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Move to main over master (#1642)

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Resolves https://github.com/PhotonVision/photonvision/issues/251

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Signed-off-by: Jade Turner <spacey-sooty@proton.me>
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Jade
2024-12-21 01:24:52 +08:00
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parent 81076375b8
commit ffc4e06ac6
16 changed files with 28 additions and 28 deletions
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docs/source/docs/advanced-installation/prerelease-software.md
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# Installing Pre-Release Versions
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 `master` branch, or by {ref}`compiling PhotonVision locally <docs/contributing/building-photon:Build Instructions>`.
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 master. To test a particular commit to master, navigate to the [PhotonVision commit list](https://github.com/PhotonVision/photonvision/commits/master/) 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".
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

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docs/source/docs/apriltag-pipelines/2D-tracking-tuning.md
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### 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 2024 FRC game will be using 36h11 tags, which can be found [here](https://github.com/AprilRobotics/apriltag-imgs/tree/main/tag36h11).
### Decimate

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docs/source/docs/calibration/calibration.md
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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/).
```
python3 /path/to/calibrationUtils.py path/to/photon_calibration.json /path/to/output/folder

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docs/source/docs/examples/aimandrange.md
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# Combining Aiming and Getting in Range
The following example is from the PhotonLib example repository ([Java](https://github.com/PhotonVision/photonvision/tree/master/photonlib-java-examples/aimandrange)/[C++](https://github.com/PhotonVision/photonvision/tree/master/photonlib-cpp-examples/aimandrange)).
The following example is from the PhotonLib example repository ([Java](https://github.com/PhotonVision/photonvision/tree/main/photonlib-java-examples/aimandrange)/[C++](https://github.com/PhotonVision/photonvision/tree/main/photonlib-cpp-examples/aimandrange)).
## Knowledge and Equipment Needed

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docs/source/docs/examples/aimingatatarget.md
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# Aiming at a Target
The following example is from the PhotonLib example repository ([Java](https://github.com/PhotonVision/photonvision/tree/master/photonlib-java-examples/aimattarget)).
The following example is from the PhotonLib example repository ([Java](https://github.com/PhotonVision/photonvision/tree/main/photonlib-java-examples/aimattarget)).
## Knowledge and Equipment Needed

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docs/source/docs/examples/poseest.md
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# Using WPILib Pose Estimation, Simulation, and PhotonVision Together
The following example comes from the PhotonLib example repository ([Java](https://github.com/PhotonVision/photonvision/tree/master/photonlib-java-examples/poseest)/[C++](https://github.com/PhotonVision/photonvision/tree/master/photonlib-cpp-examples/poseest)/[Python](https://github.com/PhotonVision/photonvision/tree/master/photonlib-python-examples/poseest)). Full code is available at that links.
The following example comes from the PhotonLib example repository ([Java](https://github.com/PhotonVision/photonvision/tree/main/photonlib-java-examples/poseest)/[C++](https://github.com/PhotonVision/photonvision/tree/main/photonlib-cpp-examples/poseest)/[Python](https://github.com/PhotonVision/photonvision/tree/main/photonlib-python-examples/poseest)). Full code is available at that links.
## Knowledge and Equipment Needed

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docs/source/docs/objectDetection/about-object-detection.md
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PhotonVision currently ONLY supports YOLOv5 models trained and converted to `.rknn` format for RK3588 CPUs! Other models require different post-processing code and will NOT work. The model conversion process is also highly particular. Proceed with care.
:::
Our [pre-trained NOTE model](https://github.com/PhotonVision/photonvision/blob/master/photon-server/src/main/resources/models/note-640-640-yolov5s.rknn) is automatically extracted from the JAR when PhotonVision starts, only if a file named “note-640-640-yolov5s.rknn” and "labels.txt" does not exist in the folder `photonvision_config/models/`. This technically allows power users to replace the model and label files with new ones without rebuilding Photon from source and uploading a new JAR.
Our [pre-trained NOTE model](https://github.com/PhotonVision/photonvision/blob/main/photon-server/src/main/resources/models/note-640-640-yolov5s.rknn) is automatically extracted from the JAR when PhotonVision starts, only if a file named “note-640-640-yolov5s.rknn” and "labels.txt" does not exist in the folder `photonvision_config/models/`. This technically allows power users to replace the model and label files with new ones without rebuilding Photon from source and uploading a new JAR.
Use a program like WinSCP or FileZilla to access your coprocessor's filesystem, and copy the new `.rknn` model file into /home/pi. Next, SSH into the coprocessor and `sudo mv /path/to/new/model.rknn /opt/photonvision/photonvision_config/models/note-640-640-yolov5s.rknn`. Repeat this process with the labels file, which should contain one line per label the model outputs with no training newline. Next, restart PhotonVision via the web UI.

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docs/source/docs/programming/photonlib/getting-target-data.md
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```
:::{note}
Unlike other vision software solutions, using the latest result guarantees that all information is from the same timestamp. This is achievable because the PhotonVision backend sends a byte-packed string of data which is then deserialized by PhotonLib to get target data. For more information, check out the [PhotonLib source code](https://github.com/PhotonVision/photonvision/tree/master/photon-lib).
Unlike other vision software solutions, using the latest result guarantees that all information is from the same timestamp. This is achievable because the PhotonVision backend sends a byte-packed string of data which is then deserialized by PhotonLib to get target data. For more information, check out the [PhotonLib source code](https://github.com/PhotonVision/photonvision/tree/main/photon-lib).
:::
## Checking for Existence of Targets

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docs/source/docs/quick-start/quick-install.md
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Unless otherwise noted in release notes or if updating from the prior years version, to update PhotonVision after the initial installation, use the offline update option in the settings page with the downloaded jar file from the latest release.
:::{note}
Limelight 2, 2+, and 3 will need a [custom hardware config file](https://github.com/PhotonVision/photonvision/tree/master/docs/source/docs/advanced-installation/sw_install/files) for lighting to work. Currently only limelight 2 and 2+ files are available.
Limelight 2, 2+, and 3 will need a [custom hardware config file](https://github.com/PhotonVision/photonvision/tree/main/docs/source/docs/advanced-installation/sw_install/files) for lighting to work. Currently only limelight 2 and 2+ files are available.
:::
:::{note}