diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 8b3ef1aca6..4f0393fdb6 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -1,28 +1,17 @@ version: 2 -sphinx: - builder: html - configuration: docs/source/conf.py - fail_on_warning: true - build: os: ubuntu-22.04 tools: - python: "3.11" - jobs: - post_checkout: - # Cancel building pull requests when there aren't changed in the docs directory or YAML file. - # You can add any other files or directories that you'd like here as well, - # like your docs requirements file, or other files that will change your docs build. - # - # If there are no changes (git diff exits with 0) we force the command to return with 183. - # This is a special exit code on Read the Docs that will cancel the build immediately. - - | - if [ "$READTHEDOCS_VERSION_TYPE" = "external" ] && git diff --quiet origin/master -- docs/ .readthedocs.yaml; - then - exit 183; - fi - -python: - install: - - requirements: docs/requirements.txt + nodejs: "18" + commands: + # "docs/" directory was created using the command to create the site: + # npx create-docusaurus@latest docs classic + # + # Install Docusaurus dependencies + - cd docs/ && npm install + # Build the site + - cd docs/ && npm run build + # Copy generated files into Read the Docs directory + - mkdir --parents _readthedocs/html/ + - cp --recursive docs/build/* _readthedocs/html/ diff --git a/docs-old/.gitignore b/docs-old/.gitignore new file mode 100644 index 0000000000..b7a9f77acb --- /dev/null +++ b/docs-old/.gitignore @@ -0,0 +1,9 @@ +build/* +.DS_Store +.vscode/* +.idea/* +source/_build +source/docs/_build + +venv/* +.venv/* diff --git a/docs/.styleguide b/docs-old/.styleguide similarity index 100% rename from docs/.styleguide rename to docs-old/.styleguide diff --git a/docs/LICENSE b/docs-old/LICENSE similarity index 100% rename from docs/LICENSE rename to docs-old/LICENSE diff --git a/docs/Makefile b/docs-old/Makefile similarity index 100% rename from docs/Makefile rename to docs-old/Makefile diff --git a/docs-old/README.MD b/docs-old/README.MD new file mode 100644 index 0000000000..1e7a067ea9 --- /dev/null +++ b/docs-old/README.MD @@ -0,0 +1,9 @@ +# PhotonVision ReadTheDocs + +[![Documentation Status](https://readthedocs.org/projects/photonvision-docs/badge/?version=latest)](https://docs.photonvision.org/en/latest/?badge=latest) + +PhotonVision is a free open-source vision processing software for FRC teams. + +This repository is the source code for our ReadTheDocs documentation, which can be found [here](https://docs.photonvision.org). + +[Contribution and formatting guidelines for this project](https://docs.photonvision.org/en/latest/docs/contributing/photonvision-docs/index.html) diff --git a/docs/make.bat b/docs-old/make.bat similarity index 100% rename from docs/make.bat rename to docs-old/make.bat diff --git a/docs/requirements.txt b/docs-old/requirements.txt similarity index 100% rename from docs/requirements.txt rename to docs-old/requirements.txt diff --git a/docs/source/404.md b/docs-old/source/404.md similarity index 100% rename from docs/source/404.md rename to docs-old/source/404.md diff --git a/docs/source/Makefile b/docs-old/source/Makefile similarity index 100% rename from docs/source/Makefile rename to docs-old/source/Makefile diff --git a/docs/source/_static/css/pv-icons.css b/docs-old/source/_static/css/pv-icons.css similarity index 100% rename from docs/source/_static/css/pv-icons.css rename to docs-old/source/_static/css/pv-icons.css diff --git a/docs/source/_templates/layout.html b/docs-old/source/_templates/layout.html similarity index 100% rename from docs/source/_templates/layout.html rename to docs-old/source/_templates/layout.html diff --git a/docs/source/_static/assets/PhotonVision-Header-noBG.png b/docs-old/source/assets/PhotonVision-Header-noBG.png similarity index 100% rename from docs/source/_static/assets/PhotonVision-Header-noBG.png rename to docs-old/source/assets/PhotonVision-Header-noBG.png diff --git a/docs/source/_static/assets/PhotonVision-Header-onWhite.png b/docs-old/source/assets/PhotonVision-Header-onWhite.png similarity index 100% rename from docs/source/_static/assets/PhotonVision-Header-onWhite.png rename to docs-old/source/assets/PhotonVision-Header-onWhite.png diff --git a/docs/source/assets/RectLogo.png b/docs-old/source/assets/RectLogo.png similarity index 100% rename from docs/source/assets/RectLogo.png rename to docs-old/source/assets/RectLogo.png diff --git a/docs/source/_static/assets/RoundLogo.png b/docs-old/source/assets/RoundLogo.png similarity index 100% rename from docs/source/_static/assets/RoundLogo.png rename to docs-old/source/assets/RoundLogo.png diff --git a/docs/source/assets/RoundLogoWhite.png b/docs-old/source/assets/RoundLogoWhite.png similarity index 100% rename from docs/source/assets/RoundLogoWhite.png rename to docs-old/source/assets/RoundLogoWhite.png diff --git a/docs/source/conf.py b/docs-old/source/conf.py similarity index 100% rename from docs/source/conf.py rename to docs-old/source/conf.py diff --git a/docs/source/index.md b/docs-old/source/index.md similarity index 100% rename from docs/source/index.md rename to docs-old/source/index.md diff --git a/docs/source/make.bat b/docs-old/source/make.bat similarity index 100% rename from docs/source/make.bat rename to docs-old/source/make.bat diff --git a/docs/.gitignore b/docs/.gitignore index b7a9f77acb..b2d6de3062 100644 --- a/docs/.gitignore +++ b/docs/.gitignore @@ -1,9 +1,20 @@ -build/* +# Dependencies +/node_modules + +# Production +/build + +# Generated files +.docusaurus +.cache-loader + +# Misc .DS_Store -.vscode/* -.idea/* -source/_build -source/docs/_build +.env.local +.env.development.local +.env.test.local +.env.production.local -venv/* -.venv/* +npm-debug.log* +yarn-debug.log* +yarn-error.log* diff --git a/docs/README.MD b/docs/README.MD index 1e7a067ea9..0c6c2c27be 100644 --- a/docs/README.MD +++ b/docs/README.MD @@ -1,9 +1,41 @@ -# PhotonVision ReadTheDocs +# Website -[![Documentation Status](https://readthedocs.org/projects/photonvision-docs/badge/?version=latest)](https://docs.photonvision.org/en/latest/?badge=latest) +This website is built using [Docusaurus](https://docusaurus.io/), a modern static website generator. -PhotonVision is a free open-source vision processing software for FRC teams. +### Installation -This repository is the source code for our ReadTheDocs documentation, which can be found [here](https://docs.photonvision.org). +``` +$ yarn +``` -[Contribution and formatting guidelines for this project](https://docs.photonvision.org/en/latest/docs/contributing/photonvision-docs/index.html) +### Local Development + +``` +$ yarn start +``` + +This command starts a local development server and opens up a browser window. Most changes are reflected live without having to restart the server. + +### Build + +``` +$ yarn build +``` + +This command generates static content into the `build` directory and can be served using any static contents hosting service. + +### Deployment + +Using SSH: + +``` +$ USE_SSH=true yarn deploy +``` + +Not using SSH: + +``` +$ GIT_USER= yarn deploy +``` + +If you are using GitHub pages for hosting, this command is a convenient way to build the website and push to the `gh-pages` branch. diff --git a/docs/babel.config.js b/docs/babel.config.js new file mode 100644 index 0000000000..e00595dae7 --- /dev/null +++ b/docs/babel.config.js @@ -0,0 +1,3 @@ +module.exports = { + presets: [require.resolve('@docusaurus/core/lib/babel/preset')], +}; diff --git a/docs/blog/2019-05-28-first-blog-post.md b/docs/blog/2019-05-28-first-blog-post.md new file mode 100644 index 0000000000..d3032efb35 --- /dev/null +++ b/docs/blog/2019-05-28-first-blog-post.md @@ -0,0 +1,12 @@ +--- +slug: first-blog-post +title: First Blog Post +authors: [slorber, yangshun] +tags: [hola, docusaurus] +--- + +Lorem ipsum dolor sit amet... + + + +...consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet diff --git a/docs/blog/2019-05-29-long-blog-post.md b/docs/blog/2019-05-29-long-blog-post.md new file mode 100644 index 0000000000..eb4435de59 --- /dev/null +++ b/docs/blog/2019-05-29-long-blog-post.md @@ -0,0 +1,44 @@ +--- +slug: long-blog-post +title: Long Blog Post +authors: yangshun +tags: [hello, docusaurus] +--- + +This is the summary of a very long blog post, + +Use a `` comment to limit blog post size in the list view. + + + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet + +Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet diff --git a/docs/blog/2021-08-01-mdx-blog-post.mdx b/docs/blog/2021-08-01-mdx-blog-post.mdx new file mode 100644 index 0000000000..0c4b4a48b9 --- /dev/null +++ b/docs/blog/2021-08-01-mdx-blog-post.mdx @@ -0,0 +1,24 @@ +--- +slug: mdx-blog-post +title: MDX Blog Post +authors: [slorber] +tags: [docusaurus] +--- + +Blog posts support [Docusaurus Markdown features](https://docusaurus.io/docs/markdown-features), such as [MDX](https://mdxjs.com/). + +:::tip + +Use the power of React to create interactive blog posts. + +::: + +{/* truncate */} + +For example, use JSX to create an interactive button: + +```js + +``` + + diff --git a/docs/blog/2021-08-26-welcome/docusaurus-plushie-banner.jpeg b/docs/blog/2021-08-26-welcome/docusaurus-plushie-banner.jpeg new file mode 100644 index 0000000000..11bda09284 Binary files /dev/null and b/docs/blog/2021-08-26-welcome/docusaurus-plushie-banner.jpeg differ diff --git a/docs/blog/2021-08-26-welcome/index.md b/docs/blog/2021-08-26-welcome/index.md new file mode 100644 index 0000000000..349ea075f5 --- /dev/null +++ b/docs/blog/2021-08-26-welcome/index.md @@ -0,0 +1,29 @@ +--- +slug: welcome +title: Welcome +authors: [slorber, yangshun] +tags: [facebook, hello, docusaurus] +--- + +[Docusaurus blogging features](https://docusaurus.io/docs/blog) are powered by the [blog plugin](https://docusaurus.io/docs/api/plugins/@docusaurus/plugin-content-blog). + +Here are a few tips you might find useful. + + + +Simply add Markdown files (or folders) to the `blog` directory. + +Regular blog authors can be added to `authors.yml`. + +The blog post date can be extracted from filenames, such as: + +- `2019-05-30-welcome.md` +- `2019-05-30-welcome/index.md` + +A blog post folder can be convenient to co-locate blog post images: + +![Docusaurus Plushie](./docusaurus-plushie-banner.jpeg) + +The blog supports tags as well! + +**And if you don't want a blog**: just delete this directory, and use `blog: false` in your Docusaurus config. diff --git a/docs/blog/authors.yml b/docs/blog/authors.yml new file mode 100644 index 0000000000..8bfa5c7c4b --- /dev/null +++ b/docs/blog/authors.yml @@ -0,0 +1,23 @@ +yangshun: + name: Yangshun Tay + title: Front End Engineer @ Facebook + url: https://github.com/yangshun + image_url: https://github.com/yangshun.png + page: true + socials: + x: yangshunz + github: yangshun + +slorber: + name: Sébastien Lorber + title: Docusaurus maintainer + url: https://sebastienlorber.com + image_url: https://github.com/slorber.png + page: + # customize the url of the author page at /blog/authors/ + permalink: '/all-sebastien-lorber-articles' + socials: + x: sebastienlorber + linkedin: sebastienlorber + github: slorber + newsletter: https://thisweekinreact.com diff --git a/docs/blog/tags.yml b/docs/blog/tags.yml new file mode 100644 index 0000000000..bfaa778fbd --- /dev/null +++ b/docs/blog/tags.yml @@ -0,0 +1,19 @@ +facebook: + label: Facebook + permalink: /facebook + description: Facebook tag description + +hello: + label: Hello + permalink: /hello + description: Hello tag description + +docusaurus: + label: Docusaurus + permalink: /docusaurus + description: Docusaurus tag description + +hola: + label: Hola + permalink: /hola + description: Hola tag description diff --git a/docs/source/docs/additional-resources/best-practices.md b/docs/docs/additional-resources/best-practices.md similarity index 100% rename from docs/source/docs/additional-resources/best-practices.md rename to docs/docs/additional-resources/best-practices.md diff --git a/docs/docs/additional-resources/config.md b/docs/docs/additional-resources/config.md new file mode 100644 index 0000000000..c50d0d6a91 --- /dev/null +++ b/docs/docs/additional-resources/config.md @@ -0,0 +1,46 @@ +# Filesystem Directory + +PhotonVision stores and loads settings in the `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 `/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 + +The directory structure is outlined below. + +Config directory structure + + +- calibImgs + - 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 `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. +- logs + - Contains timestamped logs in the format `photonvision-YYYY-MM-D_HH-MM-SS.log`. Note that on Pi or Gloworm these timestamps will likely be significantly behind the real time. +- hardwareSettings.json + - 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. + +## Importing and Exporting Settings + +The entire settings directory can be exported as a ZIP archive from the settings page. + + + +A variety of files can be imported back into PhotonVision: + +- ZIP Archive (`.zip`) + - Useful for restoring a full configuration from a different PhotonVision instance. +- Single Config File + - Currently-supported Files + - `hardwareConfig.json` + - `hardwareSettings.json` + - `networkSettings.json` + - Useful for simple hardware or network configuration tasks without overwriting all settings. diff --git a/docs/source/docs/additional-resources/images/configDir.png b/docs/docs/additional-resources/images/configDir.png similarity index 100% rename from docs/source/docs/additional-resources/images/configDir.png rename to docs/docs/additional-resources/images/configDir.png diff --git a/docs/source/docs/additional-resources/nt-api.md b/docs/docs/additional-resources/nt-api.md similarity index 95% rename from docs/source/docs/additional-resources/nt-api.md rename to docs/docs/additional-resources/nt-api.md index e89c26b356..902a09653e 100644 --- a/docs/source/docs/additional-resources/nt-api.md +++ b/docs/docs/additional-resources/nt-api.md @@ -2,13 +2,13 @@ ## About -:::{warning} +:::warning 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! ::: ## API -:::{warning} +:::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. ::: @@ -51,7 +51,7 @@ Images are returned as part of the .zip package from the "Export" operation in t | `inputSaveImgCmd` | `boolean` | Triggers saving the current input image to file. | | `outputSaveImgCmd` | `boolean` | Triggers saving the current output image to file. | -:::{warning} +:::warning If you manage to make calls to these commands faster than 500ms (between calls), additional photos will not be captured. ::: @@ -63,8 +63,8 @@ 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. ` +:::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. ` Single camera operation should work without issue. ::: diff --git a/docs/source/docs/apriltag-pipelines/2D-tracking-tuning.md b/docs/docs/apriltag-pipelines/2D-tracking-tuning.md similarity index 94% rename from docs/source/docs/apriltag-pipelines/2D-tracking-tuning.md rename to docs/docs/apriltag-pipelines/2D-tracking-tuning.md index 84e7606119..3a229d4297 100644 --- a/docs/source/docs/apriltag-pipelines/2D-tracking-tuning.md +++ b/docs/docs/apriltag-pipelines/2D-tracking-tuning.md @@ -4,20 +4,15 @@ 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 -``` + -You are now able to detect and track AprilTags in 2D (yaw, pitch, roll, etc.). In order to get 3D data from your AprilTags, please see {ref}`here. ` +You are now able to detect and track AprilTags in 2D (yaw, pitch, roll, etc.). In order to get 3D data from your AprilTags, please see \{ref}`here. ` ## 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. -```{image} images/apriltag-tune.png -:align: center -:scale: 45 % -``` + ### Target Family diff --git a/docs/source/docs/apriltag-pipelines/3D-tracking.md b/docs/docs/apriltag-pipelines/3D-tracking.md similarity index 68% rename from docs/source/docs/apriltag-pipelines/3D-tracking.md rename to docs/docs/apriltag-pipelines/3D-tracking.md index 416d12ab6e..03ab19e1fa 100644 --- a/docs/source/docs/apriltag-pipelines/3D-tracking.md +++ b/docs/docs/apriltag-pipelines/3D-tracking.md @@ -1,6 +1,6 @@ # 3D Tracking -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 `. 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. `. +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 `. 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. `. ## Ambiguity @@ -9,5 +9,5 @@ Translating from 2D to 3D using data from the calibration and the four tag corne There are a few steps you can take to resolve/mitigate this issue: 1. Mount cameras at oblique angles so it is less likely that the tag will be seen straight on. -2. Use the {ref}`MultiTag system ` in order to combine the corners from multiple tags to get a more accurate and unambiguous pose. +2. Use the \{ref}`MultiTag system ` in order to combine the corners from multiple tags to get a more accurate and unambiguous pose. 3. Reject all tag poses where the ambiguity ratio (available via PhotonLib) is greater than 0.2. diff --git a/docs/source/docs/apriltag-pipelines/about-apriltags.md b/docs/docs/apriltag-pipelines/about-apriltags.md similarity index 91% rename from docs/source/docs/apriltag-pipelines/about-apriltags.md rename to docs/docs/apriltag-pipelines/about-apriltags.md index aaee12ff96..410e237fc1 100644 --- a/docs/source/docs/apriltag-pipelines/about-apriltags.md +++ b/docs/docs/apriltag-pipelines/about-apriltags.md @@ -1,14 +1,11 @@ # About Apriltags -```{image} images/pv-apriltag.png -:align: center -:scale: 20 % -``` + AprilTags are a common type of visual fiducial marker. Visual fiducial markers are artificial landmarks added to a scene to allow "localization" (finding your current position) via images. In simpler terms, tags mark known points of reference that you can use to find your current location. They are similar to QR codes in which they encode information, however, they hold only a single number. By placing AprilTags in known locations around the field and detecting them using PhotonVision, you can easily get full field localization / pose estimation. Alternatively, you can use AprilTags the same way you used retroreflective tape, simply using them to turn to goal without any pose estimation. 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} +:::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). ::: diff --git a/docs/source/docs/apriltag-pipelines/coordinate-systems.md b/docs/docs/apriltag-pipelines/coordinate-systems.md similarity index 85% rename from docs/source/docs/apriltag-pipelines/coordinate-systems.md rename to docs/docs/apriltag-pipelines/coordinate-systems.md index c828321e9e..884a3f600c 100644 --- a/docs/source/docs/apriltag-pipelines/coordinate-systems.md +++ b/docs/docs/apriltag-pipelines/coordinate-systems.md @@ -15,15 +15,9 @@ OpenCV by default uses x-left/y-down/z-out for camera transforms. PhotonVision a - The y-axis points to the left - The z-axis points upwards -```{image} images/camera-coord.png -:align: center -:scale: 45 % -``` + -```{image} images/multiple-tags.png -:align: center -:scale: 45 % -``` + ## AprilTag Coordinate Frame @@ -34,7 +28,4 @@ The AprilTag coordinate system is defined as follows, relative to the center of - The y-axis points to the right - The z-axis points upwards -```{image} images/apriltag-coords.png -:align: center -:scale: 45 % -``` + diff --git a/docs/source/docs/apriltag-pipelines/detector-types.md b/docs/docs/apriltag-pipelines/detector-types.md similarity index 99% rename from docs/source/docs/apriltag-pipelines/detector-types.md rename to docs/docs/apriltag-pipelines/detector-types.md index 76d01b1008..b1b345e326 100644 --- a/docs/source/docs/apriltag-pipelines/detector-types.md +++ b/docs/docs/apriltag-pipelines/detector-types.md @@ -2,7 +2,7 @@ PhotonVision offers two different AprilTag pipeline types based on different implementations of the underlying algorithm. Each one has its advantages / disadvantages, which are detailed below. -:::{note} +:::note Note that both of these pipeline types detect AprilTag markers and are just two different algorithms for doing so. ::: diff --git a/docs/source/docs/apriltag-pipelines/images/apriltag-coords.png b/docs/docs/apriltag-pipelines/images/apriltag-coords.png similarity index 100% rename from docs/source/docs/apriltag-pipelines/images/apriltag-coords.png rename to docs/docs/apriltag-pipelines/images/apriltag-coords.png diff --git a/docs/source/docs/apriltag-pipelines/images/apriltag-tune.png b/docs/docs/apriltag-pipelines/images/apriltag-tune.png similarity index 100% rename from docs/source/docs/apriltag-pipelines/images/apriltag-tune.png rename to docs/docs/apriltag-pipelines/images/apriltag-tune.png diff --git a/docs/source/docs/apriltag-pipelines/images/apriltag.png b/docs/docs/apriltag-pipelines/images/apriltag.png similarity index 100% rename from docs/source/docs/apriltag-pipelines/images/apriltag.png rename to docs/docs/apriltag-pipelines/images/apriltag.png diff --git a/docs/source/docs/apriltag-pipelines/images/camera-coord.png b/docs/docs/apriltag-pipelines/images/camera-coord.png similarity index 100% rename from docs/source/docs/apriltag-pipelines/images/camera-coord.png rename to docs/docs/apriltag-pipelines/images/camera-coord.png diff --git a/docs/source/docs/apriltag-pipelines/images/field-layout.png b/docs/docs/apriltag-pipelines/images/field-layout.png similarity index 100% rename from docs/source/docs/apriltag-pipelines/images/field-layout.png rename to docs/docs/apriltag-pipelines/images/field-layout.png diff --git a/docs/source/docs/apriltag-pipelines/images/multiple-tags.png b/docs/docs/apriltag-pipelines/images/multiple-tags.png similarity index 100% rename from docs/source/docs/apriltag-pipelines/images/multiple-tags.png rename to docs/docs/apriltag-pipelines/images/multiple-tags.png diff --git a/docs/source/docs/apriltag-pipelines/images/multitag-ui.png b/docs/docs/apriltag-pipelines/images/multitag-ui.png similarity index 100% rename from docs/source/docs/apriltag-pipelines/images/multitag-ui.png rename to docs/docs/apriltag-pipelines/images/multitag-ui.png diff --git a/docs/source/docs/apriltag-pipelines/images/pv-apriltag.png b/docs/docs/apriltag-pipelines/images/pv-apriltag.png similarity index 100% rename from docs/source/docs/apriltag-pipelines/images/pv-apriltag.png rename to docs/docs/apriltag-pipelines/images/pv-apriltag.png diff --git a/docs/source/docs/apriltag-pipelines/multitag.md b/docs/docs/apriltag-pipelines/multitag.md similarity index 71% rename from docs/source/docs/apriltag-pipelines/multitag.md rename to docs/docs/apriltag-pipelines/multitag.md index 102b36ce1f..47c5168a22 100644 --- a/docs/source/docs/apriltag-pipelines/multitag.md +++ b/docs/docs/apriltag-pipelines/multitag.md @@ -1,8 +1,11 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + # MultiTag Localization PhotonVision can combine AprilTag detections from multiple simultaneously observed AprilTags from a particular camera with information about where tags are expected to be located on the field to produce a better estimate of where the camera (and therefore robot) is located on the field. PhotonVision can calculate this multi-target result on your coprocessor, reducing CPU usage on your RoboRio. This result is sent over NetworkTables along with other detected targets as part of the `PhotonPipelineResult` provided by PhotonLib. -:::{warning} +:::warning 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. ::: @@ -10,37 +13,34 @@ MultiTag requires an accurate field layout JSON to be uploaded! Differences betw 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. -```{image} images/multitag-ui.png -:alt: Multitarget enabled and running in the PhotonVision UI -:width: 600 -``` +Multitarget enabled and running in the PhotonVision UI -:::{note} +:::note 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 ` with the `MULTI_TAG_PNP_ON_COPROCESSOR` strategy to simplify code, but the transform can be directly accessed using `getMultiTagResult`/`MultiTagResult()` (Java/C++). - -```{eval-rst} -.. tab-set-code:: - - .. code-block:: java - - var result = camera.getLatestResult(); - if (result.getMultiTagResult().estimatedPose.isPresent) { - Transform3d fieldToCamera = result.getMultiTagResult().estimatedPose.best; - } +This multi-target pose estimate can be accessed using PhotonLib. We suggest using \{ref}`the PhotonPoseEstimator class ` with the `MULTI_TAG_PNP_ON_COPROCESSOR` strategy to simplify code, but the transform can be directly accessed using `getMultiTagResult`/`MultiTagResult()` (Java/C++). - - .. code-block:: C++ - - auto result = camera.GetLatestResult(); - if (result.MultiTagResult().result.isPresent) { - frc::Transform3d fieldToCamera = result.MultiTagResult().result.best; - } + + +```java +var result = camera.getLatestResult(); +if (result.getMultiTagResult().estimatedPose.isPresent) { + Transform3d fieldToCamera = result.getMultiTagResult().estimatedPose.best; +} ``` - -:::{note} + + +```cpp +auto result = camera.GetLatestResult(); +if (result.MultiTagResult().result.isPresent) { + frc::Transform3d fieldToCamera = result.MultiTagResult().result.best; +} +``` + + + +:::note The returned field to camera transform is a transform from the fixed field origin to the camera's coordinate system. This does not change based on alliance color, and by convention is on the BLUE ALLIANCE wall. ::: @@ -48,13 +48,10 @@ The returned field to camera transform is a transform from the fixed field origi 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. -```{image} images/field-layout.png -:alt: The currently saved field layout in the Photon UI -:width: 600 -``` +The currently saved field layout in the Photon UI An updated field layout can be uploaded by navigating to the "Device Control" card of the Settings tab and clicking "Import Settings". In the pop-up dialog, select the "AprilTag Layout" type and choose an updated layout JSON (in the same format as the WPILib field layout JSON linked above) using the paperclip icon, and select "Import Settings". The AprilTag layout in the "AprilTag Field Layout" card below should be updated to reflect the new layout. -:::{note} +:::note Currently, there is no way to update this layout using PhotonLib, although this feature is under consideration. ::: diff --git a/docs/source/_static/assets/3d2019.mp4 b/docs/docs/assets/3d2019.mp4 similarity index 100% rename from docs/source/_static/assets/3d2019.mp4 rename to docs/docs/assets/3d2019.mp4 diff --git a/docs/source/_static/assets/3d2020.mp4 b/docs/docs/assets/3d2020.mp4 similarity index 100% rename from docs/source/_static/assets/3d2020.mp4 rename to docs/docs/assets/3d2020.mp4 diff --git a/docs/source/docs/assets/AprilTag16h5.pdf b/docs/docs/assets/AprilTag16h5.pdf similarity index 100% rename from docs/source/docs/assets/AprilTag16h5.pdf rename to docs/docs/assets/AprilTag16h5.pdf diff --git a/docs/source/_static/assets/AreaRatioFullness.mp4 b/docs/docs/assets/AreaRatioFullness.mp4 similarity index 100% rename from docs/source/_static/assets/AreaRatioFullness.mp4 rename to docs/docs/assets/AreaRatioFullness.mp4 diff --git a/docs/source/_static/assets/calibration_small.mp4 b/docs/docs/assets/calibration_small.mp4 similarity index 100% rename from docs/source/_static/assets/calibration_small.mp4 rename to docs/docs/assets/calibration_small.mp4 diff --git a/docs/source/_static/assets/colorPicker.mp4 b/docs/docs/assets/colorPicker.mp4 similarity index 100% rename from docs/source/_static/assets/colorPicker.mp4 rename to docs/docs/assets/colorPicker.mp4 diff --git a/docs/source/_static/assets/groupingSorting.mp4 b/docs/docs/assets/groupingSorting.mp4 similarity index 100% rename from docs/source/_static/assets/groupingSorting.mp4 rename to docs/docs/assets/groupingSorting.mp4 diff --git a/docs/source/_static/assets/import-export-settings.mp4 b/docs/docs/assets/import-export-settings.mp4 similarity index 100% rename from docs/source/_static/assets/import-export-settings.mp4 rename to docs/docs/assets/import-export-settings.mp4 diff --git a/docs/source/_static/assets/logGui.mp4 b/docs/docs/assets/logGui.mp4 similarity index 100% rename from docs/source/_static/assets/logGui.mp4 rename to docs/docs/assets/logGui.mp4 diff --git a/docs/source/_static/assets/objdetectFiltering.mp4 b/docs/docs/assets/objdetectFiltering.mp4 similarity index 100% rename from docs/source/_static/assets/objdetectFiltering.mp4 rename to docs/docs/assets/objdetectFiltering.mp4 diff --git a/docs/source/_static/assets/offsetandmultiple.mp4 b/docs/docs/assets/offsetandmultiple.mp4 similarity index 100% rename from docs/source/_static/assets/offsetandmultiple.mp4 rename to docs/docs/assets/offsetandmultiple.mp4 diff --git a/docs/source/docs/assets/settings.png b/docs/docs/assets/settings.png similarity index 100% rename from docs/source/docs/assets/settings.png rename to docs/docs/assets/settings.png diff --git a/docs/source/_static/assets/simaimandrange.mp4 b/docs/docs/assets/simaimandrange.mp4 similarity index 100% rename from docs/source/_static/assets/simaimandrange.mp4 rename to docs/docs/assets/simaimandrange.mp4 diff --git a/docs/source/_static/assets/tuningHueSatVal.mp4 b/docs/docs/assets/tuningHueSatVal.mp4 similarity index 100% rename from docs/source/_static/assets/tuningHueSatVal.mp4 rename to docs/docs/assets/tuningHueSatVal.mp4 diff --git a/docs/source/docs/calibration/calibration.md b/docs/docs/calibration/calibration.md similarity index 80% rename from docs/source/docs/calibration/calibration.md rename to docs/docs/calibration/calibration.md index f9f4782da1..f2082aba90 100644 --- a/docs/source/docs/calibration/calibration.md +++ b/docs/docs/calibration/calibration.md @@ -1,16 +1,16 @@ # Calibrating Your Camera -:::{important} +:::important 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 chessboard (or grid of dots, or other target) are taken. by comparing where the grid corners (or dots) should be in object space (for example, a dot 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} +:::warning While any resolution can be calibrated, resolutions lower than 960x720 are often too low to provide accurate results. Additionally, high resolutions may be too performance intensive for a coprocessor like a Raspberry Pi to handle (solutions to this are being looked into). Thus, we recommend 960x720 when using 3D mode. ::: -:::{note} +:::note The calibration data collected during calibration is specific to each physical camera, as well as each individual resolution. ::: @@ -18,15 +18,15 @@ The calibration data collected during calibration is specific to each physical c 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. Practice calibration using your laptop webcam and . The target can be found on the website and should be printed out if possible. Once you print it out, try to line up your target with the overlay on the screen as best as possible. The point of this practice is to notice how you are prompted to place targets in certain positions on the screen that make sure you account for all regions of the sensor. The chessboard should (in general) not be facing parallel to the camera (straight on), nor should it be aligned with any of the camera axes (i.e., rotated only about an axis going left/right, up/down, or out-of-the-camera). -02. 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. -03. Use as big of a calibration target as your printer can print. -04. Ensure that your printed pattern has enough white border around it. -05. Ensure your camera stays in one position during the duration of the calibration. -06. Make sure you get all 12 images from varying distances and angles. -07. Take at least one image that covers the total image area, and generally ensure that you get even coverage of the lens with your image set. -08. Have good lighting, having a diffusely lit target would be best (light specifically shining on the target without shadows). -09. Ensure the calibration target is completely flat and does not bend or fold in any way. It should be mounted/taped down to something flat and then used for calibration, do not just hold it up. +1. Practice calibration using your laptop webcam and [calibdb](https://www.calibdb.net/). The target can be found on the website and should be printed out if possible. Once you print it out, try to line up your target with the overlay on the screen as best as possible. The point of this practice is to notice how you are prompted to place targets in certain positions on the screen that make sure you account for all regions of the sensor. The chessboard should (in general) not be facing parallel to the camera (straight on), nor should it be aligned with any of the camera axes (i.e., rotated only about an axis going left/right, up/down, or out-of-the-camera). +2. 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. +3. Use as big of a calibration target as your printer can print. +4. Ensure that your printed pattern has enough white border around it. +5. Ensure your camera stays in one position during the duration of the calibration. +6. Make sure you get all 12 images from varying distances and angles. +7. Take at least one image that covers the total image area, and generally ensure that you get even coverage of the lens with your image set. +8. Have good lighting, having a diffusely lit target would be best (light specifically shining on the target without shadows). +9. Ensure the calibration target is completely flat and does not bend or fold in any way. It should be mounted/taped down to something flat and then used for calibration, do not just hold it up. 10. Avoid having targets that are parallel to the lens of the camera / straight on towards the camera as much as possible. You want angles and variations within your calibration images. Following the ideas above should help in getting an accurate calibration. @@ -51,7 +51,7 @@ The Cameras tab of the UI houses PhotonVision's camera calibration tooling. It a 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 chessboard. -:::{warning} +:::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. ::: @@ -63,23 +63,18 @@ We'll next select a resolution to calibrate and populate our pattern spacing and Now, we'll capture images of our chessboard from various angles. The most important part of this step is to make sure that the chessboard overlay matches the chessboard 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 at least 12 images, trying to take one in each region of the camera sensor. 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 standard deviation will be shown in the table on the right. -```{raw} html -``` ## Accessing Calibration Images Details about a particular calibration can be viewed by clicking on that resolution in the calibrations tab. This tab allows you to download raw calibration data, upload a previous calibration, and inspect details about calculated camera intrinsic. -```{image} images/cal-details.png -:alt: Captured calibration images -:width: 600 -``` +Captured calibration images -:::{note} +:::note 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) ::: @@ -91,22 +86,19 @@ 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://github.com/PhotonVision/photonvision/blob/master/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 ``` -```{image} images/unpacked-json.png -:alt: Captured calibration images -:width: 600 -``` +Captured calibration images ## Investigating Calibration Data with mrcal [mrcal](https://mrcal.secretsauce.net/tour.html) is a command-line tool for camera calibration and visualization. PhotonVision has the option to use the mrcal backend during camera calibration to estimate intrinsics. mrcal can also be used post-calibration to inspect snapshots and provide feedback. These steps will closely follow the [mrcal tour](https://mrcal.secretsauce.net/tour-initial-calibration.html) -- I'm aggregating commands and notes here, but the mrcal documentation is much more thorough. -Start by [Installing mrcal](https://mrcal.secretsauce.net/install.html). Note that while mrcal *calibration* using PhotonVision is supported on all platforms, but investigation right now only works on Linux. Some users have also reported luck using [WSL 2 on Windows](https://learn.microsoft.com/en-us/windows/wsl/tutorials/gui-apps) as well. You may also need to install `feedgnuplot`. On Ubuntu systems, these commands should be run from a standalone terminal and *not* the one [built into vscode](https://github.com/ros2/ros2/issues/1406). +Start by [Installing mrcal](https://mrcal.secretsauce.net/install.html). Note that while mrcal _calibration_ using PhotonVision is supported on all platforms, but investigation right now only works on Linux. Some users have also reported luck using [WSL 2 on Windows](https://learn.microsoft.com/en-us/windows/wsl/tutorials/gui-apps) as well. You may also need to install `feedgnuplot`. On Ubuntu systems, these commands should be run from a standalone terminal and _not_ the one [built into vscode](https://github.com/ros2/ros2/issues/1406). Let's run `calibrationUtils.py` as described above, and then cd into the output folder. From here, you can follow the mrcal tour, just replacing the VNL filename and camera imager size as necessary. My camera calibration was at 1280x720, so I've set the XY limits to that below. @@ -123,9 +115,7 @@ $ < corners.vnl \ feedgnuplot --domain --square --set 'xrange [0:1280] noextend' --set 'yrange [720:0] noextend' ``` -```{image} images/mrcal-coverage.svg -:alt: A diagram showing the locations of all detected chessboard corners. -``` +![A diagram showing the locations of all detected chessboard corners](images/mrcal-coverage.svg) As you can see, we didn't do a fantastic job of covering our whole camera sensor -- there's a big gap across the whole right side, for example. We also only have 14 calibration images. We've also got our "cameramodel" file, which can be used by mrcal to display additional debug info. @@ -136,20 +126,14 @@ $ mrcal-show-residuals --magnitudes --set 'cbrange [0:1.5]' ./camera-0.cameramod $ mrcal-show-residuals --directions --unset key ./camera-0.cameramodel ``` -```{image} images/residual-magnitudes.svg -:alt: A diagram showing residual magnitudes -``` +![A diagram showing residual magnitudes](images/residual-magnitudes.svg) -```{image} images/residual-directions.svg -:alt: A diagram showing residual directions -``` +![A diagram showing residual directions](images/residual-directions.svg) Clearly we don't have anywhere near enough data to draw any meaningful conclusions (yet). But for fun, let's dig into [camera uncertainty estimation](https://mrcal.secretsauce.net/tour-uncertainty.html). This diagram shows how expected projection error changes due to noise in calibration inputs. Lower projection error across a larger area of the sensor imply a better calibration that more fully covers the whole sensor. For my calibration data, you can tell the projection error isolines (lines of constant expected projection error) are skewed to the left, following my dataset (which was also skewed left). -``` -$ mrcal-show-projection-uncertainty --unset key ./cameramodel_0.cameramodel +```sh +mrcal-show-projection-uncertainty --unset key ./cameramodel_0.cameramodel ``` -```{image} images/camera-uncertainty.svg -:alt: A diagram showing camera uncertainty -``` +![A diagram showing camera uncertainty](images/camera-uncertainty.svg) diff --git a/docs/source/docs/calibration/images/cal-details.png b/docs/docs/calibration/images/cal-details.png similarity index 100% rename from docs/source/docs/calibration/images/cal-details.png rename to docs/docs/calibration/images/cal-details.png diff --git a/docs/source/docs/calibration/images/camera-uncertainty.svg b/docs/docs/calibration/images/camera-uncertainty.svg similarity index 100% rename from docs/source/docs/calibration/images/camera-uncertainty.svg rename to docs/docs/calibration/images/camera-uncertainty.svg diff --git a/docs/source/docs/calibration/images/mrcal-coverage.svg b/docs/docs/calibration/images/mrcal-coverage.svg similarity index 100% rename from docs/source/docs/calibration/images/mrcal-coverage.svg rename to docs/docs/calibration/images/mrcal-coverage.svg diff --git a/docs/source/docs/calibration/images/residual-directions.svg b/docs/docs/calibration/images/residual-directions.svg similarity index 100% rename from docs/source/docs/calibration/images/residual-directions.svg rename to docs/docs/calibration/images/residual-directions.svg diff --git a/docs/source/docs/calibration/images/residual-magnitudes.svg b/docs/docs/calibration/images/residual-magnitudes.svg similarity index 100% rename from docs/source/docs/calibration/images/residual-magnitudes.svg rename to docs/docs/calibration/images/residual-magnitudes.svg diff --git a/docs/source/docs/calibration/images/unpacked-json.png b/docs/docs/calibration/images/unpacked-json.png similarity index 100% rename from docs/source/docs/calibration/images/unpacked-json.png rename to docs/docs/calibration/images/unpacked-json.png diff --git a/docs/source/docs/contributing/assets/git-download.png b/docs/docs/contributing/assets/git-download.png similarity index 100% rename from docs/source/docs/contributing/assets/git-download.png rename to docs/docs/contributing/assets/git-download.png diff --git a/docs/source/docs/contributing/building-docs.md b/docs/docs/contributing/building-docs.md similarity index 100% rename from docs/source/docs/contributing/building-docs.md rename to docs/docs/contributing/building-docs.md diff --git a/docs/source/docs/contributing/building-photon.md b/docs/docs/contributing/building-photon.md similarity index 55% rename from docs/source/docs/contributing/building-photon.md rename to docs/docs/contributing/building-photon.md index 602741b341..45667bce61 100644 --- a/docs/source/docs/contributing/building-photon.md +++ b/docs/docs/contributing/building-photon.md @@ -1,3 +1,6 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + # Build Instructions This section contains the build instructions from the source code available at [our GitHub page](https://github.com/PhotonVision/photonvision). @@ -8,11 +11,11 @@ This section contains the build instructions from the source code available at [ **Java Development Kit:** - This project requires Java Development Kit (JDK) 17 to be compiled. This is the same Java version that comes with WPILib for 2025+. If you don't have this JDK with WPILib, you can follow the instructions to install JDK 17 for your platform [here](https://bell-sw.com/pages/downloads/#jdk-17-lts). +This project requires Java Development Kit (JDK) 17 to be compiled. This is the same Java version that comes with WPILib for 2025+. If you don't have this JDK with WPILib, you can follow the instructions to install JDK 17 for your platform [here](https://bell-sw.com/pages/downloads/#jdk-17-lts). **Node JS:** - The UI is written in Node JS. To compile the UI, Node 14.18.0 to Node 16.0.0 is required. To install Node JS follow the instructions for your platform [on the official Node JS website](https://nodejs.org/en/download/). However, modify this line +The UI is written in Node JS. To compile the UI, Node 14.18.0 to Node 16.0.0 is required. To install Node JS follow the instructions for your platform [on the official Node JS website](https://nodejs.org/en/download/). However, modify this line ```bash nvm install 20 @@ -36,10 +39,7 @@ git clone https://github.com/PhotonVision/photonvision or alternatively download the source code from GitHub and extract the zip: -```{image} assets/git-download.png -:alt: Download source code from git -:width: 600 -``` +Download source code from git ### Install Necessary Node JS Dependencies @@ -53,59 +53,65 @@ npm install In the root directory: -```{eval-rst} -.. tab-set:: - - .. tab-item:: Linux - - ``./gradlew buildAndCopyUI`` - - .. tab-item:: macOS - - ``./gradlew buildAndCopyUI`` - - .. tab-item:: Windows (cmd) - - ``gradlew buildAndCopyUI`` -``` + + + ```bash + ./gradlew buildAndCopyUI + ``` + + + ```bash + ./gradlew buildAndCopyUI + ``` + + + ```cmd + gradlew buildAndCopyUI + ``` + + ### Build and Run PhotonVision To compile and run the project, issue the following command in the root directory: -```{eval-rst} -.. tab-set:: - - .. tab-item:: Linux - - ``./gradlew run`` - - .. tab-item:: macOS - - ``./gradlew run`` - - .. tab-item:: Windows (cmd) - - ``gradlew run`` -``` + + + ```bash + ./gradlew run + ``` + + + ```bash + ./gradlew run + ``` + + + ```cmd + gradlew run + ``` + + Running the following command under the root directory will build the jar under `photon-server/build/libs`: -```{eval-rst} -.. tab-set:: - - .. tab-item:: Linux - - ``./gradlew shadowJar`` - - .. tab-item:: macOS - - ``./gradlew shadowJar`` - - .. tab-item:: Windows (cmd) - - ``gradlew shadowJar`` -``` + + + ```bash + ./gradlew shadowJar + ``` + + + ```bash + ./gradlew shadowJar + ``` + + + ```cmd + gradlew shadowJar + ``` + + ### Build and Run PhotonVision on a Raspberry Pi Coprocessor @@ -113,27 +119,23 @@ As a convenience, the build has a built-in `deploy` command which builds, deploy An architecture override is required to specify the deploy target's architecture. -```{eval-rst} -.. tab-set:: - - .. tab-item:: Linux - - ``./gradlew clean`` - - ``./gradlew deploy -PArchOverride=linuxarm64`` - - .. tab-item:: macOS - - ``./gradlew clean`` - - ``./gradlew deploy -PArchOverride=linuxarm64`` - - .. tab-item:: Windows (cmd) - - ``gradlew clean`` - - ``gradlew deploy -PArchOverride=linuxarm64`` -``` + + + ```bash + ./gradlew deploy -PArchOverride=linuxarm64 + ``` + + + ```bash + ./gradlew deploy -PArchOverride=linuxarm64 + ``` + + + ```cmd + gradlew deploy -PArchOverride=linuxarm64 + ``` + + The `deploy` command is tested against Raspberry Pi coprocessors. Other similar coprocessors may work too. @@ -141,45 +143,48 @@ The `deploy` command is tested against Raspberry Pi coprocessors. Other similar The build process includes the following task: -```{eval-rst} -.. tab-set:: - - .. tab-item:: Linux - - ``./gradlew generateVendorJson`` - - .. tab-item:: macOS - - ``./gradlew generateVendorJson`` - - .. tab-item:: Windows (cmd) - - ``gradlew generateVendorJson`` -``` + + + ```bash + ./gradlew generateVendorJson + ``` + + + ```bash + ./gradlew generateVendorJson + ``` + + + ```cmd + gradlew generateVendorJson + ``` + + This generates a vendordep JSON of your local build at `photon-lib/build/generated/vendordeps/photonlib.json`. The photonlib source can be published to your local maven repository after building: - -```{eval-rst} -.. tab-set:: - - .. tab-item:: Linux - - ``./gradlew publishToMavenLocal`` - - .. tab-item:: macOS - - ``./gradlew publishToMavenLocal`` - - .. tab-item:: Windows (cmd) - - ``gradlew publishToMavenLocal`` -``` + + +`bash + ./gradlew publishToMavenLocal + ` + + +`bash + ./gradlew publishToMavenLocal + ` + + +`cmd + gradlew publishToMavenLocal + ` + + After adding the generated vendordep to your project, add the following to your project's `build.gradle` under the `plugins {}` block. -```Java +```java repositories { mavenLocal() } @@ -187,9 +192,9 @@ repositories { ### Debugging PhotonVision Running Locally -One way is by running the program using gradle with the {code}`--debug-jvm` flag. Run the program with {code}`./gradlew run --debug-jvm`, and attach to it with VSCode by adding the following to {code}`launch.json`. Note args can be passed with {code}`--args="foobar"`. +One way is by running the program using gradle with the `--debug-jvm` flag. Run the program with `./gradlew run --debug-jvm`, and attach to it with VSCode by adding the following to `launch.json`. Note args can be passed with `--args="foobar"`. -``` +```js { // Use IntelliSense to learn about possible attributes. // Hover to view descriptions of existing attributes. @@ -208,13 +213,13 @@ One way is by running the program using gradle with the {code}`--debug-jvm` flag } ``` -PhotonVision can also be run using the gradle tasks plugin with {code}`"args": "--debug-jvm"` added to launch.json. +PhotonVision can also be run using the gradle tasks plugin with `"args": "--debug-jvm"` added to launch.json. ### Debugging PhotonVision Running on a CoProcessor -Set up a VSCode configuration in {code}`launch.json` +Set up a VSCode configuration in `launch.json` -``` +```js { // Use IntelliSense to learn about possible attributes. // Hover to view descriptions of existing attributes. @@ -235,7 +240,7 @@ Set up a VSCode configuration in {code}`launch.json` Stop any existing instance of PhotonVision. -Launch the program with the following additional argument to the JVM: {code}`java -jar -agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:5801 photonvision.jar` +Launch the program with the following additional argument to the JVM: `java -jar -agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:5801 photonvision.jar` Once the program says it is listening on port 5801, launch the debug configuration in VSCode. @@ -246,14 +251,14 @@ The program will wait for the VSCode debugger to attach before proceeding. 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 and photonlib-cpp-examples subdirectories, respectively. The projects currently available include: - photonlib-java-examples: - - aimandrange:simulateJava - - aimattarget:simulateJava - - getinrange:simulateJava - - simaimandrange:simulateJava - - simposeest:simulateJava + - aimandrange:simulateJava + - aimattarget:simulateJava + - getinrange:simulateJava + - simaimandrange:simulateJava + - simposeest:simulateJava - photonlib-cpp-examples: - - aimandrange:simulateNative - - getinrange:simulateNative + - aimandrange:simulateNative + - getinrange:simulateNative To run them, use the commands listed below. PhotonLib must first be published to your local maven repository, then the copy PhotonLib task will copy the generated vendordep json file into each example. After that, the simulateJava/simulateNative task can be used like a normal robot project. Robot simulation with attached debugger is technically possible by using simulateExternalJava and modifying the launch script it exports, though unsupported. diff --git a/docs/source/docs/contributing/developer-docs/index.md b/docs/docs/contributing/developer-docs/index.md similarity index 100% rename from docs/source/docs/contributing/developer-docs/index.md rename to docs/docs/contributing/developer-docs/index.md diff --git a/docs/source/docs/contributing/developer-docs/photonlib-backups.md b/docs/docs/contributing/developer-docs/photonlib-backups.md similarity index 99% rename from docs/source/docs/contributing/developer-docs/photonlib-backups.md rename to docs/docs/contributing/developer-docs/photonlib-backups.md index 87e01703c9..b5a05d5f31 100644 --- a/docs/source/docs/contributing/developer-docs/photonlib-backups.md +++ b/docs/docs/contributing/developer-docs/photonlib-backups.md @@ -9,7 +9,7 @@ The Clarkson Open Source Institute at Clarkson University provides a mirror of o Artifacts from our Maven server can also be backed up locally to a folder called `photonlib-backup` using the following command, which excludes "snapshots" for space reasons: -``` +```bash rsync -avzrHy --no-perms --no-group --no-owner --ignore-errors --exclude ".~tmp~" --exclude "snapshots/org/photonvision/photontargeting*" \ --exclude "snapshots/org/photonvision/photonlib*" maven.photonvision.org::reposilite-data \ /path/to/photonlib-backup diff --git a/docs/source/docs/description.md b/docs/docs/description.md similarity index 100% rename from docs/source/docs/description.md rename to docs/docs/description.md diff --git a/docs/docs/examples/aimandrange.md b/docs/docs/examples/aimandrange.md new file mode 100644 index 0000000000..f6757cfdaa --- /dev/null +++ b/docs/docs/examples/aimandrange.md @@ -0,0 +1,37 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# 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)). + +## Knowledge and Equipment Needed + +- Everything required in \{ref}`Aiming at a Target ` and \{ref}`Getting in Range of the Target `. + +## Code + +Now that you know how to both aim and get in range of the target, it is time to combine them both at the same time. This example will take the previous two code examples and make them into one function using the same tools as before. With this example, you now have all the knowledge you need to use PhotonVision on your robot in any game. + + + +```java reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/aimandrange/src/main/java/frc/robot/Robot.java#L42-L111 +``` + + + ```cpp reference + https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/aimandrange/src/main/java/frc/robot/Robot.java#L27-L71 + ``` + + + ```cpp reference + https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-cpp-examples/aimandrange/src/main/cpp/Robot.cpp#L25-L67 + ``` + + + + + + + diff --git a/docs/docs/examples/aimingatatarget.md b/docs/docs/examples/aimingatatarget.md new file mode 100644 index 0000000000..b53d1cdc03 --- /dev/null +++ b/docs/docs/examples/aimingatatarget.md @@ -0,0 +1,40 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# 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)/[C++](https://github.com/PhotonVision/photonvision/tree/master/photonlib-cpp-examples/aimattarget)). + +## Knowledge and Equipment Needed + +- Robot with a vision system running PhotonVision +- Target +- Ability to track a target by properly tuning a pipeline + +## Code + +Now that you have properly set up your vision system and have tuned a pipeline, you can now aim your robot/turret at the target using the data from PhotonVision. This data is reported over NetworkTables and includes: latency, whether there is a target detected or not, pitch, yaw, area, skew, and target pose relative to the robot. This data will be used/manipulated by our vendor dependency, PhotonLib. The documentation for the Network Tables API can be found \{ref}`here ` and the documentation for PhotonLib \{ref}`here `. + +For this simple example, only yaw is needed. + +In this example, while the operator holds a button down, the robot will turn towards the goal using the P term of a PID loop. To learn more about how PID loops work, how WPILib implements them, and more, visit [Advanced Controls (PID)](https://docs.wpilib.org/en/stable/docs/software/advanced-control/introduction/index.html) and [PID Control in WPILib](https://docs.wpilib.org/en/stable/docs/software/advanced-controls/controllers/pidcontroller.html#pid-control-in-wpilib). + + + +```java reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/aimattarget/src/main/java/frc/robot/Robot.java#L41-L98 +``` + + +```cpp reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-cpp-examples/aimattarget/src/main/include/Robot.h#L27-L53 +``` + + +```cpp reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-cpp-examples/aimattarget/src/main/cpp/Robot.cpp#L25-L52 +``` + + + + diff --git a/docs/source/docs/examples/gettinginrangeofthetarget.md b/docs/docs/examples/gettinginrangeofthetarget.md similarity index 53% rename from docs/source/docs/examples/gettinginrangeofthetarget.md rename to docs/docs/examples/gettinginrangeofthetarget.md index c53b01c9b6..44f56c7de8 100644 --- a/docs/source/docs/examples/gettinginrangeofthetarget.md +++ b/docs/docs/examples/gettinginrangeofthetarget.md @@ -1,10 +1,13 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + # Getting in Range of the Target The following example is from the PhotonLib example repository ([Java](https://github.com/PhotonVision/photonvision/tree/master/photonlib-java-examples/getinrange)/[C++](https://github.com/PhotonVision/photonvision/tree/master/photonlib-cpp-examples/getinrange)). ## Knowledge and Equipment Needed -- Everything required in {ref}`Aiming at a Target `. +- Everything required in \{ref}`Aiming at a Target `. - Large space where your robot can move around freely ## Code @@ -17,42 +20,32 @@ While the operator holds down a button, the robot will drive towards the target This example uses P term of the PID loop and PhotonLib and the distance function of PhotonUtils. -:::{warning} +:::warning The PhotonLib utility to calculate distance depends on the camera being at a different vertical height than the target. If this is not the case, a different method for estimating distance, such as target width or area, should be used. In general, this method becomes more accurate as range decreases and as the height difference increases. ::: -:::{note} +:::note There is no strict minimum delta-height necessary for this method to be applicable, just a requirement that a delta exists. ::: -```{eval-rst} -.. tab-set:: - - .. tab-item:: Java - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/getinrange/src/main/java/frc/robot/Robot.java - :language: java - :lines: 42-107 - :linenos: - :lineno-start: 42 - - .. tab-item:: C++ (Header) - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-cpp-examples/getinrange/src/main/include/Robot.h - :language: c++ - :lines: 27-67 - :linenos: - :lineno-start: 27 - - .. tab-item:: C++ (Source) - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-cpp-examples/getinrange/src/main/cpp/Robot.cpp - :language: c++ - :lines: 25-58 - :linenos: - :lineno-start: 25 + + +```java reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/getinrange/src/main/java/frc/robot/Robot.java#L42-L107 +``` + + +```cpp reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-cpp-examples/getinrange/src/main/include/Robot.h#L27-L67 +``` + + +```cpp reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-cpp-examples/getinrange/src/main/cpp/Robot.cpp#L25-L58 ``` + + -:::{hint} -The accuracy of the measurement of the camera's pitch ({code}`CAMERA_PITCH_RADIANS` in the above example), as well as the camera's FOV, will determine the overall accuracy of this method. +:::tip +The accuracy of the measurement of the camera's pitch (`CAMERA_PITCH_RADIANS` in the above example), as well as the camera's FOV, will determine the overall accuracy of this method. ::: diff --git a/docs/docs/examples/simaimandrange.md b/docs/docs/examples/simaimandrange.md new file mode 100644 index 0000000000..c73d00b8ca --- /dev/null +++ b/docs/docs/examples/simaimandrange.md @@ -0,0 +1,87 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# Simulating Aiming and Getting in Range + +The following example comes from the PhotonLib example repository ([Java](https://github.com/PhotonVision/photonvision/tree/661f8b2c0495474015f6ea9a89d65f9788436a05/photonlib-java-examples/src/main/java/org/photonlib/examples/simaimandrange)/[C++](https://github.com/PhotonVision/photonvision/tree/661f8b2c0495474015f6ea9a89d65f9788436a05/photonlib-cpp-examples/src/main/cpp/examples/simaimandrange)). Full code is available at those links. + +## Knowledge and Equipment Needed + +- Everything required in \{ref}`Combining Aiming and Getting in Range `. + +## Background + +The previous examples show how to run PhotonVision on a real robot, with a physical robot drivetrain moving around and interacting with the software. + +This example builds upon that, adding support for simulating robot motion and incorporating that motion into a `SimVisionSystem`. This allows you to test control algorithms on your development computer, without requiring access to a real robot. + + + +## Walkthrough + +First, in the main `Robot` source file, we add support to periodically update a new simulation-specific object. This logic only gets used while running in simulation: + + + +```java reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/Robot.java#L118-L128 +``` + + + + +Then, we add in the implementation of our new `DrivetrainSim` class. Please reference the [WPILib documentation on physics simulation](https://docs.wpilib.org/en/stable/docs/software/wpilib-tools/robot-simulation/physics-sim.html). + +Simulated Vision support is added with the following steps: + +### Creating the Simulated Vision System + +First, we create a new `SimVisionSystem` to represent our camera and coprocessor running PhotonVision. + + + +```java reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java#L73-L93 +``` + + + +Next, we create objects to represent the physical location and size of the vision targets we are calibrated to detect. This example models the down-field high goal vision target from the 2020 and 2021 games. + + + +```java reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java#L95-L111 +``` + + + + +Finally, we add our target to the simulated vision system. + + + +```java reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java#L116-L117 +``` + + + +If you have additional targets you want to detect, you can add them in the same way as the first one. + +### Updating the Simulated Vision System + +Once we have all the properties of our simulated vision system defined, the work to do at runtime becomes very minimal. Simply pass in the robot's pose periodically to the simulated vision system. + + + +```java reference +https://github.com/PhotonVision/photonvision/blob/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java#124-142 +``` + + + +The rest is done behind the scenes. diff --git a/docs/source/docs/examples/simposeest.md b/docs/docs/examples/simposeest.md similarity index 53% rename from docs/source/docs/examples/simposeest.md rename to docs/docs/examples/simposeest.md index 9e9f6913f3..85a7c8bcfc 100644 --- a/docs/source/docs/examples/simposeest.md +++ b/docs/docs/examples/simposeest.md @@ -1,22 +1,22 @@ # 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/)). Full code is available at that links. +The following example comes from the PhotonLib example repository ([Java](https://github.com/PhotonVision/photonvision/tree/master/photonlib-java-examples/)). Full code is available at that links. ## Knowledge and Equipment Needed -- Everything required in {ref}`Combining Aiming and Getting in Range `, plus some familiarity with WPILib pose estimation functionality. +- Everything required in \{ref}`Combining Aiming and Getting in Range `, plus some familiarity with WPILib pose estimation functionality. ## Background -This example builds upon WPILib's [Differential Drive Pose Estimator](https://github.com/wpilibsuite/allwpilib/tree/main/wpilibjExamples/src/main/java/edu/wpi/first/wpilibj/examples/differentialdriveposeestimator). It adds a {code}`PhotonCamera` to gather estimates of the robot's position on the field. This in turn can be used for aligning with vision targets, and increasing accuracy of autonomous routines. +This example builds upon WPILib's [Differential Drive Pose Estimator](https://github.com/wpilibsuite/allwpilib/tree/main/wpilibjExamples/src/main/java/edu/wpi/first/wpilibj/examples/differentialdriveposeestimator). It adds a `PhotonCamera` to gather estimates of the robot's position on the field. This in turn can be used for aligning with vision targets, and increasing accuracy of autonomous routines. -To support simulation, a {code}`SimVisionSystem` is used to drive data into the {code}`PhotonCamera`. The far high goal target from 2020 is modeled. +To support simulation, a `SimVisionSystem` is used to drive data into the `PhotonCamera`. The far high goal target from 2020 is modeled. ## Walkthrough -WPILib's {code}`Pose2d` class is used to represent robot positions on the field. +WPILib's `Pose2d` class is used to represent robot positions on the field. -Three different {code}`Pose2d` positions are relevant for this example: +Three different `Pose2d` positions are relevant for this example: 1. Desired Pose: The location some autonomous routine wants the robot to be in. 2. Estimated Pose: The location the software `believes` the robot to be in, based on physics models and sensor feedback. @@ -24,9 +24,9 @@ Three different {code}`Pose2d` positions are relevant for this example: ### Estimating Pose -The {code}`DrivetrainPoseEstimator` class is responsible for generating an estimated robot pose using sensor readings (including PhotonVision). +The `DrivetrainPoseEstimator` class is responsible for generating an estimated robot pose using sensor readings (including PhotonVision). -Please reference the [WPILib documentation](https://docs.wpilib.org/en/stable/docs/software/advanced-controls/state-space/state-space-pose_state-estimators.html) on using the {code}`DifferentialDrivePoseEstimator` class. +Please reference the [WPILib documentation](https://docs.wpilib.org/en/stable/docs/software/advanced-controls/state-space/state-space-pose_state-estimators.html) on using the `DifferentialDrivePoseEstimator` class. For both simulation and on-robot code, we create objects to represent the physical location and size of the vision targets we are calibrated to detect. This example models the down-field high goal vision target from the 2020 and 2021 games. @@ -36,7 +36,7 @@ For both simulation and on-robot code, we create objects to represent the physic .. tab-item:: Java :sync: java - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/Constants.java + .. rli:: https://github.com/PhotonVision/photonvision/blob/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/Constants.java :language: java :lines: 83-106 :linenos: @@ -44,7 +44,7 @@ For both simulation and on-robot code, we create objects to represent the physic ``` -To incorporate PhotonVision, we need to create a {code}`PhotonCamera`: +To incorporate PhotonVision, we need to create a `PhotonCamera`: ```{eval-rst} .. tab-set:: @@ -52,14 +52,14 @@ To incorporate PhotonVision, we need to create a {code}`PhotonCamera`: .. tab-item:: Java :sync: java - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/DrivetrainPoseEstimator.java + .. rli:: https://github.com/PhotonVision/photonvision/blob/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/DrivetrainPoseEstimator.java :language: java :lines: 46 :linenos: :lineno-start: 46 ``` -During periodic execution, we read back camera results. If we see a target in the image, we pass the camera-measured pose of the robot to the {code}`DifferentialDrivePoseEstimator`. +During periodic execution, we read back camera results. If we see a target in the image, we pass the camera-measured pose of the robot to the `DifferentialDrivePoseEstimator`. ```{eval-rst} .. tab-set:: @@ -67,7 +67,7 @@ During periodic execution, we read back camera results. If we see a target in th .. tab-item:: Java :sync: java - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/DrivetrainPoseEstimator.java + .. rli:: https://github.com/PhotonVision/photonvision/blob/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/DrivetrainPoseEstimator.java :language: java :lines: 81-92 :linenos: @@ -79,7 +79,7 @@ That's it! ### Simulating the Camera -First, we create a new {code}`SimVisionSystem` to represent our camera and coprocessor running PhotonVision. +First, we create a new `SimVisionSystem` to represent our camera and coprocessor running PhotonVision. ```{eval-rst} .. tab-set:: @@ -87,7 +87,7 @@ First, we create a new {code}`SimVisionSystem` to represent our camera and copro .. tab-item:: Java :sync: java - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/DrivetrainSim.java + .. rli:: https://github.com/PhotonVision/photonvision/blob/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/DrivetrainSim.java :language: java :lines: 76-95 :linenos: @@ -103,7 +103,7 @@ Then, we add our target to the simulated vision system. .. tab-item:: Java :sync: java - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/DrivetrainSim.java + .. rli:: https://github.com/PhotonVision/photonvision/blob/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/DrivetrainSim.java :lines: 97-99 :linenos: :lineno-start: 97 @@ -122,7 +122,7 @@ Once we have all the properties of our simulated vision system defined, the rema .. tab-item:: Java :sync: java - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/DrivetrainSim.java + .. rli:: https://github.com/PhotonVision/photonvision/blob/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simposeest/src/main/java/frc/robot/DrivetrainSim.java :language: java :lines: 138-139 :linenos: diff --git a/docs/source/docs/hardware/customhardware.md b/docs/docs/hardware/customhardware.md similarity index 90% rename from docs/source/docs/hardware/customhardware.md rename to docs/docs/hardware/customhardware.md index 43252b7f84..684ac2c782 100644 --- a/docs/source/docs/hardware/customhardware.md +++ b/docs/docs/hardware/customhardware.md @@ -10,10 +10,7 @@ By default, PhotonVision attempts to make minimal assumptions of the hardware it For Raspberry-Pi based hardware, PhotonVision can use [PiGPIO](https://abyz.me.uk/rpi/pigpio/) to control IO pins. The mapping of which pins control which LED's is part of the hardware config. The pins are active-high: set high when LED's are commanded on, and set low when commanded off. -```{eval-rst} -.. tab-set-code:: - .. code-block:: json - +```js { "ledPins" : [ 13 ], "ledSetCommand" : "", @@ -27,7 +24,7 @@ For Raspberry-Pi based hardware, PhotonVision can use [PiGPIO](https://abyz.me.u } ``` -:::{note} +:::note No hardware boards with status RGB LED pins or non-dimming LED's have been tested yet. Please reach out to the development team if these features are desired, they can assist with configuration and testing. ::: @@ -37,11 +34,8 @@ For Non-Raspberry-Pi hardware, users must provide valid hardware-specific comman Leaving a command blank will disable the associated functionality. -```{eval-rst} -.. tab-set-code:: - .. code-block:: json - - { +```js +{ "cpuTempCommand" : "", "cpuMemoryCommand" : "", "cpuUtilCommand" : "", @@ -49,10 +43,10 @@ Leaving a command blank will disable the associated functionality. "gpuTempCommand" : "", "ramUtilCommand" : "", "restartHardwareCommand" : "", - } +} ``` -:::{note} +:::note These settings have no effect if PhotonVision detects it is running on a Raspberry Pi. See [the MetricsBase class](https://github.com/PhotonVision/photonvision/blob/dbd631da61b7c86b70fa6574c2565ad57d80a91a/photon-core/src/main/java/org/photonvision/common/hardware/metrics/MetricsBase.java) for the commands utilized. ::: @@ -60,22 +54,17 @@ These settings have no effect if PhotonVision detects it is running on a Raspber If your hardware contains a camera with a known field of vision, it can be entered into the hardware configuration. This will prevent users from editing it in the GUI. -```{eval-rst} -.. tab-set-code:: - .. code-block:: json - - { - "vendorFOV" : 98.9 - } +```js +{ + "vendorFOV" : 98.9 +} ``` ## Cosmetic & Branding To help differentiate your hardware from other solutions, some customization is allowed. -```{eval-rst} -.. tab-set-code:: - .. code-block:: json +```js { "deviceName" : "Super Cool Custom Hardware", @@ -84,7 +73,7 @@ To help differentiate your hardware from other solutions, some customization is } ``` -:::{note} +:::note Not all configuration is currently presented in the User Interface. Additional file uploads may be needed to support custom images. ::: @@ -92,9 +81,7 @@ Not all configuration is currently presented in the User Interface. Additional f Here is a complete example `hardwareConfig.json`: -```{eval-rst} -.. tab-set-code:: - .. code-block:: json +```js { "deviceName" : "Blinky McBlinkface", diff --git a/docs/source/docs/hardware/images/bootConfigTxt.png b/docs/docs/hardware/images/bootConfigTxt.png similarity index 100% rename from docs/source/docs/hardware/images/bootConfigTxt.png rename to docs/docs/hardware/images/bootConfigTxt.png diff --git a/docs/source/docs/hardware/images/motionblur.gif b/docs/docs/hardware/images/motionblur.gif similarity index 100% rename from docs/source/docs/hardware/images/motionblur.gif rename to docs/docs/hardware/images/motionblur.gif diff --git a/docs/source/docs/hardware/index.md b/docs/docs/hardware/index.md similarity index 100% rename from docs/source/docs/hardware/index.md rename to docs/docs/hardware/index.md diff --git a/docs/source/docs/hardware/picamconfig.md b/docs/docs/hardware/picamconfig.md similarity index 96% rename from docs/source/docs/hardware/picamconfig.md rename to docs/docs/hardware/picamconfig.md index 4a2226abe5..eeed011210 100644 --- a/docs/source/docs/hardware/picamconfig.md +++ b/docs/docs/hardware/picamconfig.md @@ -6,7 +6,7 @@ The Raspberry Pi CSI Camera port is routed through and processed by the GPU. Sin The GPU is not always capable of detecting other cameras automatically. The file `/boot/config.txt` is parsed by the GPU at boot time to determine what camera, if any, is expected to be attached. This file must be updated for some cameras. -:::{warning} +:::warning Incorrect camera configuration will cause the camera to not be detected. It looks exactly the same as if the camera was unplugged. ::: @@ -14,14 +14,13 @@ Incorrect camera configuration will cause the camera to not be detected. It look After flashing the pi image onto an SD card, open the `boot` segment in a file browser. -:::{note} +:::note Windows may report "There is a problem with this drive". This should be ignored. ::: Locate `config.txt` in the folder, and open it with your favorite text editor. -```{image} images/bootConfigTxt.png -``` + Within the file, find this block of text: @@ -47,7 +46,7 @@ cameraAutoDetect=1 Remove the leading `#` character to uncomment the line associated with your camera. Add a `#` in front of other cameras. -:::{warning} +:::warning Leave lines outside the PhotonVision Camera Config block untouched. They are necessary for proper raspberry pi functionality. ::: diff --git a/docs/source/docs/hardware/selecting-hardware.md b/docs/docs/hardware/selecting-hardware.md similarity index 67% rename from docs/source/docs/hardware/selecting-hardware.md rename to docs/docs/hardware/selecting-hardware.md index 9d26d0a321..ed599eee6e 100644 --- a/docs/source/docs/hardware/selecting-hardware.md +++ b/docs/docs/hardware/selecting-hardware.md @@ -11,22 +11,22 @@ In order to use PhotonVision, you need a coprocessor and a camera. This page wil - CPU: ARM Cortex-A53 (the CPU on Raspberry Pi 3) or better - At least 8GB of storage - 2GB of RAM - - PhotonVision isn't very RAM intensive, but you'll need at least 2GB to run the OS and PhotonVision. + - PhotonVision isn't very RAM intensive, but you'll need at least 2GB to run the OS and PhotonVision. - The following IO: - - At least 1 USB or MIPI-CSI port for the camera - - Note that we only support using the Raspberry Pi's MIPI-CSI port, other MIPI-CSI ports from other coprocessors may not work. - - Ethernet port for networking + - At least 1 USB or MIPI-CSI port for the camera + - Note that we only support using the Raspberry Pi's MIPI-CSI port, other MIPI-CSI ports from other coprocessors may not work. + - Ethernet port for networking ### Coprocessor Recommendations When selecting a coprocessor, it is important to consider various factors, particularly when it comes to AprilTag detection. Opting for a coprocessor with a more powerful CPU can generally result in higher FPS AprilTag detection, leading to more accurate pose estimation. However, it is important to note that there is a point of diminishing returns, where the benefits of a more powerful CPU may not outweigh the additional cost. Below is a list of supported hardware, along with some notes on each. - Orange Pi 5 (\$99) - - This is the recommended coprocessor for most teams. It has a powerful CPU that can handle AprilTag detection at high FPS, and is relatively cheap compared to processors of a similar power. + - This is the recommended coprocessor for most teams. It has a powerful CPU that can handle AprilTag detection at high FPS, and is relatively cheap compared to processors of a similar power. - Raspberry Pi 4/5 (\$55-\$80) - - This is the recommended coprocessor for teams on a budget. It has a less powerful CPU than the Orange Pi 5, but is still capable of running PhotonVision at a reasonable FPS. + - This is the recommended coprocessor for teams on a budget. It has a less powerful CPU than the Orange Pi 5, but is still capable of running PhotonVision at a reasonable FPS. - Mini PCs (such as Beelink N5095) - - This coprocessor will likely have similar performance to the Orange Pi 5 but has a higher performance ceiling (when using more powerful CPUs). Do note that this would require extra effort to wire to the robot / get set up. More information can be found in the set up guide [here.](https://docs.google.com/document/d/1lOSzG8iNE43cK-PgJDDzbwtf6ASyf4vbW8lQuFswxzw/edit?usp=drivesdk) + - This coprocessor will likely have similar performance to the Orange Pi 5 but has a higher performance ceiling (when using more powerful CPUs). Do note that this would require extra effort to wire to the robot / get set up. More information can be found in the set up guide [here.](https://docs.google.com/document/d/1lOSzG8iNE43cK-PgJDDzbwtf6ASyf4vbW8lQuFswxzw/edit?usp=drivesdk) - Other coprocessors can be used but may require some extra work / command line usage in order to get it working properly. ## Choosing a Camera @@ -35,11 +35,11 @@ PhotonVision works with Pi Cameras and most USB Cameras, the recommendations bel PhotonVision relies on [CSCore](https://github.com/wpilibsuite/allwpilib/tree/main/cscore) to detect and process cameras, so camera support is determined based off compatibility with CScore along with native support for the camera within your OS (ex. [V4L compatibility](https://en.wikipedia.org/wiki/Video4Linux) if using a Linux machine like a Raspberry Pi). -:::{note} +:::note Logitech Cameras and integrated laptop cameras will not work with PhotonVision due to oddities with their drivers. We recommend using a different camera. ::: -:::{note} +:::note We do not currently support the usage of two of the same camera on the same coprocessor. You can only use two or more cameras if they are of different models or they are from Arducam, which has a [tool that allows for cameras to be renamed](https://docs.arducam.com/UVC-Camera/Serial-Number-Tool-Guide/). ::: @@ -52,12 +52,12 @@ For driver camera, we recommend a USB camera with a fisheye lens, so your driver For AprilTag detection, we recommend you use a global shutter camera that has ~100 degree diagonal FOV. This will allow you to see more AprilTags in frame, and will allow for more accurate pose estimation. You also want a camera that supports high FPS, as this will allow you to update your pose estimator at a higher frequency. - Recommendations For AprilTag Detection - - Arducam USB OV9281 - - This is the recommended camera for AprilTag detection as it is a high FPS, global shutter camera USB camera that has a ~70 degree FOV. - - Innomaker OV9281 - - Spinel AR0144 - - Pi Camera Module V1 - - The V1 is strongly preferred over the V2 due to the V2 having undesirable FOV choices + - Arducam USB OV9281 + - This is the recommended camera for AprilTag detection as it is a high FPS, global shutter camera USB camera that has a ~70 degree FOV. + - Innomaker OV9281 + - Spinel AR0144 + - Pi Camera Module V1 + - The V1 is strongly preferred over the V2 due to the V2 having undesirable FOV choices ### AprilTags and Motion Blur @@ -67,30 +67,20 @@ When detecting AprilTags, you want to reduce the "motion blur" as much as possib 2. Using a global shutter (as opposed to rolling shutter) camera. This should eliminate most, if not all motion blur. 3. Only rely on tags when not moving. -```{image} images/motionblur.gif -:align: center -``` + ### Using Multiple Cameras -Using multiple cameras on your robot will help you detect more AprilTags at once and improve your pose estimation as a result. In order to use multiple cameras, you will need to create multiple PhotonPoseEstimators and add all of their measurements to a single drivetrain pose estimator. Please note that the accuracy of your robot to camera transform is especially important when using multiple cameras as any error in the transform will cause your pose estimations to "fight" each other. For more information, see {ref}`the programming reference. `. +Using multiple cameras on your robot will help you detect more AprilTags at once and improve your pose estimation as a result. In order to use multiple cameras, you will need to create multiple PhotonPoseEstimators and add all of their measurements to a single drivetrain pose estimator. Please note that the accuracy of your robot to camera transform is especially important when using multiple cameras as any error in the transform will cause your pose estimations to "fight" each other. For more information, see \{ref}`the programming reference. `. ## Performance Matrix -```{raw} html - - + - -``` Please submit performance data to be added to the matrix here: -```{raw} html - - + - -``` diff --git a/docs/source/docs/installation/images/gh_actions_1.png b/docs/docs/installation/images/gh_actions_1.png similarity index 100% rename from docs/source/docs/installation/images/gh_actions_1.png rename to docs/docs/installation/images/gh_actions_1.png diff --git a/docs/source/docs/installation/images/gh_actions_2.png b/docs/docs/installation/images/gh_actions_2.png similarity index 100% rename from docs/source/docs/installation/images/gh_actions_2.png rename to docs/docs/installation/images/gh_actions_2.png diff --git a/docs/source/docs/installation/images/gh_actions_3.png b/docs/docs/installation/images/gh_actions_3.png similarity index 100% rename from docs/source/docs/installation/images/gh_actions_3.png rename to docs/docs/installation/images/gh_actions_3.png diff --git a/docs/source/docs/installation/images/networking-diagram.png b/docs/docs/installation/images/networking-diagram.png similarity index 100% rename from docs/source/docs/installation/images/networking-diagram.png rename to docs/docs/installation/images/networking-diagram.png diff --git a/docs/source/docs/installation/images/pololu-diagram.png b/docs/docs/installation/images/pololu-diagram.png similarity index 100% rename from docs/source/docs/installation/images/pololu-diagram.png rename to docs/docs/installation/images/pololu-diagram.png diff --git a/docs/source/docs/installation/images/release-page.png b/docs/docs/installation/images/release-page.png similarity index 100% rename from docs/source/docs/installation/images/release-page.png rename to docs/docs/installation/images/release-page.png diff --git a/docs/source/docs/installation/images/static.png b/docs/docs/installation/images/static.png similarity index 100% rename from docs/source/docs/installation/images/static.png rename to docs/docs/installation/images/static.png diff --git a/docs/source/docs/installation/index.md b/docs/docs/installation/index.md similarity index 98% rename from docs/source/docs/installation/index.md rename to docs/docs/installation/index.md index fe42022db1..cc2823e57c 100644 --- a/docs/source/docs/installation/index.md +++ b/docs/docs/installation/index.md @@ -6,7 +6,7 @@ This page will help you install PhotonVision on your coprocessor, wire it, and p This section will walk you through how to install PhotonVision on your coprocessor. Your coprocessor is the device that has the camera and you are using to detect targets (ex. if you are using a Limelight / Raspberry Pi, that is your coprocessor and you should follow those instructions). -:::{warning} +:::warning You only need to install PhotonVision on the coprocessor/device that is being used to detect targets, you do NOT need to install it on the device you use to view the webdashboard. All you need to view the webdashboard is for a device to be on the same network as your vision coprocessor and an internet browser. ::: diff --git a/docs/source/docs/installation/networking.md b/docs/docs/installation/networking.md similarity index 80% rename from docs/source/docs/installation/networking.md rename to docs/docs/installation/networking.md index fd46ad3873..f93a47f491 100644 --- a/docs/source/docs/installation/networking.md +++ b/docs/docs/installation/networking.md @@ -1,24 +1,25 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + # Networking ## Physical Networking -:::{note} -When using PhotonVision off robot, you *MUST* plug the coprocessor into a physical router/radio. You can then connect your laptop/device used to view the webdashboard to the same network. Any other networking setup will not work and will not be supported in any capacity. +:::note +When using PhotonVision off robot, you _MUST_ plug the coprocessor into a physical router/radio. You can then connect your laptop/device used to view the webdashboard to the same network. Any other networking setup will not work and will not be supported in any capacity. ::: After imaging your coprocessor, run an ethernet cable from your coprocessor to a router/radio and power on your coprocessor by plugging it into the wall. Then connect whatever device you're using to view the webdashboard to the same network and navigate to photonvision.local:5800. -PhotonVision *STRONGLY* recommends the usage of a network switch on your robot. This is because the second radio port on the current FRC radios is known to be buggy and cause frequent connection issues that are detrimental during competition. An in-depth guide on how to install a network switch can be found [on FRC 900's website](https://team900.org/blog/ZebraSwitch/). +PhotonVision _STRONGLY_ recommends the usage of a network switch on your robot. This is because the second radio port on the current FRC radios is known to be buggy and cause frequent connection issues that are detrimental during competition. An in-depth guide on how to install a network switch can be found [on FRC 900's website](https://team900.org/blog/ZebraSwitch/). -```{image} images/networking-diagram.png -:alt: Correctly set static IP -``` +Correctly set static IP ## Digital Networking -PhotonVision *STRONGLY* recommends the usage of Static IPs as it increases reliability on the field and when using PhotonVision in general. To properly set up your static IP, follow the steps below: +PhotonVision _STRONGLY_ recommends the usage of Static IPs as it increases reliability on the field and when using PhotonVision in general. To properly set up your static IP, follow the steps below: -:::{warning} +:::warning Only use a static IP when connected to the **robot radio**, and never when testing at home, unless you are well versed in networking or have the relevant "know how". ::: @@ -33,27 +34,26 @@ Only use a static IP when connected to the **robot radio**, and never when testi Power-cycle your robot and then you will now be access the PhotonVision dashboard at `10.TE.AM.11:5800`. -```{image} images/static.png -:alt: Correctly set static IP -``` +Correctly set static IP ## Port Forwarding If you would like to access your Ethernet-connected vision device from a computer when tethered to the USB port on the roboRIO, you can use [WPILib's](https://docs.wpilib.org/en/stable/docs/networking/networking-utilities/portforwarding.html) `PortForwarder`. -```{eval-rst} -.. tab-set-code:: - - .. code-block:: java - - PortForwarder.add(5800, "photonvision.local", 5800); - - .. code-block:: C++ - - wpi::PortForwarder::GetInstance().Add(5800, "photonvision.local", 5800); + + +```java +PortForwarder.add(5800, "photonvision.local", 5800); +``` + + +```cpp +wpi::PortForwarder::GetInstance().Add(5800, "photonvision.local", 5800); ``` + + -:::{note} +:::note The address in the code above (`photonvision.local`) is the hostname of the coprocessor. This can be different depending on your hardware, and can be checked in the settings tab under "hostname". ::: diff --git a/docs/source/docs/installation/sw_install/advanced-cmd.md b/docs/docs/installation/sw_install/advanced-cmd.md similarity index 99% rename from docs/source/docs/installation/sw_install/advanced-cmd.md rename to docs/docs/installation/sw_install/advanced-cmd.md index ba974218b4..69db5c161b 100644 --- a/docs/source/docs/installation/sw_install/advanced-cmd.md +++ b/docs/docs/installation/sw_install/advanced-cmd.md @@ -41,7 +41,7 @@ WantedBy=multi-user.target Then copy the `.service` file to `/etc/systemd/system/` using `cp photonvision.service /etc/systemd/system/photonvision.service`. Then modify the file to have `644` permissions using `chmod 644 /etc/systemd/system/photonvision.service`. -:::{note} +:::note Many ARM processors have a big.LITTLE architecture where some of the CPU cores are more powerful than others. On this type of architecture, you may get more consistent performance by limiting which cores PhotonVision can use. To do this, add the parameter `AllowedCPUs` to the systemd service file in the `[Service]` section. For instance, for an Orange Pi 5, cores 4 through 7 are the fast ones, and you can target those cores with the line `AllowedCPUs=4-7`. @@ -51,6 +51,6 @@ For instance, for an Orange Pi 5, cores 4 through 7 are the fast ones, and you c To install the service, simply run `systemctl enable photonvision.service`. -:::{note} +:::note It is recommended to reload configurations by running `systemctl daemon-reload`. ::: diff --git a/docs/source/docs/installation/sw_install/files/Limelight2+/hardwareConfig.json b/docs/docs/installation/sw_install/files/Limelight2+/hardwareConfig.json similarity index 100% rename from docs/source/docs/installation/sw_install/files/Limelight2+/hardwareConfig.json rename to docs/docs/installation/sw_install/files/Limelight2+/hardwareConfig.json diff --git a/docs/source/docs/installation/sw_install/files/Limelight2/hardwareConfig.json b/docs/docs/installation/sw_install/files/Limelight2/hardwareConfig.json similarity index 100% rename from docs/source/docs/installation/sw_install/files/Limelight2/hardwareConfig.json rename to docs/docs/installation/sw_install/files/Limelight2/hardwareConfig.json diff --git a/docs/source/docs/installation/sw_install/gloworm.md b/docs/docs/installation/sw_install/gloworm.md similarity index 94% rename from docs/source/docs/installation/sw_install/gloworm.md rename to docs/docs/installation/sw_install/gloworm.md index 2a52497660..29569d5549 100644 --- a/docs/source/docs/installation/sw_install/gloworm.md +++ b/docs/docs/installation/sw_install/gloworm.md @@ -18,7 +18,7 @@ Select the compute module. If it doesn't show up after 30s try using another USB Hit flash. Wait for flashing to complete, then disconnect your USB C cable. -:::{warning} +:::warning Using a version of Balena Etcher older than 1.18.11 may cause bootlooping (the system will repeatedly boot and restart) when imaging your Gloworm. Updating to 1.18.11 will fix this issue. ::: @@ -34,16 +34,15 @@ A static IP address may be used as an alternative to the mDNS `photonvision.loca Download and run [Angry IP Scanner](https://angryip.org/download/#windows) to find PhotonVision/your coprocessor on your network. -```{image} images/angryIP.png -``` + -Once you find it, set the IP to a desired {ref}`static IP in PhotonVision. ` +Once you find it, set the IP to a desired \{ref}`static IP in PhotonVision. ` ## Updating PhotonVision Download the latest stable .jar from [the releases page](https://github.com/PhotonVision/photonvision/releases), go to the settings tab, and upload the .jar using the Offline Update button. -:::{note} +:::note If you are updating PhotonVision on a Gloworm/Limelight, download the LinuxArm64 .jar file. ::: diff --git a/docs/source/docs/installation/sw_install/images/angryIP.png b/docs/docs/installation/sw_install/images/angryIP.png similarity index 100% rename from docs/source/docs/installation/sw_install/images/angryIP.png rename to docs/docs/installation/sw_install/images/angryIP.png diff --git a/docs/source/docs/installation/sw_install/images/nano.png b/docs/docs/installation/sw_install/images/nano.png similarity index 100% rename from docs/source/docs/installation/sw_install/images/nano.png rename to docs/docs/installation/sw_install/images/nano.png diff --git a/docs/source/docs/installation/sw_install/index.md b/docs/docs/installation/sw_install/index.md similarity index 100% rename from docs/source/docs/installation/sw_install/index.md rename to docs/docs/installation/sw_install/index.md diff --git a/docs/source/docs/installation/sw_install/limelight.md b/docs/docs/installation/sw_install/limelight.md similarity index 56% rename from docs/source/docs/installation/sw_install/limelight.md rename to docs/docs/installation/sw_install/limelight.md index e819fd6a48..b7cedb7bc2 100644 --- a/docs/source/docs/installation/sw_install/limelight.md +++ b/docs/docs/installation/sw_install/limelight.md @@ -6,19 +6,19 @@ Limelight imaging is a very similar process to Gloworm, but with extra steps. ### Base Install Steps -Due to the similarities in hardware, follow the {ref}`Gloworm install instructions `. +Due to the similarities in hardware, follow the \{ref}`Gloworm install instructions `. ## Hardware-Specific Steps Download the hardwareConfig.json file for the version of your Limelight: -- {download}`Limelight Version 2 `. -- {download}`Limelight Version 2+ `. +- \{download}`Limelight Version 2 `. +- \{download}`Limelight Version 2+ `. -:::{note} +:::note No hardware config is provided for the Limelight 3 as AprilTags do not require the LEDs (meaning nobody has reverse-engineered what I/O pins drive the LEDs) and the camera FOV is determined as part of calibration. ::: -{ref}`Import the hardwareConfig.json file `. Again, this is **REQUIRED** or target measurements will be incorrect, and LEDs will not work. +\{ref}`Import the hardwareConfig.json file `. Again, this is **REQUIRED** or target measurements will be incorrect, and LEDs will not work. After installation you should be able to [locate the camera](https://photonvision.github.io/gloworm-docs/docs/quickstart/#finding-gloworm) at: `http://photonvision.local:5800/` (not `gloworm.local`, as previously) diff --git a/docs/source/docs/installation/sw_install/linux-pc.md b/docs/docs/installation/sw_install/linux-pc.md similarity index 97% rename from docs/source/docs/installation/sw_install/linux-pc.md rename to docs/docs/installation/sw_install/linux-pc.md index 3c6e63e4a7..88e5a96e17 100644 --- a/docs/source/docs/installation/sw_install/linux-pc.md +++ b/docs/docs/installation/sw_install/linux-pc.md @@ -2,7 +2,7 @@ PhotonVision may be run on a Debian-based Linux Desktop PC for basic testing and evaluation. -:::{note} +:::note You do not need to install PhotonVision on a Windows PC in order to access the webdashboard (assuming you are using an external coprocessor like a Raspberry Pi). ::: @@ -14,7 +14,7 @@ PhotonVision requires a JDK installed and on the system path. JDK 11 is needed ( $ sudo apt-get install openjdk-11-jdk ``` -:::{warning} +:::warning Using a JDK other than JDK11 will cause issues when running PhotonVision and is not supported. ::: @@ -22,13 +22,13 @@ Using a JDK other than JDK11 will cause issues when running PhotonVision and is Go to the [GitHub releases page](https://github.com/PhotonVision/photonvision/releases) and download the relevant .jar file for your coprocessor. -:::{note} +:::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. ::: -:::{warning} +:::warning Be careful to pick the latest stable release. "Draft" or "Pre-Release" versions are not stable and often have bugs. ::: diff --git a/docs/source/docs/installation/sw_install/mac-os.md b/docs/docs/installation/sw_install/mac-os.md similarity index 95% rename from docs/source/docs/installation/sw_install/mac-os.md rename to docs/docs/installation/sw_install/mac-os.md index 8c2c7b342e..e951ab3a71 100644 --- a/docs/source/docs/installation/sw_install/mac-os.md +++ b/docs/docs/installation/sw_install/mac-os.md @@ -1,10 +1,10 @@ # Mac OS Installation -:::{warning} +:::warning Due to current [cscore](https://github.com/wpilibsuite/allwpilib/tree/main/cscore) restrictions, the PhotonVision server backend may have issues running macOS. ::: -:::{note} +:::note You do not need to install PhotonVision on a Windows PC in order to access the webdashboard (assuming you are using an external coprocessor like a Raspberry Pi). ::: @@ -14,7 +14,7 @@ VERY Limited macOS support is available. 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. If not, [download and install it from here](https://adoptium.net/temurin/releases?version=11). -:::{warning} +:::warning Using a JDK other than JDK11 will cause issues when running PhotonVision and is not supported. ::: @@ -22,13 +22,13 @@ Using a JDK other than JDK11 will cause issues when running PhotonVision and is Go to the [GitHub releases page](https://github.com/PhotonVision/photonvision/releases) and download the relevant .jar file for your coprocessor. -:::{note} +:::note If you have an M1/M2 Mac, download the macarm64.jar file. If you have an Intel based Mac, download the macx64.jar file. ::: -:::{warning} +:::warning Be careful to pick the latest stable release. "Draft" or "Pre-Release" versions are not stable and often have bugs. ::: @@ -40,7 +40,7 @@ To run PhotonVision, open a terminal window of your choice and run the following $ java -jar /path/to/photonvision/photonvision-xxx.jar ``` -:::{warning} +:::warning Due to current [cscore](https://github.com/wpilibsuite/allwpilib/tree/main/cscore) restrictions, the PhotonVision using test mode is all that is known to work currently. ::: @@ -48,6 +48,6 @@ Due to current [cscore](https://github.com/wpilibsuite/allwpilib/tree/main/cscor Once the Java backend is up and running, you can access the main vision interface by navigating to `localhost:5800` inside your browser. -:::{warning} +:::warning Due to current [cscore](https://github.com/wpilibsuite/allwpilib/tree/main/cscore) restrictions, it is unlikely any streams will open from real webcams. ::: diff --git a/docs/source/docs/installation/sw_install/orange-pi.md b/docs/docs/installation/sw_install/orange-pi.md similarity index 79% rename from docs/source/docs/installation/sw_install/orange-pi.md rename to docs/docs/installation/sw_install/orange-pi.md index b03c7ffabe..f6dc26b1e2 100644 --- a/docs/source/docs/installation/sw_install/orange-pi.md +++ b/docs/docs/installation/sw_install/orange-pi.md @@ -2,7 +2,7 @@ ## Downloading Linux Image -Starting in 2024, PhotonVision provides pre-configured system images for Orange Pi 5 devices. Download the latest release of the PhotonVision Orange Pi 5 image (.xz file suffixed with `orangepi5.xz`) from the [releases page](https://github.com/PhotonVision/photonvision/releases). You do not need to extract the downloaded archive file. This image is configured with a `pi` user with password `raspberry`. +Starting in 2024, PhotonVision provides pre-configured system images for Orange Pi 5 devices. Download the latest release of the PhotonVision Orange Pi 5 image (.xz file suffixed with `orangepi5.xz`) from the [releases page](https://github.com/PhotonVision/photonvision/releases). You do not need to extract the downloaded archive file. This image is configured with a `pi` user with password `raspberry`. For an Orange Pi 4, download the latest release of the Armbian Bullseye CLI image from [here](https://armbian.tnahosting.net/archive/orangepi4/archive/Armbian_23.02.2_Orangepi4_bullseye_current_5.15.93.img.xz). @@ -14,7 +14,7 @@ Use the 1.18.11 version of [Balena Etcher](https://github.com/balena-io/etcher/r For more detailed instructions on using Etcher, please see the [Etcher website](https://www.balena.io/etcher/). -:::{warning} +:::warning Using a version of Balena Etcher older than 1.18.11 may cause bootlooping (the system will repeatedly boot and restart) when imaging your Orange Pi. Updating to 1.18.11 will fix this issue. ::: @@ -22,7 +22,7 @@ Alternatively, you can use the [Raspberry Pi Imager](https://www.raspberrypi.com Select "Choose OS" and then "Use custom" to select the downloaded image file. Select your microSD card and flash. -:::{note} +:::note If you are working on Linux, "dd" can be used in the command line to flash an image. ::: @@ -36,4 +36,4 @@ Plug your Orange Pi into a display via HDMI and plug in a keyboard via USB once ## Installing PhotonVision (Orange Pi 4 Only) -From here, you can follow {ref}`this guide `. +From here, you can follow \{ref}`this guide `. diff --git a/docs/source/docs/installation/sw_install/other-coprocessors.md b/docs/docs/installation/sw_install/other-coprocessors.md similarity index 92% rename from docs/source/docs/installation/sw_install/other-coprocessors.md rename to docs/docs/installation/sw_install/other-coprocessors.md index d6b6fc2776..729d71b5f1 100644 --- a/docs/source/docs/installation/sw_install/other-coprocessors.md +++ b/docs/docs/installation/sw_install/other-coprocessors.md @@ -1,10 +1,10 @@ # Other Debian-Based Co-Processor Installation -:::{warning} +:::warning Working with unsupported coprocessors requires some level of "know how" of your target system. The install script has only been tested on Debian/Raspberry Pi OS Buster and Ubuntu Bionic. If any issues arise with your specific OS, please open an issue on our [issues page](https://github.com/PhotonVision/photonvision/issues). ::: -:::{note} +:::note We'd love to have your input! If you get PhotonVision working on another coprocessor, consider documenting your steps and submitting a [docs issue](https://github.com/PhotonVision/photonvision-docs/issues)., [pull request](https://github.com/PhotonVision/photonvision-docs/pulls) , or [ping us on Discord](https://discord.com/invite/wYxTwym). For example, Limelight and Romi install instructions came about because someone spent the time to figure it out, and did a writeup. ::: @@ -19,11 +19,11 @@ $ sudo ./install.sh $ sudo reboot now ``` -:::{note} +:::note 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 `. +For installation on any other co-processors, we recommend reading the \{ref}`advanced command line documentation `. ## Updating PhotonVision diff --git a/docs/source/docs/installation/sw_install/raspberry-pi.md b/docs/docs/installation/sw_install/raspberry-pi.md similarity index 85% rename from docs/source/docs/installation/sw_install/raspberry-pi.md rename to docs/docs/installation/sw_install/raspberry-pi.md index d8e851d51e..f26cf9c5a3 100644 --- a/docs/source/docs/installation/sw_install/raspberry-pi.md +++ b/docs/docs/installation/sw_install/raspberry-pi.md @@ -6,7 +6,7 @@ A Pre-Built Raspberry Pi image is available for ease of installation. Download the latest release of the PhotonVision Raspberry image (.xz file) from the [releases page](https://github.com/PhotonVision/photonvision/releases). You do not need to extract the downloaded ZIP file. -:::{note} +:::note Make sure you download the image that ends in '-RasberryPi.xz'. ::: @@ -18,7 +18,7 @@ Use the 1.18.11 version of [Balena Etcher](https://github.com/balena-io/etcher/r For more detailed instructions on using Etcher, please see the [Etcher website](https://www.balena.io/etcher/). -:::{warning} +:::warning Using a version of Balena Etcher older than 1.18.11 may cause bootlooping (the system will repeatedly boot and restart) when imaging your Raspberry Pi. Updating to 1.18.11 will fix this issue. ::: @@ -26,7 +26,7 @@ Alternatively, you can use the [Raspberry Pi Imager](https://www.raspberrypi.com Select "Choose OS" and then "Use custom" to select the downloaded image file. Select your microSD card and flash. -If you are using a non-standard Pi Camera connected to the CSI port, {ref}`additional configuration may be required. ` +If you are using a non-standard Pi Camera connected to the CSI port, \{ref}`additional configuration may be required. ` ## Final Steps @@ -40,11 +40,10 @@ A static IP address may be used as an alternative to the mDNS `photonvision.loca Download and run [Angry IP Scanner](https://angryip.org/download/#windows) to find PhotonVision/your coprocessor on your network. -```{image} images/angryIP.png -``` + -Once you find it, set the IP to a desired {ref}`static IP in PhotonVision. ` +Once you find it, set the IP to a desired \{ref}`static IP in PhotonVision. ` ## Updating PhotonVision -To upgrade a Raspberry Pi device with PhotonVision already installed, follow the {ref}`Raspberry Pi update instructions`. +To upgrade a Raspberry Pi device with PhotonVision already installed, follow the \{ref}`Raspberry Pi update instructions`. diff --git a/docs/docs/installation/sw_install/romi.md b/docs/docs/installation/sw_install/romi.md new file mode 100644 index 0000000000..f7b4a3af5f --- /dev/null +++ b/docs/docs/installation/sw_install/romi.md @@ -0,0 +1,21 @@ +# Romi Installation + +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`. + +Follow the process for installing PhotonVision on \{ref}`"Other Debian-Based Co-Processor Installation" `. As it mentions this will require an internet connection so plugging into the ethernet jack on the Raspberry Pi will be the easiest solution. The pi must remain writable! + +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`. + + + +After it reboots, you should be able to [locate the PhotonVision UI](https://photonvision.github.io/gloworm-docs/docs/quickstart/#finding-gloworm) at: `http://10.0.0.2:5800/`. + +:::warning +In order for settings, logs, etc. to be saved / take effect, ensure that PhotonVision is in writable mode. +::: diff --git a/docs/source/docs/installation/sw_install/snakeyes.md b/docs/docs/installation/sw_install/snakeyes.md similarity index 94% rename from docs/source/docs/installation/sw_install/snakeyes.md rename to docs/docs/installation/sw_install/snakeyes.md index e099fde408..cdca36ddd3 100644 --- a/docs/source/docs/installation/sw_install/snakeyes.md +++ b/docs/docs/installation/sw_install/snakeyes.md @@ -14,7 +14,7 @@ Use the 1.18.11 version of [Balena Etcher](https://github.com/balena-io/etcher/r For more detailed instructions on using Etcher, please see the [Etcher website](https://www.balena.io/etcher/). -:::{warning} +:::warning Using a version of Balena Etcher older than 1.18.11 may cause bootlooping (the system will repeatedly boot and restart) when imaging your Raspberry Pi. Updating to 1.18.11 will fix this issue. ::: @@ -34,10 +34,9 @@ A static IP address may be used as an alternative to the mDNS `photonvision.loca Download and run [Angry IP Scanner](https://angryip.org/download/#windows) to find PhotonVision/your coprocessor on your network. -```{image} images/angryIP.png -``` + -Once you find it, set the IP to a desired {ref}`static IP in PhotonVision. ` +Once you find it, set the IP to a desired \{ref}`static IP in PhotonVision. ` ## Updating PhotonVision diff --git a/docs/source/docs/installation/sw_install/windows-pc.md b/docs/docs/installation/sw_install/windows-pc.md similarity index 98% rename from docs/source/docs/installation/sw_install/windows-pc.md rename to docs/docs/installation/sw_install/windows-pc.md index 9bfde737c5..6ee55d7eb0 100644 --- a/docs/source/docs/installation/sw_install/windows-pc.md +++ b/docs/docs/installation/sw_install/windows-pc.md @@ -2,7 +2,7 @@ PhotonVision may be run on a Windows Desktop PC for basic testing and evaluation. -:::{note} +:::note You do not need to install PhotonVision on a Windows PC in order to access the webdashboard (assuming you are using an external coprocessor like a Raspberry Pi). ::: @@ -14,7 +14,7 @@ Bonjour provides more stable networking when using Windows PCs. Install [Bonjour 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} +:::warning Using a JDK other than JDK11 will cause issues when running PhotonVision and is not supported. ::: @@ -32,7 +32,7 @@ To run PhotonVision, open a terminal window of your choice and run the following If your computer has a compatible webcam connected, PhotonVision should startup without any error messages. If there are error messages, your webcam isn't supported or another issue has occurred. If it is the latter, please open an issue on the [PhotonVision issues page](https://github.com/PhotonVision/photonvision/issues). -:::{warning} +:::warning Using an integrated laptop camera may cause issues when trying to run PhotonVision. If you are unable to run PhotonVision on a laptop with an integrated camera, try disabling the camera's driver in Windows Device Manager. ::: diff --git a/docs/source/docs/installation/updating.md b/docs/docs/installation/updating.md similarity index 67% rename from docs/source/docs/installation/updating.md rename to docs/docs/installation/updating.md index 76ad2ea54f..3af0b73f3a 100644 --- a/docs/source/docs/installation/updating.md +++ b/docs/docs/installation/updating.md @@ -2,22 +2,20 @@ PhotonVision provides many different files on a single release page. Each release contains JAR files for performing "offline updates" of a device with PhotonVision already installed, as well as full image files to "flash" to supported coprocessors. -```{image} images/release-page.png -:alt: Example GitHub release page -``` +Example GitHub release page In the example release above, we see: - Image files for flashing directly to supported coprocessors. - - Raspberry Pi 3/4/5/CM4: follow our {ref}`Raspberry Pi flashing instructions`. - - For LimeLight devices: follow our {ref}`LimeLight flashing instructions`. - - For Orange Pi 5 devices: follow our {ref}`Orange Pi flashing instructions`. + - Raspberry Pi 3/4/5/CM4: follow our \{ref}`Raspberry Pi flashing instructions`. + - For LimeLight devices: follow our \{ref}`LimeLight flashing instructions`. + - For Orange Pi 5 devices: follow our \{ref}`Orange Pi flashing instructions`. - JAR files for the suite of supported operating systems for use with Offline Update. In general: - - Raspberry Pi, Limelight, and Orange Pi: use images suffixed with -linuxarm64.jar. For example: {code}`photonvision-v2024.1.1-linuxarm64.jar` - - Beelink and other Intel/AMD-based Mini-PCs: use images suffixed with -linuxx64.jar. For example: {code}`photonvision-v2024.1.1-linuxx64.jar` + - Raspberry Pi, Limelight, and Orange Pi: use images suffixed with -linuxarm64.jar. For example: `photonvision-v2024.1.1-linuxarm64.jar` + - Beelink and other Intel/AMD-based Mini-PCs: use images suffixed with -linuxx64.jar. For example: `photonvision-v2024.1.1-linuxx64.jar` ## Offline Update @@ -25,30 +23,24 @@ Unless noted in the release page, an offline update allows you to quickly upgrad Unless otherwise noted on the release page, config files should be backward compatible with previous version of PhotonVision, and this offline update process should preserve any pipelines and calibrations previously performed. For paranoia, we suggest exporting settings from the Settings tab prior to performing an offline update. -:::{note} +:::note Carefully review release notes to ensure that reflashing the device (for supported devices) or other installation steps are not required, as dependencies needed for PhotonVision may change between releases ::: ## 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 `. +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 `. -:::{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`. +:::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 [installing specific version of PhotonLib](/programming/photonlib/adding-vendordep.md#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". -```{image} images/gh_actions_1.png -:alt: Github Actions Badge -``` +Github Actions Badge -```{image} images/gh_actions_2.png -:alt: Github Actions artifact list -``` +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. -```{image} images/gh_actions_3.png -:alt: Github Actions artifacts from PR -``` +Github Actions artifacts from PR diff --git a/docs/source/docs/installation/wiring.md b/docs/docs/installation/wiring.md similarity index 92% rename from docs/source/docs/installation/wiring.md rename to docs/docs/installation/wiring.md index c20fc9916d..1789d9df79 100644 --- a/docs/source/docs/installation/wiring.md +++ b/docs/docs/installation/wiring.md @@ -4,13 +4,13 @@ Plugging your coprocessor into the wall via a power brick will suffice for off robot wiring. -:::{note} +:::note Please make sure your chosen power supply can provide enough power for your coprocessor. Undervolting (where enough power isn't being supplied) can cause many issues. ::: ## On-Robot Wiring -:::{note} +:::note We recommend users use the [SnakeEyes Pi Hat](https://www.playingwithfusion.com/productview.php?pdid=133) as it provides passive power over ethernet (POE) and other useful features to simplify wiring and make your life easier. ::: @@ -18,7 +18,7 @@ We recommend users use the [SnakeEyes Pi Hat](https://www.playingwithfusion.com/ 1. Plug the [passive POE injector](https://www.revrobotics.com/rev-11-1210/) into the coprocessor and wire it to PDP/PDH (NOT the VRM). 2. Add a breaker to relevant slot in your PDP/PDH -3. Run an ethernet cable from the passive POE injector to your network switch / radio (we *STRONGLY* recommend the usage of a network switch, see the [networking](networking.md) section for more info.) +3. Run an ethernet cable from the passive POE injector to your network switch / radio (we _STRONGLY_ recommend the usage of a network switch, see the [networking](networking.md) section for more info.) ### Coprocessor without Passive POE @@ -26,7 +26,7 @@ We recommend users use the [SnakeEyes Pi Hat](https://www.playingwithfusion.com/ 1b. Option 2: Use a USB power bank to power your coprocessor. Refer to this year's robot rulebook on legal implementations of this. -2. Run an ethernet cable from your Pi to your network switch / radio (we *STRONGLY* recommend the usage of a network switch, see the [networking](networking.md) section for more info.) +2. Run an ethernet cable from your Pi to your network switch / radio (we _STRONGLY_ recommend the usage of a network switch, see the [networking](networking.md) section for more info.) This diagram shows how to use the recommended regulator to power a coprocessor. @@ -35,7 +35,7 @@ This diagram shows how to use the recommended regulator to power a coprocessor. : the recommended voltage regulator and then a Coprocessor. ``` -:::{note} +:::note The regulator comes with optional screw terminals that may be used to connect the PDP/PDH and Coprocessor power wires if you do not wish to solder them. ::: diff --git a/docs/source/docs/integration/advancedStrategies.md b/docs/docs/integration/advancedStrategies.md similarity index 67% rename from docs/source/docs/integration/advancedStrategies.md rename to docs/docs/integration/advancedStrategies.md index 4d02547b17..68bf9e6589 100644 --- a/docs/source/docs/integration/advancedStrategies.md +++ b/docs/docs/integration/advancedStrategies.md @@ -1,8 +1,8 @@ # Advanced Strategies -Advanced strategies for using vision processing results involve working with the robot's *pose* on the field. A *pose* is a combination an X/Y coordinate, and an angle describing where the robot's front is pointed. It is always considered *relative* to some fixed point on the field. +Advanced strategies for using vision processing results involve working with the robot's _pose_ on the field. A _pose_ is a combination an X/Y coordinate, and an angle describing where the robot's front is pointed. It is always considered _relative_ to some fixed point on the field. -WPILib provides a [Pose2d](https://docs.wpilib.org/en/stable/docs/software/advanced-controls/geometry/pose.html) class to describe poses in software. +WPILib provides a [Pose2d](https://docs.wpilib.org/en/stable/docs/software/advanced-controls/geometry/pose.html) class to describe poses in software. ## Knowledge and Equipment Needed @@ -16,17 +16,17 @@ WPILib provides a [Pose2d](https://docs.wpilib.org/en/stable/docs/software/advan ## Path Planning in a Target-Centered Reference Frame -When using 3D mode in PhotonVision, the [SolvePNP Algorithm](https://en.wikipedia.org/wiki/Perspective-n-Point) is used to deduce the *camera's* position in a 3D coordinate system centered on the target itself. +When using 3D mode in PhotonVision, the [SolvePNP Algorithm](https://en.wikipedia.org/wiki/Perspective-n-Point) is used to deduce the _camera's_ position in a 3D coordinate system centered on the target itself. A simple algorithm for using this measurement is: -1. Assume your robot needs to be at a fixed `Pose2D` *relative to the target*. +1. Assume your robot needs to be at a fixed `Pose2D` _relative to the target_. 2. When triggered: - #. Read the most recent vision measurement - this is your *actual* pose. + #. Read the most recent vision measurement - this is your _actual_ pose. #. Generate a simple trajectory to the goal position #. Execute the trajectory -:::{note} +:::note There is not currently an example demonstrating this technique. ::: @@ -34,8 +34,8 @@ There is not currently an example demonstrating this technique. A more complex way to utilize a camera-supplied `Pose2D` is to incorporate it into an estimation of the robot's `Pose2D` in a global field reference frame. -When using this strategy, the measurements made by the camera are *fused* with measurements from other sensors, a model of expected robot behavior, and a matrix of weights that describes how trustworthy each sensor is. The result is a *best-guess* at the current pose on the field. +When using this strategy, the measurements made by the camera are _fused_ with measurements from other sensors, a model of expected robot behavior, and a matrix of weights that describes how trustworthy each sensor is. The result is a _best-guess_ at the current pose on the field. In turn, this best-guess position is used to path plan to the known positions on the field, which may or may not have vision targets nearby. -See the {ref}`Pose Estimation ` example for more information. +See the \{ref}`Pose Estimation ` example for more information. diff --git a/docs/source/docs/integration/aprilTagStrategies.md b/docs/docs/integration/aprilTagStrategies.md similarity index 99% rename from docs/source/docs/integration/aprilTagStrategies.md rename to docs/docs/integration/aprilTagStrategies.md index 3e181a7654..a56c96f7fb 100644 --- a/docs/source/docs/integration/aprilTagStrategies.md +++ b/docs/docs/integration/aprilTagStrategies.md @@ -1,6 +1,6 @@ # AprilTag Strategies -:::{note} +:::note The same strategies covered in the simple and advanced strategy sections still apply to AprilTags, and we encourage you to read them first. This page will discuss the specific nuances to using AprilTags. ::: @@ -26,7 +26,7 @@ Equipment ### Global Pose Estimation / Pose Estimation Strategies -:::{note} +:::note See the previous page for more general information. Most of the information is the same except now the camera is supplying a `Pose3D`. ::: diff --git a/docs/source/docs/integration/background.md b/docs/docs/integration/background.md similarity index 100% rename from docs/source/docs/integration/background.md rename to docs/docs/integration/background.md diff --git a/docs/source/docs/integration/simpleStrategies.md b/docs/docs/integration/simpleStrategies.md similarity index 77% rename from docs/source/docs/integration/simpleStrategies.md rename to docs/docs/integration/simpleStrategies.md index 5edf49878f..1ac509b4e1 100644 --- a/docs/source/docs/integration/simpleStrategies.md +++ b/docs/docs/integration/simpleStrategies.md @@ -1,6 +1,6 @@ # Simple Strategies -Simple strategies for using vision processor outputs involve using the target's position in the 2D image to infer *range* and *angle* to the target. +Simple strategies for using vision processor outputs involve using the target's position in the 2D image to infer _range_ and _angle_ to the target. ## Knowledge and Equipment Needed @@ -14,9 +14,9 @@ The simplest way to use a vision processing result is to first determine how far 1. Read the current angle to the target from the vision Coprocessor. 2. If too far in one direction, command the drivetrain to rotate in the opposite direction to compensate. -See the {ref}`Aiming at a Target ` example for more information. +See the \{ref}`Aiming at a Target ` example for more information. -:::{note} +:::note Sometimes, these strategies have also involved incorporating a gyroscope. This can be necessary due to the high latency of vision processing algorithms. However, advancements in the tools available (including PhotonVision) has made that unnecessary for most applications. ::: @@ -27,10 +27,10 @@ By looking at the position of the target in the "vertical" direction in the imag 1. Read the current distance to the target from the vision coprocessor. 2. If too far in one direction, command the drivetrain to travel in the opposite direction to compensate. -See the {ref}`Getting in Range of the Target ` example for more information. +See the \{ref}`Getting in Range of the Target ` example for more information. ## Angle + Range Since the previous two alignment strategies work on independent axes of the robot, there's no reason you can't do them simultaneously. -See the {ref}`Aim and Range ` example for more information. +See the \{ref}`Aim and Range ` example for more information. diff --git a/docs/source/docs/objectDetection/about-object-detection.md b/docs/docs/objectDetection/about-object-detection.md similarity index 92% rename from docs/source/docs/objectDetection/about-object-detection.md rename to docs/docs/objectDetection/about-object-detection.md index c11a5d3899..bd22b43e6c 100644 --- a/docs/source/docs/objectDetection/about-object-detection.md +++ b/docs/docs/objectDetection/about-object-detection.md @@ -6,8 +6,7 @@ PhotonVision supports object detection using neural network accelerator hardware For the 2024 season, PhotonVision ships with a **pre-trained NOTE detector** (shown above), as well as a mechanism for swapping in custom models. Future development will focus on enabling lower friction management of multiple custom models. -```{image} images/notes-ui.png -``` + ## Tracking Objects @@ -15,7 +14,7 @@ Before you get started with object detection, ensure that you have followed the PhotonVision currently ships with a NOTE detector based on a [YOLOv5 model](https://docs.ultralytics.com/yolov5/). This model is trained to detect one or more object "classes" (such as cars, stoplights, or in our case, NOTES) in an input image. For each detected object, the model outputs a bounding box around where in the image the object is located, what class the object belongs to, and a unitless confidence between 0 and 1. -:::{note} +:::note This model output means that while its fairly easy to say that "this rectangle probably contains a NOTE", we don't have any information about the NOTE's orientation or location. Further math in user code would be required to make estimates about where an object is physically located relative to the camera. ::: @@ -23,14 +22,12 @@ This model output means that while its fairly easy to say that "this rectangle p Compared to other pipelines, object detection exposes very few tuning handles. The Confidence slider changes the minimum confidence that the model needs to have in a given detection to consider it valid, as a number between 0 and 1 (with 0 meaning completely uncertain and 1 meaning maximally certain). -```{raw} html -``` -The same area, aspect ratio, and target orientation/sort parameters from {ref}`reflective pipelines ` are also exposed in the object detection card. +The same area, aspect ratio, and target orientation/sort parameters from \{ref}`reflective pipelines ` are also exposed in the object detection card. ## Training Custom Models @@ -38,7 +35,7 @@ Coming soon! ## Uploading Custom Models -:::{warning} +:::warning 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. ::: diff --git a/docs/source/docs/objectDetection/images/notes-ui.png b/docs/docs/objectDetection/images/notes-ui.png similarity index 100% rename from docs/source/docs/objectDetection/images/notes-ui.png rename to docs/docs/objectDetection/images/notes-ui.png diff --git a/docs/source/docs/pipelines/about-pipelines.md b/docs/docs/pipelines/about-pipelines.md similarity index 96% rename from docs/source/docs/pipelines/about-pipelines.md rename to docs/docs/pipelines/about-pipelines.md index 744a6b807d..74d850ba4c 100644 --- a/docs/source/docs/pipelines/about-pipelines.md +++ b/docs/docs/pipelines/about-pipelines.md @@ -22,8 +22,8 @@ This pipeline type is based on detecting different shapes like circles, triangle This pipeline type is based on detecting AprilTag fiducial markers. More information about AprilTags can be found in the WPILib documentation. While being more performance intensive than the reflective and colored shape pipeline, it has the benefit of providing easy to use 3D pose information which allows localization. -:::{note} -In order to get 3D Pose data about AprilTags, you are required to {ref}`calibrate your camera`. +:::note +In order to get 3D Pose data about AprilTags, you are required to \{ref}`calibrate your camera`. ::: ## Note About Multiple Cameras and Pipelines diff --git a/docs/source/docs/pipelines/images/motionblur.gif b/docs/docs/pipelines/images/motionblur.gif similarity index 100% rename from docs/source/docs/pipelines/images/motionblur.gif rename to docs/docs/pipelines/images/motionblur.gif diff --git a/docs/source/docs/pipelines/images/pipelinetype.png b/docs/docs/pipelines/images/pipelinetype.png similarity index 100% rename from docs/source/docs/pipelines/images/pipelinetype.png rename to docs/docs/pipelines/images/pipelinetype.png diff --git a/docs/source/docs/pipelines/input.md b/docs/docs/pipelines/input.md similarity index 97% rename from docs/source/docs/pipelines/input.md rename to docs/docs/pipelines/input.md index ec93c1218e..95b77245bc 100644 --- a/docs/source/docs/pipelines/input.md +++ b/docs/docs/pipelines/input.md @@ -14,13 +14,13 @@ When using the AprilTag pipeline, you should try to use as high of a resolution Camera exposure and brightness control how bright the captured image will be, although they function differently. Camera exposure changes how long the camera shutter lets in light, which changes the overall brightness of the captured image. This is in contrast to brightness, which is a post-processing effect that boosts the overall brightness of the image at the cost of desaturating colors (making colors look less distinct). -:::{important} +:::important For all pipelines, exposure time should be set as low as possible while still allowing for the target to be reliably tracked. This allows for faster processing as decreasing exposure will increase your camera FPS. ::: For reflective pipelines, after adjusting exposure and brightness, the target should be lit green (or the color of the vision tracking LEDs used). The more distinct the color of the target, the more likely it will be tracked reliably. -:::{note} +:::note Unlike with retroreflective tape, AprilTag tracking is not very dependent on lighting consistency. If you have trouble detecting tags due to low light, you may want to try increasing exposure, but this will likely decrease your achievable framerate. ::: @@ -32,9 +32,7 @@ For AprilTag pipelines, your goal is to reduce the "motion blur" as much as poss 2. Using a global shutter (as opposed to rolling shutter) camera. This should eliminate most, if not all motion blur. 3. Only rely on tags when not moving. -```{image} images/motionblur.gif -:align: center -``` + ## Orientation diff --git a/docs/source/docs/pipelines/output.md b/docs/docs/pipelines/output.md similarity index 86% rename from docs/source/docs/pipelines/output.md rename to docs/docs/pipelines/output.md index 072cf1924e..7f280611cf 100644 --- a/docs/source/docs/pipelines/output.md +++ b/docs/docs/pipelines/output.md @@ -6,14 +6,12 @@ The output card contains sections for target manipulation and offset modes. In this section, the Target Offset Point changes where the "center" of the target is. This can be useful if the pitch/yaw of the middle of the top edge of the target is desired, rather than the center of mass of the target. The "top"/"bottom"/"left"/"right" of the target are defined by the Target Orientation selection. For example, a 400x200px target in landscape mode would have the "top" offset point located at the middle of the uppermost long edge of the target, while in portrait mode the "top" offset point would be located in the middle of the topmost short edge (in this case, either the left or right sides). -This section also includes a switch to enable processing and sending multiple targets, up to 5, simultaneously. This information is available through PhotonLib. Note that the {code}`GetPitch`/{code}`GetYaw` methods will report the pitch/yaw of the "best" (lowest indexed) target. +This section also includes a switch to enable processing and sending multiple targets, up to 5, simultaneously. This information is available through PhotonLib. Note that the `GetPitch`/`GetYaw` methods will report the pitch/yaw of the "best" (lowest indexed) target. -```{raw} html -``` ## Robot Offset diff --git a/docs/source/docs/programming/photonlib/adding-vendordep.md b/docs/docs/programming/photonlib/adding-vendordep.md similarity index 91% rename from docs/source/docs/programming/photonlib/adding-vendordep.md rename to docs/docs/programming/photonlib/adding-vendordep.md index 5a08d93207..0b10998acb 100644 --- a/docs/source/docs/programming/photonlib/adding-vendordep.md +++ b/docs/docs/programming/photonlib/adding-vendordep.md @@ -10,14 +10,13 @@ PhotonLibPy is a minimal, pure-python implementation of PhotonLib. Click on the WPI icon on the top right of your VS Code window or hit Ctrl+Shift+P (Cmd+Shift+P on macOS) to bring up the command palette. Type, "Manage Vendor Libraries" and select the "WPILib: Manage Vendor Libraries" option. Then, select the "Install new library (online)" option. -```{image} images/adding-offline-library.png -``` + Paste the following URL into the box that pops up: `https://maven.photonvision.org/repository/internal/org/photonvision/photonlib-json/1.0/photonlib-json-1.0.json` -:::{note} +:::note It is recommended to Build Robot Code at least once when connected to the Internet before heading to an area where Internet connectivity is limited (for example, a competition). This ensures that the relevant files are downloaded to your filesystem. ::: @@ -42,7 +41,6 @@ See [The WPILib/RobotPy docs](https://docs.wpilib.org/en/stable/docs/software/py ## Install Specific Version - Java/C++ -In cases where you want to test a specific version of PhotonLib, make sure you have finished the steps in Online Install - Java/C++ and then manually change the version string in the PhotonLib vendordep json file(at ``/path/to/your/project/vendordep/photonlib.json``) to your desired version. +In cases where you want to test a specific version of PhotonLib, make sure you have finished the steps in Online Install - Java/C++ and then manually change the version string in the PhotonLib vendordep json file(at `/path/to/your/project/vendordep/photonlib.json`) to your desired version. -```{image} images/photonlib-vendordep-json.png -``` + diff --git a/docs/source/docs/programming/photonlib/controlling-led.md b/docs/docs/programming/photonlib/controlling-led.md similarity index 51% rename from docs/source/docs/programming/photonlib/controlling-led.md rename to docs/docs/programming/photonlib/controlling-led.md index 34649ddfd5..df3ca9cd54 100644 --- a/docs/source/docs/programming/photonlib/controlling-led.md +++ b/docs/docs/programming/photonlib/controlling-led.md @@ -1,16 +1,21 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + # Controlling LEDs You can control the vision LEDs of supported hardware via PhotonLib using the `setLED()` method on a `PhotonCamera` instance. In Java and C++, an `VisionLEDMode` enum class is provided to choose values from. These values include, `kOff`, `kOn`, `kBlink`, and `kDefault`. `kDefault` uses the default LED value from the selected pipeline. -```{eval-rst} -.. tab-set-code:: - .. code-block:: java - - // Blink the LEDs. - camera.setLED(VisionLEDMode.kBlink); - - .. code-block:: c++ - - // Blink the LEDs. - camera.SetLED(photonlib::VisionLEDMode::kBlink); + + +```java +// Blink the LEDs. +camera.setLED(VisionLEDMode.kBlink); +``` + + +```cpp +// Blink the LEDs. +camera.SetLED(photonlib::VisionLEDMode::kBlink); ``` + + diff --git a/docs/source/docs/programming/photonlib/driver-mode-pipeline-index.md b/docs/docs/programming/photonlib/driver-mode-pipeline-index.md similarity index 88% rename from docs/source/docs/programming/photonlib/driver-mode-pipeline-index.md rename to docs/docs/programming/photonlib/driver-mode-pipeline-index.md index 2b9444dc29..c9d551a1ab 100644 --- a/docs/source/docs/programming/photonlib/driver-mode-pipeline-index.md +++ b/docs/docs/programming/photonlib/driver-mode-pipeline-index.md @@ -1,6 +1,6 @@ # Driver Mode and Pipeline Index/Latency -After {ref}`creating a PhotonCamera `, one can toggle Driver Mode and change the Pipeline Index of the vision program from robot code. +After \{ref}`creating a PhotonCamera `, one can toggle Driver Mode and change the Pipeline Index of the vision program from robot code. ## Toggle Driver Mode @@ -55,6 +55,6 @@ You can also get the pipeline latency from a pipeline result using the `getLaten units::second_t latency = result.GetLatency(); ``` -:::{note} +:::note The C++ version of PhotonLib returns the latency in a unit container. For more information on the Units library, see [here](https://docs.wpilib.org/en/stable/docs/software/basic-programming/cpp-units.html). ::: diff --git a/docs/source/docs/programming/photonlib/getting-target-data.md b/docs/docs/programming/photonlib/getting-target-data.md similarity index 92% rename from docs/source/docs/programming/photonlib/getting-target-data.md rename to docs/docs/programming/photonlib/getting-target-data.md index f22e837559..3f508de422 100644 --- a/docs/source/docs/programming/photonlib/getting-target-data.md +++ b/docs/docs/programming/photonlib/getting-target-data.md @@ -12,7 +12,7 @@ The `PhotonCamera` class has two constructors: one that takes a `NetworkTable` a .. tab-set-code:: - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/a3bcd3ac4f88acd4665371abc3073bdbe5effea8/photonlib-java-examples/src/main/java/org/photonlib/examples/aimattarget/Robot.java + .. rli:: https://github.com/PhotonVision/photonvision/blob/a3bcd3ac4f88acd4665371abc3073bdbe5effea8/photonlib-java-examples/src/main/java/org/photonlib/examples/aimattarget/Robot.java :language: java :lines: 51-52 @@ -27,7 +27,7 @@ The `PhotonCamera` class has two constructors: one that takes a `NetworkTable` a ``` -:::{warning} +:::warning Teams must have unique names for all of their cameras regardless of which coprocessor they are attached to. ::: @@ -43,7 +43,7 @@ Use the `getLatestResult()`/`GetLatestResult()` (Java and C++ respectively) to o .. tab-set-code:: - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/a3bcd3ac4f88acd4665371abc3073bdbe5effea8/photonlib-java-examples/src/main/java/org/photonlib/examples/aimattarget/Robot.java + .. rli:: https://github.com/PhotonVision/photonvision/blob/a3bcd3ac4f88acd4665371abc3073bdbe5effea8/photonlib-java-examples/src/main/java/org/photonlib/examples/aimattarget/Robot.java :language: java :lines: 79-80 @@ -59,7 +59,7 @@ Use the `getLatestResult()`/`GetLatestResult()` (Java and C++ respectively) to o ``` -:::{note} +:::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). ::: @@ -85,8 +85,8 @@ Each pipeline result has a `hasTargets()`/`HasTargets()` (Java and C++ respectiv hasTargets = result.hasTargets() ``` -:::{warning} -In Java/C++, You must *always* check if the result has a target via `hasTargets()`/`HasTargets()` before getting targets or else you may get a null pointer exception. Further, you must use the same result in every subsequent call in that loop. +:::warning +In Java/C++, You must _always_ check if the result has a target via `hasTargets()`/`HasTargets()` before getting targets or else you may get a null pointer exception. Further, you must use the same result in every subsequent call in that loop. ::: ## Getting a List of Targets @@ -117,7 +117,7 @@ You can get a list of tracked targets using the `getTargets()`/`GetTargets()` (J ## Getting the Best Target -You can get the {ref}`best target ` using `getBestTarget()`/`GetBestTarget()` (Java and C++ respectively) method from the pipeline result. +You can get the \{ref}`best target ` using `getBestTarget()`/`GetBestTarget()` (Java and C++ respectively) method from the pipeline result. ```{eval-rst} .. tab-set-code:: @@ -182,7 +182,7 @@ You can get the {ref}`best target `. +::: + +PhotonLib includes a `PhotonPoseEstimator` class, which allows you to combine the pose data from all tags in view in order to get a field relative pose. The `PhotonPoseEstimator` class works with one camera per object instance, but more than one instance may be created. + +## Creating an `AprilTagFieldLayout` + +`AprilTagFieldLayout` is used to represent a layout of AprilTags within a space (field, shop at home, classroom, etc.). WPILib provides a JSON that describes the layout of AprilTags on the field which you can then use in the AprilTagFieldLayout constructor. You can also specify a custom layout. + +The API documentation can be found in here: [Java](https://github.wpilib.org/allwpilib/docs/release/java/edu/wpi/first/apriltag/AprilTagFieldLayout.html) and [C++](https://github.wpilib.org/allwpilib/docs/release/cpp/classfrc_1_1_april_tag_field_layout.html). + + + +```java +// The field from AprilTagFields will be different depending on the game. +AprilTagFieldLayout aprilTagFieldLayout = AprilTagFields.k2024Crescendo.loadAprilTagLayoutField(); +``` + + +```cpp +// The parameter for LoadAPrilTagLayoutField will be different depending on the game. +frc::AprilTagFieldLayout aprilTagFieldLayout = frc::LoadAprilTagLayoutField(frc::AprilTagField::k2024Crescendo); +``` + + + + +## Creating a `PhotonPoseEstimator` + +The PhotonPoseEstimator has a constructor that takes an `AprilTagFieldLayout` (see above), `PoseStrategy`, `PhotonCamera`, and `Transform3d`. `PoseStrategy` has six possible values: + +- MULTI_TAG_PNP_ON_COPROCESSOR + - Calculates a new robot position estimate by combining all visible tag corners. Recommended for all teams as it will be the most accurate. + - Must configure the AprilTagFieldLayout properly in the UI, please see \{ref}`here ` for more information. +- LOWEST_AMBIGUITY + - Choose the Pose with the lowest ambiguity. +- CLOSEST_TO_CAMERA_HEIGHT + - Choose the Pose which is closest to the camera height. +- CLOSEST_TO_REFERENCE_POSE + - Choose the Pose which is closest to the pose from setReferencePose(). +- CLOSEST_TO_LAST_POSE + - Choose the Pose which is closest to the last pose calculated. +- AVERAGE_BEST_TARGETS + - Choose the Pose which is the average of all the poses from each tag. + + + +```java + //Forward Camera + cam = new PhotonCamera("testCamera"); + Transform3d robotToCam = new Transform3d(new Translation3d(0.5, 0.0, 0.5), new Rotation3d(0,0,0)); //Cam mounted facing forward, half a meter forward of center, half a meter up from center. + + // Construct PhotonPoseEstimator + PhotonPoseEstimator photonPoseEstimator = new PhotonPoseEstimator(aprilTagFieldLayout, PoseStrategy.CLOSEST_TO_REFERENCE_POSE, cam, robotToCam); +``` + + +```cpp +// Forward Camera +std::shared_ptr cameraOne = + std::make_shared("testCamera"); +// Camera is mounted facing forward, half a meter forward of center, half a +// meter up from center. +frc::Transform3d robotToCam = + frc::Transform3d(frc::Translation3d(0.5_m, 0_m, 0.5_m), + frc::Rotation3d(0_rad, 0_rad, 0_rad)); + +// ... Add other cameras here + +// Assemble the list of cameras & mount locations +std::vector< + std::pair, frc::Transform3d>> + cameras; +cameras.push_back(std::make_pair(cameraOne, robotToCam)); + +photonlib::RobotPoseEstimator estimator( + aprilTags, photonlib::CLOSEST_TO_REFERENCE_POSE, cameras); +``` + + + +## Using a `PhotonPoseEstimator` + +Calling `update()` on your `PhotonPoseEstimator` will return an `EstimatedRobotPose`, which includes a `Pose3d` of the latest estimated pose (using the selected strategy) along with a `double` of the timestamp when the robot pose was estimated. You should be updating your [drivetrain pose estimator](https://docs.wpilib.org/en/latest/docs/software/advanced-controls/state-space/state-space-pose-estimators.html) with the result from the `PhotonPoseEstimator` every loop using `addVisionMeasurement()`. + + + +```java reference +https://github.com/PhotonVision/photonvision/blob/357d8a518a93f7a1f8084a79449249e613b605a7/photonlib-java-examples/apriltagExample/src/main/java/frc/robot/PhotonCameraWrapper.java#L85-L88 +``` + + +```cpp +std::pair getEstimatedGlobalPose( + frc::Pose3d prevEstimatedRobotPose) { + robotPoseEstimator.SetReferencePose(prevEstimatedRobotPose); + units::millisecond_t currentTime = frc::Timer::GetFPGATimestamp(); + auto result = robotPoseEstimator.Update(); + if (result.second) { + return std::make_pair<>(result.first.ToPose2d(), + currentTime - result.second); + } else { + return std::make_pair(frc::Pose2d(), 0_ms); + } +} +``` + + + +You should be updating your [drivetrain pose estimator](https://docs.wpilib.org/en/latest/docs/software/advanced-controls/state-space/state-space-pose-estimators.html) with the result from the `RobotPoseEstimator` every loop using `addVisionMeasurement()`. TODO: add example note + +## Additional `PhotonPoseEstimator` Methods + +### `setReferencePose(Pose3d referencePose)` + +Updates the stored reference pose when using the CLOSEST_TO_REFERENCE_POSE strategy. + +### `setLastPose(Pose3d lastPose)` + +Update the stored last pose. Useful for setting the initial estimate when using the CLOSEST_TO_LAST_POSE strategy. diff --git a/docs/source/docs/programming/photonlib/using-target-data.md b/docs/docs/programming/photonlib/using-target-data.md similarity index 99% rename from docs/source/docs/programming/photonlib/using-target-data.md rename to docs/docs/programming/photonlib/using-target-data.md index c5f67ce8a0..107ae0bed8 100644 --- a/docs/source/docs/programming/photonlib/using-target-data.md +++ b/docs/docs/programming/photonlib/using-target-data.md @@ -54,7 +54,7 @@ If your camera is at a fixed height on your robot and the height of the target i :lines: 33-46 ``` -:::{note} +:::note The C++ version of PhotonLib uses the Units library. For more information, see [here](https://docs.wpilib.org/en/stable/docs/software/basic-programming/cpp-units.html). ::: @@ -92,7 +92,7 @@ You can get a [translation](https://docs.wpilib.org/en/latest/docs/software/adva distance, frc::Rotation2d(units::degree_t(-target.GetYaw()))); ``` -:::{note} +:::note We are negating the yaw from the camera from CV (computer vision) conventions to standard mathematical conventions. In standard mathematical conventions, as you turn counter-clockwise, angles become more positive. ::: diff --git a/docs/source/docs/reflectiveAndShape/3D.md b/docs/docs/reflectiveAndShape/3D.md similarity index 76% rename from docs/source/docs/reflectiveAndShape/3D.md rename to docs/docs/reflectiveAndShape/3D.md index 043c82ff8e..db0c931c93 100644 --- a/docs/source/docs/reflectiveAndShape/3D.md +++ b/docs/docs/reflectiveAndShape/3D.md @@ -1,21 +1,20 @@ # 3D Tuning -In 3D mode, the SolvePNP algorithm is used to compute the position and rotation of the target relative to the robot. This requires your {ref}`camera to be calibrated ` which can be done through the cameras tab. +In 3D mode, the SolvePNP algorithm is used to compute the position and rotation of the target relative to the robot. This requires your \{ref}`camera to be calibrated ` which can be done through the cameras tab. The target model dropdown is used to select the target model used to compute target position. This should match the target your camera will be tracking. If solvePNP is working correctly, the target should be displayed as a small rectangle within the "Target Location" minimap. The X/Y/Angle reading will also be displayed in the "Target Info" card. -```{raw} html -``` + ## Contour Simplification diff --git a/docs/source/docs/reflectiveAndShape/contour-filtering.md b/docs/docs/reflectiveAndShape/contour-filtering.md similarity index 73% rename from docs/source/docs/reflectiveAndShape/contour-filtering.md rename to docs/docs/reflectiveAndShape/contour-filtering.md index 75783ac1cd..2489004895 100644 --- a/docs/source/docs/reflectiveAndShape/contour-filtering.md +++ b/docs/docs/reflectiveAndShape/contour-filtering.md @@ -16,39 +16,31 @@ Fullness is a measurement of the ratio between the contour's area and the area o Finally, speckle rejection is an algorithm that can discard contours whose area are below a certain percentage of the average area of all visible contours. This might be useful in rejecting stray lights or image noise. -```{raw} html -``` ### Colored Shape -The contours tab has new options for specifying the properties of your colored shape. The target shape types are: +The contours tab has new options for specifying the properties of your colored shape. The target shape types are: - Circle - No edges - Triangle - 3 edges - Quadrilateral - 4 edges - Polygon - Any number of edges -```{image} images/triangle.png -:alt: Dropdown to select the colored shape pipeline type. -:width: 600 -``` +Dropdown to select the colored shape pipeline type. Only the settings used for the current target shape are available. -- Shape Simplification - This is the only setting available for polygon, triangle, and quadrilateral target shapes. If you are having issues with edges being "noisy" or "unclean", adjust this setting to be higher (>75). This high setting helps prevent imperfections in the edge from being counted as a separate edge. -- Circle Match Distance - How close the centroid of a contour must be to the center of the circle in order for them to be matched. This value is usually pretty small (\<25) as you usually only want to identify circles that are nearly centered in the contour. +- Shape Simplification - This is the only setting available for polygon, triangle, and quadrilateral target shapes. If you are having issues with edges being "noisy" or "unclean", adjust this setting to be higher (>75). This high setting helps prevent imperfections in the edge from being counted as a separate edge. +- Circle Match Distance - How close the centroid of a contour must be to the center of the circle in order for them to be matched. This value is usually pretty small (\<25) as you usually only want to identify circles that are nearly centered in the contour. - Radius - Percentage of the frame that the radius of the circle represents. - Max Canny Threshold - This sets the amount of change between pixels needed to be considered an edge. The smaller it is, the more false circles may be detected. Circles with more points along their ring having high contrast values will be returned first. -- Circle Accuracy - This determines how perfect the circle contour must be in order to be considered a circle. Low values (\<40) are required to detect things that aren't perfect circles. +- Circle Accuracy - This determines how perfect the circle contour must be in order to be considered a circle. Low values (\<40) are required to detect things that aren't perfect circles. -```{image} images/pumpkin.png -:alt: Dropdown to select the colored shape pipeline type. -:width: 600 -``` +Dropdown to select the colored shape pipeline type. ## Contour Grouping and Sorting @@ -64,9 +56,7 @@ Finally, target sort defines how targets are ranked, from "best" to "worst." The - Leftmost - Centermost -```{raw} html -``` diff --git a/docs/source/docs/reflectiveAndShape/images/hsl_top.png b/docs/docs/reflectiveAndShape/images/hsl_top.png similarity index 100% rename from docs/source/docs/reflectiveAndShape/images/hsl_top.png rename to docs/docs/reflectiveAndShape/images/hsl_top.png diff --git a/docs/source/docs/reflectiveAndShape/images/pumpkin.png b/docs/docs/reflectiveAndShape/images/pumpkin.png similarity index 100% rename from docs/source/docs/reflectiveAndShape/images/pumpkin.png rename to docs/docs/reflectiveAndShape/images/pumpkin.png diff --git a/docs/source/docs/reflectiveAndShape/images/triangle.png b/docs/docs/reflectiveAndShape/images/triangle.png similarity index 100% rename from docs/source/docs/reflectiveAndShape/images/triangle.png rename to docs/docs/reflectiveAndShape/images/triangle.png diff --git a/docs/source/docs/reflectiveAndShape/thresholding.md b/docs/docs/reflectiveAndShape/thresholding.md similarity index 89% rename from docs/source/docs/reflectiveAndShape/thresholding.md rename to docs/docs/reflectiveAndShape/thresholding.md index 93debb8b68..5ccc90b75d 100644 --- a/docs/source/docs/reflectiveAndShape/thresholding.md +++ b/docs/docs/reflectiveAndShape/thresholding.md @@ -4,23 +4,19 @@ For colored shape detection, we want to tune our HSV thresholds such that only t In PhotonVision, HSV thresholds is available in the "Threshold" tab. -```{raw} html -``` ## Color Picker The color picker can be used to quickly adjust HSV values. "Set to average" will set the HSV range to the color of the pixel selected, while "shrink range" and "expand range" will change the HSV threshold to include or exclude the selected pixel, respectively. -```{raw} html -``` ## Tuning Steps @@ -30,7 +26,4 @@ In order to properly capture the colors that you want, first turn your exposure For HSV tuning, start with Hue, as it is the most important/differentiating factor when it comes to detecting color. You want to make the range for Hue as small as possible in order to get accurate tracking. Feel free to reference the chart below to help. After you have properly tuned Hue, tune for high saturation/color intensity (S), and then brightness (V). Using this method will decrease the likelihood that you need to calibrate on the field. Saturation and Value's upper bounds will often end up needing to be the maximum (255). -```{image} images/hsl_top.png -:alt: HSV chart -:width: 600 -``` +HSV chart diff --git a/docs/source/docs/settings.md b/docs/docs/settings.md similarity index 96% rename from docs/source/docs/settings.md rename to docs/docs/settings.md index d35657c326..8e6451165a 100644 --- a/docs/source/docs/settings.md +++ b/docs/docs/settings.md @@ -1,7 +1,7 @@ # Settings -```{image} assets/settings.png -``` +![settings page](assets/settings.png) + ## General @@ -14,7 +14,7 @@ Here, you can set your team number, switch your IP between DHCP and static, and The "team number" field will accept (in addition to a team number) an IP address or hostname. This is useful for testing PhotonVision on the same computer as a simulated robot program; you can set the team number to "localhost", and PhotonVision will send data to the network tables in the simulated robot. -:::{note} +:::note Something must be entered into the team number field if using PhotonVision on a robot. Using a team number is recommended (as opposed to an IP address or hostname). ::: diff --git a/docs/source/docs/simulation/diagrams/SimArchitecture-deprecated.drawio.svg b/docs/docs/simulation/diagrams/SimArchitecture-deprecated.drawio.svg similarity index 100% rename from docs/source/docs/simulation/diagrams/SimArchitecture-deprecated.drawio.svg rename to docs/docs/simulation/diagrams/SimArchitecture-deprecated.drawio.svg diff --git a/docs/source/docs/simulation/diagrams/SimArchitecture.drawio.svg b/docs/docs/simulation/diagrams/SimArchitecture.drawio.svg similarity index 100% rename from docs/source/docs/simulation/diagrams/SimArchitecture.drawio.svg rename to docs/docs/simulation/diagrams/SimArchitecture.drawio.svg diff --git a/docs/source/docs/simulation/hardware-in-the-loop-sim.md b/docs/docs/simulation/hardware-in-the-loop-sim.md similarity index 88% rename from docs/source/docs/simulation/hardware-in-the-loop-sim.md rename to docs/docs/simulation/hardware-in-the-loop-sim.md index b23276b1df..e7ef1caf38 100644 --- a/docs/source/docs/simulation/hardware-in-the-loop-sim.md +++ b/docs/docs/simulation/hardware-in-the-loop-sim.md @@ -2,7 +2,7 @@ Hardware in the loop simulation is using a physical device, such as a supported co-processor running PhotonVision, to enhance simulation capabilities. This is useful for developing and validating code before the camera is attached to a robot, as well as reducing the work required to use WPILib simulation with PhotonVision. -Before continuing, ensure PhotonVision is installed on your target device. Instructions can be found {ref}`here ` for all devices. +Before continuing, ensure PhotonVision is installed on your target device. Instructions can be found \{ref}`here ` for all devices. Your coprocessor and computer running simulation will have to be connected to the same network, like a home router. Connecting the coprocessor directly to the computer will not work. @@ -10,7 +10,7 @@ To simulate with hardware in the loop, a one-line change is required. From the P During normal robot operation, a team's number would be entered into this field so that the PhotonVision coprocessor connects to the roboRIO as a NT client. Instead, enter the IP address of your computer running the simulation here. -:::{note} +:::note To find the IP address of your Windows computer, open command prompt and run `ipconfig`. ```console @@ -26,14 +26,13 @@ Ethernet adapter Ethernet: Subnet Mask . . . . . . . . . . . : 255.255.255.0 Default Gateway . . . . . . . . . : 192.168.254.254 ``` + ::: -```{image} images/coproc-client-to-desktop-sim.png -``` + No code changes are required, PhotonLib should function similarly to normal operation. Now launch simulation, and you should be able to see the PhotonVision table on your simulation's NetworkTables dashboard. -```{image} images/hardware-in-the-loop-sim.png -``` + diff --git a/docs/source/docs/simulation/images/SimArchitecture.svg b/docs/docs/simulation/images/SimArchitecture.svg similarity index 100% rename from docs/source/docs/simulation/images/SimArchitecture.svg rename to docs/docs/simulation/images/SimArchitecture.svg diff --git a/docs/source/docs/simulation/images/SimExampleField.png b/docs/docs/simulation/images/SimExampleField.png similarity index 100% rename from docs/source/docs/simulation/images/SimExampleField.png rename to docs/docs/simulation/images/SimExampleField.png diff --git a/docs/source/docs/simulation/images/SimExampleFrame.png b/docs/docs/simulation/images/SimExampleFrame.png similarity index 100% rename from docs/source/docs/simulation/images/SimExampleFrame.png rename to docs/docs/simulation/images/SimExampleFrame.png diff --git a/docs/source/docs/simulation/images/coproc-client-to-desktop-sim.png b/docs/docs/simulation/images/coproc-client-to-desktop-sim.png similarity index 100% rename from docs/source/docs/simulation/images/coproc-client-to-desktop-sim.png rename to docs/docs/simulation/images/coproc-client-to-desktop-sim.png diff --git a/docs/source/docs/simulation/images/hardware-in-the-loop-sim.png b/docs/docs/simulation/images/hardware-in-the-loop-sim.png similarity index 100% rename from docs/source/docs/simulation/images/hardware-in-the-loop-sim.png rename to docs/docs/simulation/images/hardware-in-the-loop-sim.png diff --git a/docs/source/docs/simulation/simulation-deprecated.md b/docs/docs/simulation/simulation-deprecated.md similarity index 61% rename from docs/source/docs/simulation/simulation-deprecated.md rename to docs/docs/simulation/simulation-deprecated.md index ba7be7e458..54d89000d6 100644 --- a/docs/source/docs/simulation/simulation-deprecated.md +++ b/docs/docs/simulation/simulation-deprecated.md @@ -1,7 +1,10 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + # Simulation Support in PhotonLib (Deprecated) -:::{attention} -This page details the pre-2024 simulation support. For current Java simulation support, see {doc}`/docs/simulation/simulation`. +:::attention +This page details the pre-2024 simulation support. For current Java simulation support, see \{doc}`/docs/simulation/simulation`. ::: ## What Is Supported? @@ -23,16 +26,13 @@ Targets are considered in view if: 3. The target's in-image pixel size is greater than `minTargetArea` 4. The distance from the camera to the target is less than `maxLEDRange` -:::{warning} +:::warning Not all network tables objects are updated in simulation. The interaction through PhotonLib remains the same. Actual camera images are also not simulated. ::: Latency of processing is not yet modeled. -```{image} diagrams/SimArchitecture-deprecated.drawio.svg -:alt: A diagram comparing the architecture of a real PhotonVision process to a simulated -: one. -``` +![A diagram comparing the architecture of a real PhotonVision process to a simulated one.](diagrams/SimArchitecture-deprecated.drawio.svg) ## Simulated Vision System @@ -40,33 +40,35 @@ A `SimVisionSystem` represents the camera and coprocessor running PhotonVision m It requires a number of pieces of configuration to accurately simulate your physical setup. Match them to your configuration in PhotonVision, and to your robot's physical dimensions. -```{eval-rst} -.. tab-set-code:: - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java - :language: java - :lines: 73-93 + + +```java reference +https://github.com/PhotonVision/photonvision/blob/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java#L73-L93 ``` + + -After declaring the system, you should create and add one `SimVisionTarget` per target you are attempting to detect. -```{eval-rst} -.. tab-set-code:: +After declaring the system, you should create and add one `SimVisionTarget` per target you are attempting to detect. - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java - :language: java - :lines: 95-111 + + +```java reference +https://github.com/PhotonVision/photonvision/blob/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java#L95-L111 ``` + + -Finally, while running the simulation, process simulated camera frames by providing the robot's pose to the system. -```{eval-rst} -.. tab-set-code:: +Finally, while running the simulation, process simulated camera frames by providing the robot's pose to the system. - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java - :language: java - :lines: 138-139 + + +```java reference +https://github.com/PhotonVision/photonvision/blob/80e16ece87c735e30755dea271a56a2ce217b588/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java#L138-L139 ``` + + This will cause most NetworkTables fields to update properly, representing any targets that are in view of the robot. @@ -78,26 +80,26 @@ Users may wish to directly provide target information based on an existing detai A `SimPhotonCamera` can be created for this purpose. It provides an interface where the user can supply target data via a list of `PhotonTrackedTarget` objects. -```{eval-rst} -.. tab-set-code:: - - .. code-block:: java - - @Override - public void simulationInit() { - // ... - cam = new SimPhotonCamera("MyCamera"); - // ... - } - - @Override - public void simulationPeriodic() { - // ... - ArrayList visibleTgtList = new ArrayList(); - visibleTgtList.add(new PhotonTrackedTarget(yawDegrees, pitchDegrees, area, skew, camToTargetTrans)); // Repeat for each target that you see - cam.submitProcessedFrame(0.0, visibleTgtList); - // ... - } + + +```java +@Override +public void simulationInit() { + // ... + cam = new SimPhotonCamera("MyCamera"); + // ... +} + +@Override +public void simulationPeriodic() { + // ... + ArrayList visibleTgtList = new ArrayList(); + visibleTgtList.add(new PhotonTrackedTarget(yawDegrees, pitchDegrees, area, skew, camToTargetTrans)); // Repeat for each target that you see + cam.submitProcessedFrame(0.0, visibleTgtList); + // ... +} ``` + + Note that while there is less code and configuration required to get basic data into the simulation, this approach will cause the user to need to implement much more code on their end to calculate the relative positions of the robot and target. If you already have this, the raw interface may be helpful. However, if you don't, you'll likely want to be looking at the Simulated Vision System first. diff --git a/docs/source/docs/simulation/simulation.md b/docs/docs/simulation/simulation.md similarity index 87% rename from docs/source/docs/simulation/simulation.md rename to docs/docs/simulation/simulation.md index 2c23708d1d..9ab6b7d2a3 100644 --- a/docs/source/docs/simulation/simulation.md +++ b/docs/docs/simulation/simulation.md @@ -1,7 +1,7 @@ # Simulation Support in PhotonLib -:::{attention} -This page details the current simulation support for Java. For other languages, see {doc}`/docs/simulation/simulation-deprecated`. +:::attention +This page details the current simulation support for Java. For other languages, see \{doc}`/docs/simulation/simulation-deprecated`. ::: ## What Is Simulated? @@ -11,35 +11,32 @@ Simulation is a powerful tool for validating robot code without access to a phys PhotonLib can simulate cameras on the field and generate target data approximating what would be seen in reality. This simulation attempts to include the following: - Camera Properties - - Field of Vision - - Lens distortion - - Image noise - - Framerate - - Latency + - Field of Vision + - Lens distortion + - Image noise + - Framerate + - Latency - Target Data - - Detected / minimum-area-rectangle corners - - Center yaw/pitch - - Contour image area percentage - - Fiducial ID - - Fiducial ambiguity - - Fiducial solvePNP transform estimation + - Detected / minimum-area-rectangle corners + - Center yaw/pitch + - Contour image area percentage + - Fiducial ID + - Fiducial ambiguity + - Fiducial solvePNP transform estimation - Camera Raw/Processed Streams (grayscale) -:::{note} +:::note Simulation does NOT include the following: - Full physical camera/world simulation (targets are automatically thresholded) - Image Thresholding Process (camera gain, brightness, etc) - Pipeline switching - Snapshots -::: + ::: This scope was chosen to balance fidelity of the simulation with the ease of setup, in a way that would best benefit most teams. -```{image} diagrams/SimArchitecture.drawio.svg -:alt: A diagram comparing the architecture of a real PhotonVision process to a simulated -: one. -``` +![A diagram comparing the architecture of a real PhotonVision process to a simulated one.](diagrams/SimArchitecture.drawio.svg) ## Drivetrain Simulation Prerequisite @@ -47,7 +44,7 @@ A prerequisite for simulating vision frames is knowing where the camera is on th References for using PhotonVision simulation with drivetrain simulation can be found in the [PhotonLib Java Examples](https://github.com/PhotonVision/photonvision/blob/2a6fa1b6ac81f239c59d724da5339f608897c510/photonlib-java-examples/README.md) for both a differential drivetrain and a swerve drive. -:::{important} +:::important The simulated drivetrain pose must be separate from the drivetrain estimated pose if a pose estimator is utilized. ::: @@ -68,15 +65,17 @@ PhotonLib will use this label to put a `Field2d` widget on NetworkTables at `/Vi Vision targets require a `TargetModel`, which describes the shape of the target. For AprilTags, PhotonLib provides `TargetModel.kAprilTag16h5` for the tags used in 2023, and `TargetModel.kAprilTag36h11` for the tags used starting in 2024. For other target shapes, convenience constructors exist for spheres, cuboids, and planar rectangles. For example, a planar rectangle can be created with: -```{eval-rst} -.. tab-set-code:: + + - .. code-block:: java - - // A 0.5 x 0.25 meter rectangular target - TargetModel targetModel = new TargetModel(0.5, 0.25); +```java +// A 0.5 x 0.25 meter rectangular target +TargetModel targetModel = new TargetModel(0.5, 0.25); ``` + + + These `TargetModel` are paired with a target pose to create a `VisionTargetSim`. A `VisionTargetSim` is added to the `VisionSystemSim` to become visible to all of its cameras. ```{eval-rst} @@ -95,7 +94,7 @@ These `TargetModel` are paired with a target pose to create a `VisionTargetSim`. visionSim.addVisionTargets(visionTarget); ``` -:::{note} +:::note The pose of a `VisionTargetSim` object can be updated to simulate moving targets. Note, however, that this will break latency simulation for that target. ::: @@ -112,7 +111,7 @@ For convenience, an `AprilTagFieldLayout` can also be added to automatically cre visionSim.addAprilTags(tagLayout); ``` -:::{note} +:::note The poses of the AprilTags from this layout depend on its current alliance origin (e.g. blue or red). If this origin is changed later, the targets will have to be cleared from the `VisionSystemSim` and re-added. ::: @@ -181,7 +180,7 @@ The `PhotonCameraSim` can now be added to the `VisionSystemSim`. We have to defi visionSim.addCamera(cameraSim, robotToCamera); ``` -:::{important} +:::important You may add multiple cameras to one `VisionSystemSim`, but not one camera to multiple `VisionSystemSim`. All targets in the `VisionSystemSim` will be visible to all its cameras. ::: @@ -229,7 +228,7 @@ Each `VisionSystemSim` has its own built-in `Field2d` for displaying object pose ``` :::{figure} images/SimExampleField.png -*A* `VisionSystemSim`*'s internal* `Field2d` *customized with target images and colors, as seen in the* [swervedriveposeestsim](https://github.com/PhotonVision/photonvision/tree/2a6fa1b6ac81f239c59d724da5339f608897c510/photonlib-java-examples/swervedriveposeestsim) *example.* +_A_ `VisionSystemSim`_'s internal_ `Field2d` _customized with target images and colors, as seen in the_ [swervedriveposeestsim](https://github.com/PhotonVision/photonvision/tree/2a6fa1b6ac81f239c59d724da5339f608897c510/photonlib-java-examples/swervedriveposeestsim) _example._ ::: A `PhotonCameraSim` can also draw and publish generated camera frames to a MJPEG stream similar to an actual PhotonVision process. @@ -248,8 +247,8 @@ A `PhotonCameraSim` can also draw and publish generated camera frames to a MJPEG cameraSim.enableDrawWireframe(true); ``` -These streams follow the port order mentioned in {ref}`docs/installation/networking:Camera Stream Ports`. For example, a single simulated camera will have its raw stream at `localhost:1181` and processed stream at `localhost:1182`, which can also be found in the CameraServer tab of Shuffleboard like a normal camera stream. +These streams follow the port order mentioned in \{ref}`docs/installation/networking:Camera Stream Ports`. For example, a single simulated camera will have its raw stream at `localhost:1181` and processed stream at `localhost:1182`, which can also be found in the CameraServer tab of Shuffleboard like a normal camera stream. :::{figure} images/SimExampleFrame.png -*A frame from the processed stream of a simulated camera viewing some 2023 AprilTags with the field wireframe enabled, as seen in the* [swervedriveposeestsim example](https://github.com/PhotonVision/photonvision/tree/2a6fa1b6ac81f239c59d724da5339f608897c510/photonlib-java-examples/swervedriveposeestsim). +_A frame from the processed stream of a simulated camera viewing some 2023 AprilTags with the field wireframe enabled, as seen in the_ [swervedriveposeestsim example](https://github.com/PhotonVision/photonvision/tree/2a6fa1b6ac81f239c59d724da5339f608897c510/photonlib-java-examples/swervedriveposeestsim). ::: diff --git a/docs/docs/troubleshooting/camera-troubleshooting.md b/docs/docs/troubleshooting/camera-troubleshooting.md new file mode 100644 index 0000000000..b65495af35 --- /dev/null +++ b/docs/docs/troubleshooting/camera-troubleshooting.md @@ -0,0 +1,110 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# Camera Troubleshooting + +## Pi Cameras + +If you haven't yet, please refer to \{ref}`the Pi CSI Camera Configuration page ` for information on updating `config.txt` for your use case. If you've tried that, and things still aren't working, restart PhotonVision using the restart button in the settings tab, and press tilde (\`) in the web UI once connection is restored. This should show the most recent boot log. + +| | Expected output | Bad | +| ------------------------------- | ----------------------------------------------------- | ---------------------------------- | +| LibCamera driver initialization | Successfully loaded libpicam shared object | Failed to load native libraries! | +| Camera detected | Adding local video device - "unicam" at "/dev/video0" | No output from VisionSourceManager | +| VisionSource created | Adding 1 configs to VMM. | No output from VisionSourceManager | + +If the driver isn't loaded, you may be using a non-official Pi image, or an image not new enough. Try updating to the most recent image available (one released for 2023) -- if that doesn't resolve the problem, \{ref}`contact us` with your settings ZIP file and Pi version/camera version/config.txt file used. + +If the camera is not detected, the most likely cause is either a config.txt file incorrectly set-up, or a ribbon cable attached backwards. Review the \{ref}`picam configuration page `, and verify the ribbon cable is properly oriented at both ends, and that it is \_fully\_ inserted into the FFC connector. Then, \{ref}`contact us` with your settings ZIP file and Pi version/camera version/config.txt file used. + +## USB cameras + +USB cameras supported by CSCore require no libcamera driver initialization to work -- however, similar troubleshooting steps apply. Restart PhotonVision using the restart button in the settings tab, and press tilde on your keyboard (\`) when you're in the web UI once connection is restored. We expect to see the following output: + +| | Expected output | Bad | +| -------------------- | ----------------------------------------------------- | ---------------------------------- | +| Camera detected | Adding local video device - "foobar" at "/dev/foobar" | No output from VisionSourceManager | +| VisionSource created | Adding 1 configs to VMM. | No output from VisionSourceManager | + +## Determining detected cameras in Video4Linux (v4l2) + +On Linux devices (including Raspberry Pi), PhotonVision uses WPILib's CSCore to interact with video devices, which internally uses Video4Linux (v4l2). CSCore, and therefore Photon, requires that cameras attached have good v4l drivers for proper functionality. These should be built into the Linux kernel, and do not need to be installed manually. Valid picamera setup (from /boot/config.txt) can also be determined using these steps. The list-devices command will show all valid video devices detected, and list-formats the list of "video modes" each camera can be in. + +- For picams: edit the config.txt file as described in the \{ref}`picam configuration page ` +- SSH into your Pi: `ssh pi@photonvision.local` and enter the username "pi" & password "raspberry" +- run `v4l2-ctl --list-devices` and `v4l2-ctl --list-formats` + +We expect an output similar to the following. For picameras, note the "unicam" entry with path `platform:3f801000.csi` (if we don't see this, that's bad), and a huge list of valid video formats. USB cameras should show up similarly in the output of these commands. + + + +```shell +pi@photonvision:~ $ v4l2-ctl --list-devices +unicam (platform:3f801000.csi): + /dev/video0 + /dev/media3 + +bcm2835-codec-decode (platform:bcm2835-codec): +/dev/video10 +/dev/video11 +/dev/video12 +/dev/video18 +/dev/video31 +/dev/media2 + +bcm2835-isp (platform:bcm2835-isp): +/dev/video13 +/dev/video14 +/dev/video15 +/dev/video16 +/dev/video20 +/dev/video21 +/dev/video22 +/dev/video23 +/dev/media0 +/dev/media1 + +pi@photonvision:~ $ v4l2-ctl --list-formats +ioctl: VIDIOC_ENUM_FMT +Type: Video Capture + +[0]: 'YUYV' "YUYV 4:2:2" +[1]: 'UYVY' "UYVY 4:2:2" +[2]: 'YVYU' "YVYU 4:2:2" +[3]: 'VYUY' "VYUY 4:2:2" + + +[42]: 'Y12P' (12-bit Greyscale (MIPI Packed)) +[43]: 'Y12 ' (12-bit Greyscale) +[44]: 'Y14P' (14-bit Greyscale (MIPI Packed)) +[45]: 'Y14 ' (14-bit Greyscale) +``` + + +```shell +pi@photonvision:~ $ v4l2-ctl --list-devices +bcm2835-codec-decode (platform:bcm2835-codec): + /dev/video10 + /dev/video11 + /dev/video12 + /dev/video18 + /dev/video31 + /dev/media3 + bcm2835-isp (platform:bcm2835-isp): + /dev/video13 + /dev/video14 + /dev/video15 + /dev/video16 + /dev/video20 + /dev/video21 + /dev/video22 + /dev/video23 + /dev/media0 + /dev/media1 +rpivid (platform:rpivid): + /dev/video19 + /dev/media2 +Cannot open device /dev/video0, exiting. +``` + + diff --git a/docs/source/docs/troubleshooting/common-errors.md b/docs/docs/troubleshooting/common-errors.md similarity index 70% rename from docs/source/docs/troubleshooting/common-errors.md rename to docs/docs/troubleshooting/common-errors.md index 5addeafbc2..8b3904d194 100644 --- a/docs/source/docs/troubleshooting/common-errors.md +++ b/docs/docs/troubleshooting/common-errors.md @@ -1,6 +1,6 @@ # Common Issues / Questions -This page will grow as needed in order to cover commonly seen issues by teams. If this page doesn't help you and you need further assistance, feel free to {ref}`Contact Us`. +This page will grow as needed in order to cover commonly seen issues by teams. If this page doesn't help you and you need further assistance, feel free to \{ref}`Contact Us`. ## Known Issues @@ -14,23 +14,23 @@ Due to an issue with Linux kernels, the drivers for the PS3Eye are no longer sup The logic for controlling LED mode when `multiple cameras are connected` is not fully fleshed out. In its current state, LED control is only enabled when a Pi Camera Module is not in driver mode—meaning a USB camera on its own is unable to control the LEDs. -For now, if you are using multiple cameras, it is recommended that teams set the value of the NetworkTables entry {code}`photonvision/ledMode` from the robot code to control LED state. +For now, if you are using multiple cameras, it is recommended that teams set the value of the NetworkTables entry `photonvision/ledMode` from the robot code to control LED state. ## Commonly Seen Issues ### Networking Issues -Please refer to our comprehensive {ref}`networking troubleshooting tips ` for debugging suggestions and possible causes. +Please refer to our comprehensive \{ref}`networking troubleshooting tips ` for debugging suggestions and possible causes. ### Camera won't show up -Try these steps to {ref}`troubleshoot your camera connection `. +Try these steps to \{ref}`troubleshoot your camera connection `. -If you are using a USB camera, it is possible your USB Camera isn't supported by CSCore and therefore won't work with PhotonVision. See {ref}`supported hardware page for more information `, or the above Camera Troubleshooting page for more information on determining this locally. +If you are using a USB camera, it is possible your USB Camera isn't supported by CSCore and therefore won't work with PhotonVision. See \{ref}`supported hardware page for more information `, or the above Camera Troubleshooting page for more information on determining this locally. ### Camera is consistently returning incorrect values when in 3D mode -Read the tips on the {ref}`camera calibration page`, follow the advice there, and redo the calibration. +Read the tips on the \{ref}`camera calibration page`, follow the advice there, and redo the calibration. ### Not getting data from PhotonLib @@ -38,17 +38,11 @@ Read the tips on the {ref}`camera calibration page 4. When creating a `PhotonCamera` in code, does the `cameraName` provided match the name in the upper-right card of the web interface? Glass can be used to verify the RoboRIO is receiving NetworkTables data by inspecting the `photonvision` subtable for your camera nickname. -```{image} images/camera-subtable.png -:alt: Using Glass to check camera publishing -:width: 600 -``` +Using Glass to check camera publishing ### Unable to download PhotonLib diff --git a/docs/source/docs/troubleshooting/images/camera-subtable.png b/docs/docs/troubleshooting/images/camera-subtable.png similarity index 100% rename from docs/source/docs/troubleshooting/images/camera-subtable.png rename to docs/docs/troubleshooting/images/camera-subtable.png diff --git a/docs/source/docs/troubleshooting/images/glass-connections.png b/docs/docs/troubleshooting/images/glass-connections.png similarity index 100% rename from docs/source/docs/troubleshooting/images/glass-connections.png rename to docs/docs/troubleshooting/images/glass-connections.png diff --git a/docs/source/docs/troubleshooting/logging.md b/docs/docs/troubleshooting/logging.md similarity index 73% rename from docs/source/docs/troubleshooting/logging.md rename to docs/docs/troubleshooting/logging.md index ddf275a606..b97ce7dc67 100644 --- a/docs/source/docs/troubleshooting/logging.md +++ b/docs/docs/troubleshooting/logging.md @@ -1,22 +1,21 @@ # Logging -:::{note} +:::note Logging is very helpful when trying to debug issues within PhotonVision, as it allows us to see what is happening within the program after it is ran. Whenever reporting an issue to PhotonVision, we request that you include logs whenever possible. ::: In addition to storing logs in timestamped files in the config directory, PhotonVision streams logs to the web dashboard. These logs can be viewed later by pressing the \` key. In this view, logs can be filtered by level or downloaded. -:::{note} +:::note When the program first starts, it sends logs from startup to the client that first connects. This does not happen on subsequent connections. ::: -:::{note} -Logs are stored inside the {code}`photonvision_config/logs` directory. Exporting the settings ZIP will also download all old logs for further review. +:::note +Logs are stored inside the `photonvision_config/logs` directory. Exporting the settings ZIP will also download all old logs for further review. ::: -```{raw} html -``` + diff --git a/docs/docs/troubleshooting/networking-troubleshooting.md b/docs/docs/troubleshooting/networking-troubleshooting.md new file mode 100644 index 0000000000..4783b055ca --- /dev/null +++ b/docs/docs/troubleshooting/networking-troubleshooting.md @@ -0,0 +1,47 @@ +# Networking Troubleshooting + +Before reading further, ensure that you follow all the recommendations \{ref}`in our networking section `. You should follow these guidelines in order for PhotonVision to work properly; other networking setups are not officially supported. + +## Checklist + +A few issues make up the majority of support requests. Run through this checklist quickly to catch some common mistakes. + +- Is your camera connected to the robot's radio through a \{ref}`network switch `? + - Ethernet straight from a laptop to a coprocessor will not work (most likely), due to the unreliability of link-local connections. + - Even if there's a switch between your laptop and coprocessor, you'll still want a radio or router in the loop somehow. + - The FRC radio is the _only_ router we will officially support due to the innumerable variations between routers. +- (Raspberry Pi, Orange Pi & Limelight only) have you flashed the correct image, and is it up to date? + - Limelights 2/2+ and Gloworms should be flashed using the Limelight 2 image (eg, `photonvision-v2024.2.8-linuxarm64_limelight2.img.xz`). + - Limelights 3 should be flashed using the Limelight 3 image (eg, `photonvision-v2024.2.8-linuxarm64_limelight3.img.xz`). + - Raspberry Pi devices (including Pi 3, Pi 4, CM3 and CM4) should be flashed using the Raspberry Pi image (eg, `photonvision-v2024.2.8-linuxarm64_RaspberryPi.img.xz`). + - Orange Pi 5 devices should be flashed using the Orange Pi 5 image (eg, `photonvision-v2024.2.8-linuxarm64_orangepi5.img.xz`). + - Orange Pi 5+ devices should be flashed using the Orange Pi 5+ image (eg, `photonvision-v2024.2.8-linuxarm64_orangepi5plus.img.xz`). +- Is your robot code using a **2024** version of WPILib, and is your coprocessor using the most up to date **2024** release? + - 2022, 2023 and 2024 versions of either cannot be mix-and-matched! + - Your PhotonVision version can be checked on the \{ref}`settings tab`. +- Is your team number correctly set on the \{ref}`settings tab`? + +### photonvision.local Not Found + +Use [Angry IP Scanner](https://angryip.org/) and look for an IP that has port 5800 open. Then go to your web browser and do \:5800. + +Alternatively, you can plug your coprocessor into a display, plug in a keyboard, and run `hostname -I` in the terminal. This should give you the IP Address of your coprocessor, then go to your web browser and do \:5800. + +If nothing shows up, ensure your coprocessor has power, and you are following all of our networking recommendations, feel free to \{ref}`contact us ` and we will help you. + +### Can't Connect To Robot + +Please check that: +1\. You don't have the NetworkTables Server on (toggleable in the settings tab). Turn this off when doing work on a robot. +2\. You have your team number set properly in the settings tab. +3\. Your camera name in the `PhotonCamera` constructor matches the name in the UI. +4\. You are using the 2024 version of WPILib and RoboRIO image. +5\. Your robot is on. + +If all of the above are met and you still have issues, feel free to \{ref}`contact us ` and provide the following information: + +- The WPILib version used by your robot code +- PhotonLib vendor dependency version +- PhotonVision version (from the UI) +- Your settings exported from your coprocessor (if you're able to access it) +- How your RoboRIO/coprocessor are networked together diff --git a/docs/docusaurus.config.ts b/docs/docusaurus.config.ts new file mode 100644 index 0000000000..b37f0c5010 --- /dev/null +++ b/docs/docusaurus.config.ts @@ -0,0 +1,130 @@ +import { themes as prismThemes } from "prism-react-renderer"; +import type { Config } from "@docusaurus/types"; +import type * as Preset from "@docusaurus/preset-classic"; + +const config: Config = { + title: "Photonvison Docs", + tagline: "Dinosaurs are cool", + favicon: "RoundLogo.png", + themes: ["docusaurus-theme-github-codeblock"], + // Set the production url of your site here + url: "https://your-docusaurus-site.example.com", + // Set the // pathname under which your site is served + // For GitHub pages deployment, it is often '//' + baseUrl: process.env.READTHEDOCS + ? `/${process.env.READTHEDOCS_LANGUAGE}/${process.env.READTHEDOCS_VERSION}/` + : "/", + + // GitHub pages deployment config. + // If you aren't using GitHub pages, you don't need these. + organizationName: "facebook", // Usually your GitHub org/user name. + projectName: "docusaurus", // Usually your repo name. + + onBrokenLinks: "throw", + onBrokenMarkdownLinks: "warn", + + // Even if you don't use internationalization, you can use this field to set + // useful metadata like html lang. For example, if your site is Chinese, you + // may want to replace "en" with "zh-Hans". + i18n: { + defaultLocale: "en", + locales: ["en"], + }, + + presets: [ + [ + "classic", + { + docs: { + sidebarPath: "./sidebars.ts", + // Please change this to your repo. + // Remove this to remove the "edit this page" links. + editUrl: + "https://github.com/photonvision/photonvision/tree/main/docs/", + }, + + theme: { + customCss: "./src/css/custom.css", + }, + } satisfies Preset.Options, + ], + ], + + themeConfig: { + // Replace with your project's social card + image: "img/docusaurus-social-card.jpg", + navbar: { + title: "Photonvision Docs", + logo: { + alt: "My Site Logo", + src: "RoundLogo.png", + }, + items: [ + { + type: "docSidebar", + sidebarId: "docs", + position: "left", + label: "Tutorial", + }, + { + href: "https://github.com/photonvision/photonvision", + label: "GitHub", + position: "right", + }, + ], + }, + footer: { + style: "dark", + links: [ + { + title: "Docs", + items: [ + { + label: "Tutorial", + to: "/docs/description", + }, + ], + }, + { + title: "Community", + items: [ + { + label: "Stack Overflow", + href: "https://stackoverflow.com/questions/tagged/docusaurus", + }, + { + label: "Discord", + href: "https://discordapp.com/invite/docusaurus", + }, + { + label: "Twitter", + href: "https://twitter.com/docusaurus", + }, + ], + }, + { + title: "More", + items: [ + { + label: "Blog", + to: "/blog", + }, + { + label: "GitHub", + href: "https://github.com/facebook/docusaurus", + }, + ], + }, + ], + copyright: `Copyright © ${new Date().getFullYear()} My Project, Inc. Built with Docusaurus.`, + }, + prism: { + additionalLanguages: ["java", "bash"], + + theme: prismThemes.github, + darkTheme: prismThemes.dracula, + }, + } satisfies Preset.ThemeConfig, +}; + +export default config; diff --git a/docs/package-lock.json b/docs/package-lock.json new file mode 100644 index 0000000000..7d40913f8a --- /dev/null +++ b/docs/package-lock.json @@ -0,0 +1,15879 @@ +{ + "name": "docsu", + "version": "0.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "docsu", + "version": "0.0.0", + "dependencies": { + "@docusaurus/core": "3.5.2", + "@docusaurus/preset-classic": "3.5.2", + "@mdx-js/react": "^3.0.0", + "@saucelabs/theme-github-codeblock": "^0.2.3", + "clsx": "^2.0.0", + "docusaurus-theme-github-codeblock": "^2.0.2", + "prism-react-renderer": "^2.3.0", + "react": "^18.0.0", + "react-dom": "^18.0.0" + }, + "devDependencies": { + "@docusaurus/module-type-aliases": "3.5.2", + "@docusaurus/tsconfig": "3.5.2", + "@docusaurus/types": 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clear", + "serve": "docusaurus serve", + "write-translations": "docusaurus write-translations", + "write-heading-ids": "docusaurus write-heading-ids", + "typecheck": "tsc" + }, + "dependencies": { + "@docusaurus/core": "3.5.2", + "@docusaurus/preset-classic": "3.5.2", + "@mdx-js/react": "^3.0.0", + "@saucelabs/theme-github-codeblock": "^0.2.3", + "clsx": "^2.0.0", + "docusaurus-theme-github-codeblock": "^2.0.2", + "prism-react-renderer": "^2.3.0", + "react": "^18.0.0", + "react-dom": "^18.0.0" + }, + "devDependencies": { + "@docusaurus/module-type-aliases": "3.5.2", + "@docusaurus/tsconfig": "3.5.2", + "@docusaurus/types": "3.5.2", + "typescript": "~5.5.2" + }, + "browserslist": { + "production": [ + ">0.5%", + "not dead", + "not op_mini all" + ], + "development": [ + "last 3 chrome version", + "last 3 firefox version", + "last 5 safari version" + ] + }, + "engines": { + "node": ">=18.0" + } +} diff --git a/docs/sidebars.ts b/docs/sidebars.ts new file mode 100644 index 0000000000..662abbaa9b --- /dev/null +++ b/docs/sidebars.ts @@ -0,0 +1,103 @@ +import type { SidebarsConfig } from "@docusaurus/plugin-content-docs"; + +/** + * Creating a sidebar enables you to: + - create an ordered group of docs + - render a sidebar for each doc of that group + - provide next/previous navigation + + The sidebars can be generated from the filesystem, or explicitly defined here. + + Create as many sidebars as you want. + */ + +const dirToAutogenerated = (dirName: string, title: string) => ({ + type: "category", + label: title, + link: { + slug: `/${dirName}`, + type: "generated-index", + }, + items: [ + { + type: "autogenerated", + dirName, + }, + ], +}); +export default { + docs: [ + { + type: "category", + label: "Getting Started", + collapsible: false, + collapsed: false, + items: [ + "description", + dirToAutogenerated("hardware", "Hardware Selection"), + dirToAutogenerated("installation", "Installation & Setup"), + "settings", + ], + }, + { + type: "category", + label: "Pipeline Tuning and Calibration", + collapsible: true, + collapsed: false, + items: [ + dirToAutogenerated("pipelines", "Pipelines"), + dirToAutogenerated("apriltag-pipelines", "AprilTag Detection"), + dirToAutogenerated("reflectiveAndShape", "Colored Shape & Reflective"), + dirToAutogenerated("objectDetection", "Object Detection"), + "calibration/calibration", + ], + }, + { + type: "category", + label: "Programming Reference", + collapsible: false, + collapsed: false, + items: [ + //"programming/photonlib/index", + dirToAutogenerated( + "programming/photonlib", + "PhotonLib: Robot Code Interface" + ), + dirToAutogenerated("simulation", "Simulation"), + dirToAutogenerated("integration", "Robot Integration"), + dirToAutogenerated("examples", "Code Examples") + ], + }, + { + type: "category", + label: "Additional Resources", + collapsible: false, + collapsed: false, + items: [ + dirToAutogenerated("troubleshooting", "Troubleshooting"), + "additional-resources/best-practices", + "additional-resources/config", + "additional-resources/nt-api", + dirToAutogenerated("contributing", "Contributing to PhotonVision Projects") + ], + }, + { + type: "category", + label: "API Documentation", + collapsible: false, + collapsed: false, + items: [ + { + type: "link", + label: "Java", + href: "https://javadocs.photonvision.org", + }, + { + type: "link", + label: "C++", + href: "https://cppdocs.photonvision.org", + }, + ], + }, + ], +}; diff --git a/docs/source/docs/additional-resources/config.md b/docs/source/docs/additional-resources/config.md deleted file mode 100644 index 76fdfee9cb..0000000000 --- a/docs/source/docs/additional-resources/config.md +++ /dev/null @@ -1,50 +0,0 @@ -# Filesystem Directory - -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. - -## Directory Structure - -The directory structure is outlined below. - -```{image} images/configDir.png -:alt: Config directory structure -:width: 600 -``` - -- calibImgs - - 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 -- imgSaves - - 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. -- hardwareSettings.json - - 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. - -## Importing and Exporting Settings - -The entire settings directory can be exported as a ZIP archive from the settings page. - -```{raw} html - -``` - -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. -- 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. diff --git a/docs/source/docs/apriltag-pipelines/index.md b/docs/source/docs/apriltag-pipelines/index.md deleted file mode 100644 index 1a9044e964..0000000000 --- a/docs/source/docs/apriltag-pipelines/index.md +++ /dev/null @@ -1,10 +0,0 @@ -# AprilTag Detection - -```{toctree} -about-apriltags -detector-types -2D-tracking-tuning -3D-tracking -multitag -coordinate-systems -``` diff --git a/docs/source/docs/contributing/index.md b/docs/source/docs/contributing/index.md deleted file mode 100644 index d9f1137b3e..0000000000 --- a/docs/source/docs/contributing/index.md +++ /dev/null @@ -1,7 +0,0 @@ -# Contributing to PhotonVision Projects - -```{toctree} -building-photon -building-docs -developer-docs/index -``` diff --git a/docs/source/docs/examples/aimandrange.md b/docs/source/docs/examples/aimandrange.md deleted file mode 100644 index f50a711881..0000000000 --- a/docs/source/docs/examples/aimandrange.md +++ /dev/null @@ -1,39 +0,0 @@ -# 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)). - -## Knowledge and Equipment Needed - -- Everything required in {ref}`Aiming at a Target ` and {ref}`Getting in Range of the Target `. - -## Code - -Now that you know how to both aim and get in range of the target, it is time to combine them both at the same time. This example will take the previous two code examples and make them into one function using the same tools as before. With this example, you now have all the knowledge you need to use PhotonVision on your robot in any game. - -```{eval-rst} -.. tab-set:: - - .. tab-item:: Java - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/aimandrange/src/main/java/frc/robot/Robot.java - :language: java - :lines: 42-111 - :linenos: - :lineno-start: 42 - - .. tab-item:: C++ (Header) - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-cpp-examples/aimandrange/src/main/include/Robot.h - :language: cpp - :lines: 27-71 - :linenos: - :lineno-start: 27 - - .. tab-item:: C++ (Source) - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-cpp-examples/aimandrange/src/main/cpp/Robot.cpp - :language: cpp - :lines: 25-67 - :linenos: - :lineno-start: 25 -``` diff --git a/docs/source/docs/examples/aimingatatarget.md b/docs/source/docs/examples/aimingatatarget.md deleted file mode 100644 index d0d4bd3944..0000000000 --- a/docs/source/docs/examples/aimingatatarget.md +++ /dev/null @@ -1,45 +0,0 @@ -# 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)/[C++](https://github.com/PhotonVision/photonvision/tree/master/photonlib-cpp-examples/aimattarget)). - -## Knowledge and Equipment Needed - -- Robot with a vision system running PhotonVision -- Target -- Ability to track a target by properly tuning a pipeline - -## Code - -Now that you have properly set up your vision system and have tuned a pipeline, you can now aim your robot/turret at the target using the data from PhotonVision. This data is reported over NetworkTables and includes: latency, whether there is a target detected or not, pitch, yaw, area, skew, and target pose relative to the robot. This data will be used/manipulated by our vendor dependency, PhotonLib. The documentation for the Network Tables API can be found {ref}`here ` and the documentation for PhotonLib {ref}`here `. - -For this simple example, only yaw is needed. - -In this example, while the operator holds a button down, the robot will turn towards the goal using the P term of a PID loop. To learn more about how PID loops work, how WPILib implements them, and more, visit [Advanced Controls (PID)](https://docs.wpilib.org/en/stable/docs/software/advanced-control/introduction/index.html) and [PID Control in WPILib](https://docs.wpilib.org/en/stable/docs/software/advanced-controls/controllers/pidcontroller.html#pid-control-in-wpilib). - -```{eval-rst} -.. tab-set:: - - .. tab-item:: Java - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/aimattarget/src/main/java/frc/robot/Robot.java - :language: java - :lines: 41-98 - :linenos: - :lineno-start: 41 - - .. tab-item:: C++ (Header) - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-cpp-examples/aimattarget/src/main/include/Robot.h - :language: c++ - :lines: 27-53 - :linenos: - :lineno-start: 27 - - .. tab-item:: C++ (Source) - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-cpp-examples/aimattarget/src/main/cpp/Robot.cpp - :language: c++ - :lines: 25-52 - :linenos: - :lineno-start: 25 -``` diff --git a/docs/source/docs/examples/index.md b/docs/source/docs/examples/index.md deleted file mode 100644 index 1737b68e5f..0000000000 --- a/docs/source/docs/examples/index.md +++ /dev/null @@ -1,11 +0,0 @@ -# Code Examples - -```{toctree} -:maxdepth: 1 - -aimingatatarget -gettinginrangeofthetarget -aimandrange -simaimandrange -simposeest -``` diff --git a/docs/source/docs/examples/simaimandrange.md b/docs/source/docs/examples/simaimandrange.md deleted file mode 100644 index 403c8d5370..0000000000 --- a/docs/source/docs/examples/simaimandrange.md +++ /dev/null @@ -1,96 +0,0 @@ -# Simulating Aiming and Getting in Range - -The following example comes from the PhotonLib example repository ([Java](https://github.com/PhotonVision/photonvision/tree/661f8b2c0495474015f6ea9a89d65f9788436a05/photonlib-java-examples/src/main/java/org/photonlib/examples/simaimandrange)/[C++](https://github.com/PhotonVision/photonvision/tree/661f8b2c0495474015f6ea9a89d65f9788436a05/photonlib-cpp-examples/src/main/cpp/examples/simaimandrange)). Full code is available at those links. - -## Knowledge and Equipment Needed - -- Everything required in {ref}`Combining Aiming and Getting in Range `. - -## Background - -The previous examples show how to run PhotonVision on a real robot, with a physical robot drivetrain moving around and interacting with the software. - -This example builds upon that, adding support for simulating robot motion and incorporating that motion into a {code}`SimVisionSystem`. This allows you to test control algorithms on your development computer, without requiring access to a real robot. - -```{raw} html - -``` - -## Walkthrough - -First, in the main {code}`Robot` source file, we add support to periodically update a new simulation-specific object. This logic only gets used while running in simulation: - -```{eval-rst} -.. tab-set-code:: - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/Robot.java - :language: java - :lines: 118-128 - :linenos: - :lineno-start: 118 -``` - -Then, we add in the implementation of our new `DrivetrainSim` class. Please reference the [WPILib documentation on physics simulation](https://docs.wpilib.org/en/stable/docs/software/wpilib-tools/robot-simulation/physics-sim.html). - -Simulated Vision support is added with the following steps: - -### Creating the Simulated Vision System - -First, we create a new {code}`SimVisionSystem` to represent our camera and coprocessor running PhotonVision. - -```{eval-rst} -.. tab-set-code:: - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java - :language: java - :lines: 73-93 - :linenos: - :lineno-start: 72 -``` - -Next, we create objects to represent the physical location and size of the vision targets we are calibrated to detect. This example models the down-field high goal vision target from the 2020 and 2021 games. - -```{eval-rst} -.. tab-set-code:: - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java - :language: java - :lines: 95-111 - :linenos: - :lineno-start: 95 -``` - -Finally, we add our target to the simulated vision system. - -```{eval-rst} -.. tab-set-code:: - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java - :language: java - :lines: 116-117 - :linenos: - :lineno-start: 113 - -``` - -If you have additional targets you want to detect, you can add them in the same way as the first one. - -### Updating the Simulated Vision System - -Once we have all the properties of our simulated vision system defined, the work to do at runtime becomes very minimal. Simply pass in the robot's pose periodically to the simulated vision system. - -```{eval-rst} -.. tab-set-code:: - - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/ebef19af3d926cf87292177c9a16d01b71219306/photonlib-java-examples/simaimandrange/src/main/java/frc/robot/sim/DrivetrainSim.java - :language: java - :lines: 124-142 - :linenos: - :lineno-start: 122 - -``` - -The rest is done behind the scenes. diff --git a/docs/source/docs/installation/sw_install/romi.md b/docs/source/docs/installation/sw_install/romi.md deleted file mode 100644 index a6b327157f..0000000000 --- a/docs/source/docs/installation/sw_install/romi.md +++ /dev/null @@ -1,22 +0,0 @@ -# Romi Installation - -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`. - -Follow the process for installing PhotonVision on {ref}`"Other Debian-Based Co-Processor Installation" `. As it mentions this will require an internet connection so plugging into the ethernet jack on the Raspberry Pi will be the easiest solution. The pi must remain writable! - -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`. - -```{image} images/nano.png -``` - -After it reboots, you should be able to [locate the PhotonVision UI](https://photonvision.github.io/gloworm-docs/docs/quickstart/#finding-gloworm) at: `http://10.0.0.2:5800/`. - -:::{warning} -In order for settings, logs, etc. to be saved / take effect, ensure that PhotonVision is in writable mode. -::: diff --git a/docs/source/docs/integration/index.md b/docs/source/docs/integration/index.md deleted file mode 100644 index e38af90b68..0000000000 --- a/docs/source/docs/integration/index.md +++ /dev/null @@ -1,10 +0,0 @@ -# Robot Integration - -```{toctree} -:maxdepth: 2 - -background -simpleStrategies -advancedStrategies -aprilTagStrategies -``` diff --git a/docs/source/docs/objectDetection/index.md b/docs/source/docs/objectDetection/index.md deleted file mode 100644 index 694b8c1bd3..0000000000 --- a/docs/source/docs/objectDetection/index.md +++ /dev/null @@ -1,8 +0,0 @@ -# Object Detection - -```{toctree} -:maxdepth: 0 -:titlesonly: true - -about-object-detection -``` diff --git a/docs/source/docs/pipelines/index.md b/docs/source/docs/pipelines/index.md deleted file mode 100644 index 7d8ba7dbd2..0000000000 --- a/docs/source/docs/pipelines/index.md +++ /dev/null @@ -1,7 +0,0 @@ -# Pipelines - -```{toctree} -about-pipelines -input -output -``` diff --git a/docs/source/docs/programming/index.md b/docs/source/docs/programming/index.md deleted file mode 100644 index 3fe28f5843..0000000000 --- a/docs/source/docs/programming/index.md +++ /dev/null @@ -1,11 +0,0 @@ ---- -orphan: true ---- - -# Programming Reference - -```{toctree} -:maxdepth: 1 - -photonlib/index -``` diff --git a/docs/source/docs/programming/photonlib/robot-pose-estimator.md b/docs/source/docs/programming/photonlib/robot-pose-estimator.md deleted file mode 100644 index 2e288f3fc3..0000000000 --- a/docs/source/docs/programming/photonlib/robot-pose-estimator.md +++ /dev/null @@ -1,117 +0,0 @@ -# AprilTags and PhotonPoseEstimator - -:::{note} -For more information on how to methods to get AprilTag data, look {ref}`here `. -::: - -PhotonLib includes a `PhotonPoseEstimator` class, which allows you to combine the pose data from all tags in view in order to get a field relative pose. The `PhotonPoseEstimator` class works with one camera per object instance, but more than one instance may be created. - -## Creating an `AprilTagFieldLayout` - -`AprilTagFieldLayout` is used to represent a layout of AprilTags within a space (field, shop at home, classroom, etc.). WPILib provides a JSON that describes the layout of AprilTags on the field which you can then use in the AprilTagFieldLayout constructor. You can also specify a custom layout. - -The API documentation can be found in here: [Java](https://github.wpilib.org/allwpilib/docs/release/java/edu/wpi/first/apriltag/AprilTagFieldLayout.html) and [C++](https://github.wpilib.org/allwpilib/docs/release/cpp/classfrc_1_1_april_tag_field_layout.html). - -```{eval-rst} -.. tab-set-code:: - .. code-block:: java - - // The field from AprilTagFields will be different depending on the game. - AprilTagFieldLayout aprilTagFieldLayout = AprilTagFields.k2024Crescendo.loadAprilTagLayoutField(); - - .. code-block:: c++ - - // The parameter for LoadAPrilTagLayoutField will be different depending on the game. - frc::AprilTagFieldLayout aprilTagFieldLayout = frc::LoadAprilTagLayoutField(frc::AprilTagField::k2024Crescendo); - -``` - -## Creating a `PhotonPoseEstimator` - -The PhotonPoseEstimator has a constructor that takes an `AprilTagFieldLayout` (see above), `PoseStrategy`, `PhotonCamera`, and `Transform3d`. `PoseStrategy` has six possible values: - -- MULTI_TAG_PNP_ON_COPROCESSOR - - Calculates a new robot position estimate by combining all visible tag corners. Recommended for all teams as it will be the most accurate. - - Must configure the AprilTagFieldLayout properly in the UI, please see {ref}`here ` for more information. -- LOWEST_AMBIGUITY - - Choose the Pose with the lowest ambiguity. -- CLOSEST_TO_CAMERA_HEIGHT - - Choose the Pose which is closest to the camera height. -- CLOSEST_TO_REFERENCE_POSE - - Choose the Pose which is closest to the pose from setReferencePose(). -- CLOSEST_TO_LAST_POSE - - Choose the Pose which is closest to the last pose calculated. -- AVERAGE_BEST_TARGETS - - Choose the Pose which is the average of all the poses from each tag. - -```{eval-rst} -.. tab-set-code:: - .. code-block:: java - - //Forward Camera - cam = new PhotonCamera("testCamera"); - Transform3d robotToCam = new Transform3d(new Translation3d(0.5, 0.0, 0.5), new Rotation3d(0,0,0)); //Cam mounted facing forward, half a meter forward of center, half a meter up from center. - - // Construct PhotonPoseEstimator - PhotonPoseEstimator photonPoseEstimator = new PhotonPoseEstimator(aprilTagFieldLayout, PoseStrategy.CLOSEST_TO_REFERENCE_POSE, cam, robotToCam); - - .. code-block:: c++ - - // Forward Camera - std::shared_ptr cameraOne = - std::make_shared("testCamera"); - // Camera is mounted facing forward, half a meter forward of center, half a - // meter up from center. - frc::Transform3d robotToCam = - frc::Transform3d(frc::Translation3d(0.5_m, 0_m, 0.5_m), - frc::Rotation3d(0_rad, 0_rad, 0_rad)); - - // ... Add other cameras here - - // Assemble the list of cameras & mount locations - std::vector< - std::pair, frc::Transform3d>> - cameras; - cameras.push_back(std::make_pair(cameraOne, robotToCam)); - - photonlib::RobotPoseEstimator estimator( - aprilTags, photonlib::CLOSEST_TO_REFERENCE_POSE, cameras); -``` - -## Using a `PhotonPoseEstimator` - -Calling `update()` on your `PhotonPoseEstimator` will return an `EstimatedRobotPose`, which includes a `Pose3d` of the latest estimated pose (using the selected strategy) along with a `double` of the timestamp when the robot pose was estimated. You should be updating your [drivetrain pose estimator](https://docs.wpilib.org/en/latest/docs/software/advanced-controls/state-space/state-space-pose-estimators.html) with the result from the `PhotonPoseEstimator` every loop using `addVisionMeasurement()`. - -```{eval-rst} -.. tab-set-code:: - .. rli:: https://raw.githubusercontent.com/PhotonVision/photonvision/357d8a518a93f7a1f8084a79449249e613b605a7/photonlib-java-examples/apriltagExample/src/main/java/frc/robot/PhotonCameraWrapper.java - :language: java - :lines: 85-88 - - .. code-block:: c++ - - std::pair getEstimatedGlobalPose( - frc::Pose3d prevEstimatedRobotPose) { - robotPoseEstimator.SetReferencePose(prevEstimatedRobotPose); - units::millisecond_t currentTime = frc::Timer::GetFPGATimestamp(); - auto result = robotPoseEstimator.Update(); - if (result.second) { - return std::make_pair<>(result.first.ToPose2d(), - currentTime - result.second); - } else { - return std::make_pair(frc::Pose2d(), 0_ms); - } - } -``` - -You should be updating your [drivetrain pose estimator](https://docs.wpilib.org/en/latest/docs/software/advanced-controls/state-space/state-space-pose-estimators.html) with the result from the `RobotPoseEstimator` every loop using `addVisionMeasurement()`. TODO: add example note - -## Additional `PhotonPoseEstimator` Methods - -### `setReferencePose(Pose3d referencePose)` - -Updates the stored reference pose when using the CLOSEST_TO_REFERENCE_POSE strategy. - -### `setLastPose(Pose3d lastPose)` - -Update the stored last pose. Useful for setting the initial estimate when using the CLOSEST_TO_LAST_POSE strategy. diff --git a/docs/source/docs/reflectiveAndShape/index.md b/docs/source/docs/reflectiveAndShape/index.md deleted file mode 100644 index a9e293ffcc..0000000000 --- a/docs/source/docs/reflectiveAndShape/index.md +++ /dev/null @@ -1,10 +0,0 @@ -# Colored Shape & Reflective - -```{toctree} -:maxdepth: 0 -:titlesonly: true - -thresholding -contour-filtering -3D -``` diff --git a/docs/source/docs/simulation/index.md b/docs/source/docs/simulation/index.md deleted file mode 100644 index a63a143a97..0000000000 --- a/docs/source/docs/simulation/index.md +++ /dev/null @@ -1,10 +0,0 @@ -# Simulation - -```{toctree} -:maxdepth: 0 -:titlesonly: true - -simulation -simulation-deprecated -hardware-in-the-loop-sim -``` diff --git a/docs/source/docs/troubleshooting/camera-troubleshooting.md b/docs/source/docs/troubleshooting/camera-troubleshooting.md deleted file mode 100644 index a55ff29716..0000000000 --- a/docs/source/docs/troubleshooting/camera-troubleshooting.md +++ /dev/null @@ -1,108 +0,0 @@ -# Camera Troubleshooting - -## Pi Cameras - -If you haven't yet, please refer to {ref}`the Pi CSI Camera Configuration page ` for information on updating {code}`config.txt` for your use case. If you've tried that, and things still aren't working, restart PhotonVision using the restart button in the settings tab, and press tilde (\`) in the web UI once connection is restored. This should show the most recent boot log. - -| | Expected output | Bad | -| ------------------------------- | ----------------------------------------------------- | ---------------------------------- | -| LibCamera driver initialization | Successfully loaded libpicam shared object | Failed to load native libraries! | -| Camera detected | Adding local video device - "unicam" at "/dev/video0" | No output from VisionSourceManager | -| VisionSource created | Adding 1 configs to VMM. | No output from VisionSourceManager | - -If the driver isn't loaded, you may be using a non-official Pi image, or an image not new enough. Try updating to the most recent image available (one released for 2023) -- if that doesn't resolve the problem, {ref}`contact us` with your settings ZIP file and Pi version/camera version/config.txt file used. - -If the camera is not detected, the most likely cause is either a config.txt file incorrectly set-up, or a ribbon cable attached backwards. Review the {ref}`picam configuration page `, and verify the ribbon cable is properly oriented at both ends, and that it is \_fully\_ inserted into the FFC connector. Then, {ref}`contact us` with your settings ZIP file and Pi version/camera version/config.txt file used. - -## USB cameras - -USB cameras supported by CSCore require no libcamera driver initialization to work -- however, similar troubleshooting steps apply. Restart PhotonVision using the restart button in the settings tab, and press tilde on your keyboard (\`) when you're in the web UI once connection is restored. We expect to see the following output: - -| | Expected output | Bad | -| -------------------- | ----------------------------------------------------- | ---------------------------------- | -| Camera detected | Adding local video device - "foobar" at "/dev/foobar" | No output from VisionSourceManager | -| VisionSource created | Adding 1 configs to VMM. | No output from VisionSourceManager | - -## Determining detected cameras in Video4Linux (v4l2) - -On Linux devices (including Raspberry Pi), PhotonVision uses WPILib's CSCore to interact with video devices, which internally uses Video4Linux (v4l2). CSCore, and therefore Photon, requires that cameras attached have good v4l drivers for proper functionality. These should be built into the Linux kernel, and do not need to be installed manually. Valid picamera setup (from /boot/config.txt) can also be determined using these steps. The list-devices command will show all valid video devices detected, and list-formats the list of "video modes" each camera can be in. - -- For picams: edit the config.txt file as described in the {ref}`picam configuration page ` -- SSH into your Pi: {code}`ssh pi@photonvision.local` and enter the username "pi" & password "raspberry" -- run {code}`v4l2-ctl --list-devices` and {code}`v4l2-ctl --list-formats` - -We expect an output similar to the following. For picameras, note the "unicam" entry with path {code}`platform:3f801000.csi` (if we don't see this, that's bad), and a huge list of valid video formats. USB cameras should show up similarly in the output of these commands. - -```{eval-rst} -.. tab-set:: - .. tab-item:: Working - - .. code-block:: - - pi@photonvision:~ $ v4l2-ctl --list-devices - unicam (platform:3f801000.csi): - /dev/video0 - /dev/media3 - - bcm2835-codec-decode (platform:bcm2835-codec): - /dev/video10 - /dev/video11 - /dev/video12 - /dev/video18 - /dev/video31 - /dev/media2 - - bcm2835-isp (platform:bcm2835-isp): - /dev/video13 - /dev/video14 - /dev/video15 - /dev/video16 - /dev/video20 - /dev/video21 - /dev/video22 - /dev/video23 - /dev/media0 - /dev/media1 - - pi@photonvision:~ $ v4l2-ctl --list-formats - ioctl: VIDIOC_ENUM_FMT - Type: Video Capture - - [0]: 'YUYV' (YUYV 4:2:2) - [1]: 'UYVY' (UYVY 4:2:2) - [2]: 'YVYU' (YVYU 4:2:2) - [3]: 'VYUY' (VYUY 4:2:2) - - [42]: 'Y12P' (12-bit Greyscale (MIPI Packed)) - [43]: 'Y12 ' (12-bit Greyscale) - [44]: 'Y14P' (14-bit Greyscale (MIPI Packed)) - [45]: 'Y14 ' (14-bit Greyscale) - - .. tab-item:: Not Working - - .. code-block:: - - pi@photonvision:~ $ v4l2-ctl --list-devices - bcm2835-codec-decode (platform:bcm2835-codec): - /dev/video10 - /dev/video11 - /dev/video12 - /dev/video18 - /dev/video31 - /dev/media3 - bcm2835-isp (platform:bcm2835-isp): - /dev/video13 - /dev/video14 - /dev/video15 - /dev/video16 - /dev/video20 - /dev/video21 - /dev/video22 - /dev/video23 - /dev/media0 - /dev/media1 - rpivid (platform:rpivid): - /dev/video19 - /dev/media2 - Cannot open device /dev/video0, exiting. -``` diff --git a/docs/source/docs/troubleshooting/index.md b/docs/source/docs/troubleshooting/index.md deleted file mode 100644 index 0b8f8384c8..0000000000 --- a/docs/source/docs/troubleshooting/index.md +++ /dev/null @@ -1,10 +0,0 @@ -# Troubleshooting - -```{toctree} -:maxdepth: 1 - -common-errors -logging -camera-troubleshooting -networking-troubleshooting -``` diff --git a/docs/source/docs/troubleshooting/networking-troubleshooting.md b/docs/source/docs/troubleshooting/networking-troubleshooting.md deleted file mode 100644 index d02520aae4..0000000000 --- a/docs/source/docs/troubleshooting/networking-troubleshooting.md +++ /dev/null @@ -1,47 +0,0 @@ -# Networking Troubleshooting - -Before reading further, ensure that you follow all the recommendations {ref}`in our networking section `. You should follow these guidelines in order for PhotonVision to work properly; other networking setups are not officially supported. - -## Checklist - -A few issues make up the majority of support requests. Run through this checklist quickly to catch some common mistakes. - -- Is your camera connected to the robot's radio through a {ref}`network switch `? - - Ethernet straight from a laptop to a coprocessor will not work (most likely), due to the unreliability of link-local connections. - - Even if there's a switch between your laptop and coprocessor, you'll still want a radio or router in the loop somehow. - - The FRC radio is the *only* router we will officially support due to the innumerable variations between routers. -- (Raspberry Pi, Orange Pi & Limelight only) have you flashed the correct image, and is it up to date? - - Limelights 2/2+ and Gloworms should be flashed using the Limelight 2 image (eg, `photonvision-v2024.2.8-linuxarm64_limelight2.img.xz`). - - Limelights 3 should be flashed using the Limelight 3 image (eg, `photonvision-v2024.2.8-linuxarm64_limelight3.img.xz`). - - Raspberry Pi devices (including Pi 3, Pi 4, CM3 and CM4) should be flashed using the Raspberry Pi image (eg, `photonvision-v2024.2.8-linuxarm64_RaspberryPi.img.xz`). - - Orange Pi 5 devices should be flashed using the Orange Pi 5 image (eg, `photonvision-v2024.2.8-linuxarm64_orangepi5.img.xz`). - - Orange Pi 5+ devices should be flashed using the Orange Pi 5+ image (eg, `photonvision-v2024.2.8-linuxarm64_orangepi5plus.img.xz`). -- Is your robot code using a **2024** version of WPILib, and is your coprocessor using the most up to date **2024** release? - - 2022, 2023 and 2024 versions of either cannot be mix-and-matched! - - Your PhotonVision version can be checked on the {ref}`settings tab`. -- Is your team number correctly set on the {ref}`settings tab`? - -### photonvision.local Not Found - -Use [Angry IP Scanner](https://angryip.org/) and look for an IP that has port 5800 open. Then go to your web browser and do \:5800. - -Alternatively, you can plug your coprocessor into a display, plug in a keyboard, and run `hostname -I` in the terminal. This should give you the IP Address of your coprocessor, then go to your web browser and do \:5800. - -If nothing shows up, ensure your coprocessor has power, and you are following all of our networking recommendations, feel free to {ref}`contact us ` and we will help you. - -### Can't Connect To Robot - -Please check that: -1\. You don't have the NetworkTables Server on (toggleable in the settings tab). Turn this off when doing work on a robot. -2\. You have your team number set properly in the settings tab. -3\. Your camera name in the `PhotonCamera` constructor matches the name in the UI. -4\. You are using the 2024 version of WPILib and RoboRIO image. -5\. Your robot is on. - -If all of the above are met and you still have issues, feel free to {ref}`contact us ` and provide the following information: - -- The WPILib version used by your robot code -- PhotonLib vendor dependency version -- PhotonVision version (from the UI) -- Your settings exported from your coprocessor (if you're able to access it) -- How your RoboRIO/coprocessor are networked together diff --git a/docs/src/components/HomepageFeatures/index.tsx b/docs/src/components/HomepageFeatures/index.tsx new file mode 100644 index 0000000000..e69de29bb2 diff --git a/docs/src/components/HomepageFeatures/styles.module.css b/docs/src/components/HomepageFeatures/styles.module.css new file mode 100644 index 0000000000..b248eb2e5d --- /dev/null +++ b/docs/src/components/HomepageFeatures/styles.module.css @@ -0,0 +1,11 @@ +.features { + display: flex; + align-items: center; + padding: 2rem 0; + width: 100%; +} + +.featureSvg { + height: 200px; + width: 200px; +} diff --git a/docs/src/css/custom.css b/docs/src/css/custom.css new file mode 100644 index 0000000000..906f5bc377 --- /dev/null +++ b/docs/src/css/custom.css @@ -0,0 +1,29 @@ +/** + * Any CSS included here will be global. The classic template + * bundles Infima by default. Infima is a CSS framework designed to + * work well for content-centric websites. + */ + +/* You can override the default Infima variables here. */ +:root { + --ifm-color-primary: #006492; + --ifm-color-primary-dark: #005a83; + --ifm-color-primary-darker: #00557c; + --ifm-color-primary-darkest: #004666; + --ifm-color-primary-light: #006ea1; + --ifm-color-primary-lighter: #0073a8; + --ifm-color-primary-lightest: #0082be; +} + + +/* For readability concerns, you should choose a lighter palette in dark mode. */ +[data-theme='dark'] { + --ifm-color-primary: #25c2a0; + --ifm-color-primary-dark: #21af90; + --ifm-color-primary-darker: #1fa588; + --ifm-color-primary-darkest: #1a8870; + --ifm-color-primary-light: #29d5b0; + --ifm-color-primary-lighter: #32d8b4; + --ifm-color-primary-lightest: #4fddbf; + --docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.3); +} diff --git a/docs/src/pages/index.module.css b/docs/src/pages/index.module.css new file mode 100644 index 0000000000..9f71a5da77 --- /dev/null +++ b/docs/src/pages/index.module.css @@ -0,0 +1,23 @@ +/** + * CSS files with the .module.css suffix will be treated as CSS modules + * and scoped locally. + */ + +.heroBanner { + padding: 4rem 0; + text-align: center; + position: relative; + overflow: hidden; +} + +@media screen and (max-width: 996px) { + .heroBanner { + padding: 2rem; + } +} + +.buttons { + display: flex; + align-items: center; + justify-content: center; +} diff --git a/docs/src/pages/index.tsx b/docs/src/pages/index.tsx new file mode 100644 index 0000000000..a2475fae4c --- /dev/null +++ b/docs/src/pages/index.tsx @@ -0,0 +1,42 @@ +import clsx from 'clsx'; +import Link from '@docusaurus/Link'; +import useDocusaurusContext from '@docusaurus/useDocusaurusContext'; +import Layout from '@theme/Layout'; +import HomepageFeatures from '@site/src/components/HomepageFeatures'; +import Heading from '@theme/Heading'; + +import styles from './index.module.css'; + +function HomepageHeader() { + const {siteConfig} = useDocusaurusContext(); + return ( +
+
+ + {siteConfig.title} + +

{siteConfig.tagline}

+
+ + Docusaurus Tutorial - 5min ⏱️ + +
+
+
+ ); +} + +export default function Home(): JSX.Element { + const {siteConfig} = useDocusaurusContext(); + return ( + + +
+
+ + ); +} diff --git a/docs/src/pages/markdown-page.md b/docs/src/pages/markdown-page.md new file mode 100644 index 0000000000..9756c5b668 --- /dev/null +++ b/docs/src/pages/markdown-page.md @@ -0,0 +1,7 @@ +--- +title: Markdown page example +--- + +# Markdown page example + +You don't need React to write simple standalone pages. diff --git a/docs/source/assets/PhotonVision-Header-noBG.png b/docs/static/PhotonVision-Header-noBG.png similarity index 100% rename from docs/source/assets/PhotonVision-Header-noBG.png rename to docs/static/PhotonVision-Header-noBG.png diff --git a/docs/source/assets/PhotonVision-Header-onWhite.png b/docs/static/PhotonVision-Header-onWhite.png similarity index 100% rename from docs/source/assets/PhotonVision-Header-onWhite.png rename to docs/static/PhotonVision-Header-onWhite.png diff --git a/docs/source/assets/RoundLogo.png b/docs/static/RoundLogo.png similarity index 100% rename from docs/source/assets/RoundLogo.png rename to docs/static/RoundLogo.png diff --git a/docs/source/_static/assets/RoundLogoLight.png b/docs/static/RoundLogoLight.png similarity index 100% rename from docs/source/_static/assets/RoundLogoLight.png rename to docs/static/RoundLogoLight.png diff --git a/docs/tsconfig.json b/docs/tsconfig.json new file mode 100644 index 0000000000..314eab8a41 --- /dev/null +++ b/docs/tsconfig.json @@ -0,0 +1,7 @@ +{ + // This file is not used in compilation. It is here just for a nice editor experience. + "extends": "@docusaurus/tsconfig", + "compilerOptions": { + "baseUrl": "." + } +}