set-code::
.. code-block:: Java
.. code-block:: java
var result = camera.getLatestResult();
if (result.getMultiTagResult().estimatedPose.isPresent) {
@@ -51,7 +66,7 @@ The returned field to camera transform is a transform from the fixed field origi
## Updating the Field Layout
PhotonVision ships by default with the [2024 field layout JSON](https://github.com/wpilibsuite/allwpilib/blob/main/apriltag/src/main/native/resources/edu/wpi/first/apriltag/2024-crescendo.json). The layout can be inspected by navigating to the settings tab and scrolling down to the "AprilTag Field Layout" card, as shown below.
PhotonVision ships by default with the [2026 welded field layout JSON](https://github.com/wpilibsuite/allwpilib/blob/main/apriltag/src/main/native/resources/edu/wpi/first/apriltag/2026-rebuilt-welded.json). The layout can be inspected by navigating to the settings tab and scrolling down to the "AprilTag Field Layout" card, as shown below.
```{image} images/field-layout.png
:alt: The currently saved field layout in the Photon UI
This benchmark compares the performance of four object detection models: YOLOv5, YOLOv5u, YOLOv8, and YOLOv11 on the [COCO 2017 Validation Set](http://images.cocodataset.org/zips/val2017.zip). The main purpose is to assess and compare the inference speed and detection accuracy of these models when deployed on the Orange Pi devices using the RKNN framework and int8 quantization.
- **Quantization**: int8 using 20 randomly selected images from the validation set
- **Framework**: RKNN Toolkit 2
## Operator-Level Benchmark Results
The following tables break down the average CPU time, NPU time, and total execution time (in microseconds) for each operator used by the models. Each value represents the mean ± standard deviation across 5,000 inferences.
### YOLOv5
| OpType | CPU Time (μs) | NPU Time (μs) | Total Time (μs) | Time Ratio (%) | Number of Times Called |
The table below summarizes the mean average precision (mAP) and total inference time for each model. These metrics provide a high-level view of how each model performs in terms of both detection accuracy and runtime efficiency.
The benchmark reveals a clear performance trade-off between inference time and detection accuracy:
- **YOLOv5** is the fastest model with the lowest total inference time, making it well-suited for situations where speed is more important than high detection precision.
- **YOLOv11** achieves the highest accuracy (mAP) across all IoU thresholds but comes with the longest inference time, which may limit its use in real-time applications.
- **YOLOv8** offers a strong balance between speed and accuracy, making it a practical choice when both factors matter.
- **YOLOv5u** improves accuracy compared to YOLOv5 but falls behind YOLOv8 in both speed and detection quality.
When choosing a model for edge devices like the Orange Pi 5, it’s important to weigh how much latency your system can tolerate versus how much accuracy you need. A faster model may give quicker results, while a more accurate one may offer better detection reliability, but at the cost of speed.
In order to detect AprilTags and use 3D mode, your camera must be calibrated at the desired resolution! Inaccurate calibration will lead to poor performance.
:::
To calibrate a camera, images of a Charuco board (or chessboard) are taken. By comparing where the grid corners should be in object space (for example, a corner once every inch in an 8x6 grid) with where they appear in the camera image, we can find a least-squares estimate for intrinsic camera properties like focal lengths, center point, and distortion coefficients. For more on camera calibration, please review the [OpenCV documentation](https://docs.opencv.org/4.x/dc/dbb/tutorial_py_calibration.html).
To calibrate a camera, images of a ChArUco board (or chessboard) are taken. By comparing where the grid corners should be in object space (for example, a corner once every inch in an 8x6 grid) with where they appear in the camera image, we can find a least-squares estimate for intrinsic camera properties like focal lengths, center point, and distortion coefficients. For more on camera calibration, please review the [OpenCV documentation](https://docs.opencv.org/4.x/dc/dbb/tutorial_py_calibration.html).
:::{warning}
While any resolution can be calibrated, higher resolutions may be too performance-intensive for some coprocessors to handle. Therefore, we recommend experimenting to see what works best for your coprocessor.
PhotonVision supports many resolution configuration options, with only a minimum of 640x480 required. However, higher resolutions may be too performance-intensive for some coprocessors to handle. Therefore, we recommend experimenting to see what works best for your coprocessor.
:::
:::{note}
@@ -16,9 +16,13 @@ The calibration data collected during calibration is specific to each physical c
## Calibration Tips
:::{warning}
The usage of chessboards can result in bad calibration results if multiple similar images are taken. We strongly recommend that teams use ChArUco boards instead!
:::
Accurate camera calibration is required in order to get accurate pose measurements when using AprilTags and 3D mode. The tips below should help ensure success:
01. Ensure your the images you take have the target in different positions and angles, with as big of a difference between angles as possible. It is important to make sure the target overlay still lines up with the board while doing this. Tilt no more than 45 degrees.
01. Ensure the images you take have the target in different positions and angles, with as big of a difference between angles as possible. It is important to make sure the target overlay still lines up with the board while doing this. Tilt no more than 45 degrees.
02. Use as big of a calibration target as your printer can print.
03. Ensure that your printed pattern has enough white border around it.
04. Ensure your camera stays in one position during the duration of the calibration.
@@ -34,11 +38,11 @@ Following the ideas above should help in getting an accurate calibration.
### 1. Navigate to the calibration section in the UI.
The Cameras tab of the UI houses PhotonVision's camera calibration tooling. It assists users with calibrating their cameras, as well as allows them to view previously calibrated resolutions. We support both charuco and chessboard calibrations.
The Cameras tab of the UI houses PhotonVision's camera calibration tooling. It assists users with calibrating their cameras, as well as allows them to view previously calibrated resolutions. We support both ChArUco and chessboard calibrations.
### 2. Print out the calibration target.
In the Camera Calibration tab, we'll print out the calibration target using the "Download" button. This should be printed on 8.5x11 printer paper. This page shows using an 8x8 charuco board (or chessboard depending on the selected calibration type).
In the Camera Calibration tab, we'll print out the calibration target using the "Download" button. This should be printed on 8.5x11 printer paper. This page shows using an 8x8 ChArUco board (or chessboard depending on the selected calibration type).
:::{warning}
Ensure that there is no scaling applied during printing (it should be at 100%) and that the PDF is printed as is on regular printer paper. Check the square size with calipers or an accurate measuring device after printing to ensure squares are sized properly, and enter the true size of the square in the UI text box. For optimal results, various resources are available online to calibrate your specific printer if needed.
@@ -46,11 +50,15 @@ Ensure that there is no scaling applied during printing (it should be at 100%) a
### 3. Select calibration resolution and fill in appropriate target data.
We'll next select a resolution to calibrate and populate our pattern spacing, marker size, and board size. The provided chessboard and charuco board are an 8x8 grid of 1 inch square. The provided charuco board uses the 4x4 dictionary with a marker size of 0.75 inches (this board does not need the old OpenCV pattern selector selected). Printers are not perfect, and you need to measure your calibration target and enter the correct marker size (size of the aruco marker) and pattern spacing (aka size of the black square) using calipers or similar. Finally, once our entered data is correct, we'll click "start calibration."
We'll next select a resolution to calibrate and populate our pattern spacing, marker size, and board size. The provided chessboard and ChArUco board are an 8x8 grid of 1 inch square. The provided ChArUco board uses the 4x4 dictionary with a marker size of 0.75 inches (this board does not need the old OpenCV pattern selector selected). Printers are not perfect, and you need to measure your calibration target and enter the correct marker size (size of the ArUco marker) and pattern spacing (aka size of the black square) using calipers or similar. Finally, once our entered data is correct, we'll click "start calibration."
:::{warning} Old OpenCV Pattern selector. This should be used in the case that the calibration image is generated from a version of OpenCV before version 4.6.0. This would include targets created by calib.io. If this selector is not set correctly the calibration will be completely invalid. For more info view [this GitHub issue](https://github.com/opencv/opencv_contrib/issues/3291).
:::
:::{note}
If you have a [calib.io](https://calib.io/) ChArUco Target you will have to enter the paramaters of your target. For example if your target says "9x12 | Checker Size: 30 mm | Marker Size: 22 mm | Dictionary: ArUco DICT 5x5", you would have to set the board type to Dict_5x5_1000, the pattern spacing to 1.1811 in (30 mm converted to inches), the marker size 0.866142 in (22 mm converted to inches), the board width to 12 and the board height to 9. If you chose the wrong tag family the board wont be detected during calibration. If you swap the width and height your calibration will have a very high error.
:::
### 4. Take at calibration images from various angles.
Now, we'll capture images of our board from various angles. It's important to check that the board overlay matches the board in your image. The further the overdrawn points are from the true position of the chessboard corners, the less accurate the final calibration will be. We'll want to capture enough images to cover the whole camera's FOV (with a minimum of 12). Once we've got our images, we'll click "Finish calibration" and wait for the calibration process to complete. If all goes well, the mean error and FOVs will be shown in the table on the right. The FOV should be close to the camera's specified FOV (usually found in a datasheet) usually within + or - 10 degrees. The mean error should also be low, usually less than 1 pixel.
@@ -75,7 +83,7 @@ Details about a particular calibration can be viewed by clicking on that resolut
More info on what these parameters mean can be found in [OpenCV's docs](https://docs.opencv.org/4.8.0/d4/d94/tutorial_camera_calibration.html)
:::
- Fx/Fy: Estimated camera focal length, in mm
- Fx/Fy: Estimated camera focal length, in pixels
- Fx/Cy: Estimated camera optical center, in pixels. This should be at about the center of the image
- Distortion: OpenCV camera model distortion coefficients
- FOV: calculated using estimated focal length and image size. Useful for gut-checking calibration results
@@ -83,7 +91,7 @@ More info on what these parameters mean can be found in [OpenCV's docs](https://
Below these outputs are the snapshots collected for calibration, along with a per-snapshot mean reprojection error. A snapshot with a larger reprojection error might indicate a bad snapshot, due to effects such as motion blur or misidentified chessboard corners.
Calibration images can also be extracted from the downloaded JSON file using [this Python script](https://raw.githubusercontent.com/PhotonVision/photonvision/master/devTools/calibrationUtils.py). This script will unpack calibration images, and also generate a VNL file for use [with mrcal](https://mrcal.secretsauce.net/).
Calibration images can also be extracted from the downloaded JSON file using [this Python script](https://raw.githubusercontent.com/PhotonVision/photonvision/main/devTools/calibrationUtils.py). This script will unpack calibration images, and also generate a VNL file for use [with mrcal](https://mrcal.secretsauce.net/).
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