Compare commits

...

43 Commits

Author SHA1 Message Date
Matt M
d3025fe458 Backport maven changes 2024-08-02 08:17:04 -07:00
Matt
6a2d83e19b Upload docs to VPS via SFTP (#1235)
Still in testing, might break our docs for now
2024-02-12 19:57:23 -05:00
Matt
1c0d92641f Check empty mean errors in calibration card (#1229)
Fixes calibration card disappearing if calibdb calibration was used
2024-02-12 15:55:31 -05:00
DeltaDizzy
9653c46bdb fix cpp and java photoncamera names (#1230) 2024-02-11 04:27:25 -05:00
Chris Gerth
3738e7821b fix latency calculation (#1227) 2024-02-09 18:45:38 -06:00
Tim Winters
0eb0a4e3c5 Store the last pose on update (#1207)
* Store the last pose on update

* Don't clear lastPose if pose isn't calculated

---------

Co-authored-by: Mohammad Durrani <46766905+mdurrani808@users.noreply.github.com>
2024-02-05 09:50:36 -05:00
Chris Gerth
7666f152bb Fix chessboard gen for unique square sizes (#1217) 2024-02-05 09:48:39 -05:00
Craig Schardt
45a39f6609 Remove duplicate video modes (#1221)
(Fixes #1219)
2024-02-04 22:42:01 -05:00
Matt
bc55218739 Add NPU usage to metrics on supported platforms (#1215) 2024-02-03 12:31:31 -05:00
Matt
e616d93d59 Update CameraCalibrationInfoCard.vue (#1214) 2024-02-02 21:53:47 -05:00
Chris Gerth
5851509a9e Python tweaks (#1211)
* Increasing api parity with java/cpp by adding hasTargets

* type hints fixed up

* wpiFormat
2024-02-02 14:17:53 -06:00
james20902
ea1b701ba7 Add support for different RKNN YOLO models in the backend (#1205) 2024-02-01 23:48:02 -05:00
Matt
62112cd2fd Reduce initial connection bandwidth (#1200)
Reduces bandwidth requirements by being much lazier about how much calibration data is sent to the UI.
2024-02-01 21:42:54 -05:00
Gautam
c7508fea46 Add v4l-utils to install script (#1201)
adds about 2kb to our image
2024-01-27 09:46:50 -05:00
Matt
eca3cea82d Sort object detection results and reduce code duplication (#1173)
* Sort object detection results and reduce code dup.

* Filter objdet results by ratio and area

* Address code review

---------

Co-authored-by: Mohammad Durrani <46766905+mdurrani808@users.noreply.github.com>
2024-01-23 14:10:31 -05:00
Craig Schardt
cbbfbda59d clean up debugging println (#1193) 2024-01-22 22:59:42 -05:00
Drew Williams
a3e1dda3aa Fixed cpp sim apriltag layout and cleaned up cpp sim example (#1190)
* Fixed cpp sim apriltag layout and cleaned up cpp sim example

* changed layout for photoncamerasim

---------

Co-authored-by: Drew Williams <DrewW@iARx.com>
2024-01-22 15:38:25 -05:00
Aiden Lambert
939283df0e Fix positioning of multitarget struct in pipelineresult unpack (#1181)
fixed the unpacking order to match the current pipelineresult data layout.

* fix positioning of multitarget struct in pipelineresult unpack

* fix encode order in PhotonPipelineResult.cpp
2024-01-22 13:05:30 -05:00
Craig Schardt
43338a4e96 Temperature monitoring for RK3588 (#1186) 2024-01-22 07:59:40 -05:00
Craig Schardt
bcea6fcc8d Bump WPILib to 2024.2.1 (#1188) 2024-01-21 20:06:47 -05:00
Ethan Wall
90773e0e4a [photonlib-py] Begin implementing PhotonPoseEstimator in Python (#1178)
* [photonlib-py] Initial impl of PhotonPoseEstimator

---------

Co-authored-by: Matt <matthew.morley.ca@gmail.com>
2024-01-21 06:57:32 -06:00
Matt
57f02f31a5 Dont flush settings on exit after import (#1179)
Fixes bug when importing settings zip that would have the new settings be over written, and would not actually update
2024-01-20 20:49:51 -05:00
Matt
580bbb4a4d Draw calibration rainbow and scale thickness based on image size (#1174) 2024-01-20 20:04:15 -05:00
Craig Schardt
4a0c15b61b Disable the network controls when networkingIsDisabled is true (#1118)
* commented controls that should depend on networkingIsDisabled

* add the thing

* fix Manage Device Networking showing disabled

* commented controls that should depend on networkingIsDisabled

* add the thing

* fix Manage Device Networking showing disabled

* Hide the settings that aren't available when networking is disabled

* Update NetworkingCard.vue

* Update NetworkingCard.vue

---------

Co-authored-by: Sriman Achanta <68172138+srimanachanta@users.noreply.github.com>
2024-01-20 19:46:47 -05:00
Programmers3539
a1df37e20f Add Orange Pi 5 Plus image (#1170)
And bumps both opi images to kill snapd
2024-01-20 19:45:58 -05:00
DeltaDizzy
644c162834 Make java examples independent by adding GradleRIO version (#1158) 2024-01-20 19:45:29 -05:00
Max Worrall
5f591a51c4 [photonlib-py] Remove print statement (#1171) 2024-01-18 11:21:42 -05:00
Sriman Achanta
d59be893ae Fix UI bugs from RKNN PR (#1169)
* fix interactiveCols

* fix deferred store bug

* Fix bug where ObjectDetection pipeline could be made on invalid platforms

* Update vite.config.ts
2024-01-16 22:23:05 -05:00
Ryan Blue
f13a507a71 Fix total ram reporting (#1161) 2024-01-15 23:03:52 -05:00
Programmers3539
628cead2dc Add LL3 image from photon-image-modifier (#1166)
* LL3

* Update build.yml
2024-01-15 22:50:44 -05:00
Mohammad Durrani
7b67f6bebf Add RKNN / Object Detection Pipeline (#1144)
Tested on Orange Pi 5 and Cool Pi 4B. Merge with parts of the OpenCV DNN PR. 

Adds support for YOLOv5s models for Rockchip CPUs with a NPU. Right now hard coded to a note model from alex_idk. Very much still incubating and largely untested.
2024-01-15 22:28:34 -05:00
Matt
e1f550a751 Load libquadmath on Windows (#1163)
Nobody reads these, right? This probably won't make things worse. Surely.
2024-01-15 18:44:58 -05:00
Ryan Blue
a40e4049d4 Update spotless to fix exception spam (#1162) 2024-01-15 15:44:43 -05:00
Matt
152888f216 Bind-mount repo in image builder (#1157)
Reduces built image size by not accidentally copying source in
2024-01-14 13:31:12 -05:00
ArchB1W
b729d9e917 [photon-lib java] Implement ProtobufSerializable (#1156)
* [photon-lib java] Fix classes with protobuf support not "announcing it"

Since they didn't implement `ProtobufSerializable` this meant that most other software didn't even know protobufs were even implemented.
In AdvantageKit for example this would cause it to not work it all and crash.

* Run `spotlessJavaApply`
2024-01-13 22:35:57 -05:00
Thad House
6917ec8401 Fix vendordep including all wpilib libraries (#1155)
* Fix vendordep including all wpilib libraries. Without this fix, users were consuming a massively oversized .jar
2024-01-13 18:57:56 -06:00
Judson James
a8aa32fab5 Fix build.yml (#1153) 2024-01-12 21:39:48 -08:00
Sriman Achanta
e40761aaba Publish photonlib json to releases (#1141) 2024-01-12 23:55:52 -05:00
Judson James
354dd15620 Rewrite ARM builds to use arm-runner-action to resolve OrangePi5 images (#1143) 2024-01-12 20:52:39 -08:00
Matt
07b299a076 Update vendor JSON url (#1150) 2024-01-12 10:07:19 -05:00
Matt
0cec1eef9f [python] Only add maturity/suffix to version if groups matched (#1146)
* Only add maturity/suffix if groups matched

---------

Co-authored-by: Chris Gerth <gerth2@users.noreply.github.com>
2024-01-10 23:23:40 -06:00
Matt
68d8a943f7 Add 2024 test mode pictures (#1136) 2024-01-08 14:09:15 -05:00
Drew Williams
9f0aebe4ce Updates workflow to publish photon-targeting for docker hosts (#1138) 2024-01-08 14:08:48 -05:00
143 changed files with 2620 additions and 1009 deletions

View File

@@ -2,123 +2,14 @@ name: Build
on:
push:
branches: [ master ]
branches:
- master
tags:
- 'v*'
pull_request:
branches: [ master ]
jobs:
build-client:
name: "PhotonClient Build"
defaults:
run:
working-directory: photon-client
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: 18
- name: Install Dependencies
run: npm ci
- name: Build Production Client
run: npm run build
- uses: actions/upload-artifact@v4
with:
name: built-client
path: photon-client/dist/
build-examples:
name: "Build Examples"
runs-on: ubuntu-22.04
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Fetch tags
run: git fetch --tags --force
- name: Install Java 17
uses: actions/setup-java@v4
with:
java-version: 17
distribution: temurin
# Need to publish to maven local first, so that C++ sim can pick it up
# Still haven't figured out how to make the vendordep file be copied before trying to build examples
- name: Publish photonlib to maven local
run: |
chmod +x gradlew
./gradlew publishtomavenlocal -x check
- name: Build Java examples
working-directory: photonlib-java-examples
run: |
chmod +x gradlew
./gradlew copyPhotonlib -x check
./gradlew build -x check --max-workers 2
- name: Build C++ examples
working-directory: photonlib-cpp-examples
run: |
chmod +x gradlew
./gradlew copyPhotonlib -x check
./gradlew build -x check --max-workers 2
build-gradle:
name: "Gradle Build"
runs-on: ubuntu-22.04
steps:
# Checkout code.
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Fetch tags
run: git fetch --tags --force
- name: Install Java 17
uses: actions/setup-java@v3
with:
java-version: 17
distribution: temurin
- name: Install mrcal deps
run: sudo apt-get update && sudo apt-get install -y libcholmod3 liblapack3 libsuitesparseconfig5
- name: Gradle Build
run: |
chmod +x gradlew
./gradlew build -x check --max-workers 2
- name: Gradle Tests
run: ./gradlew testHeadless -i --max-workers 1 --stacktrace
- name: Gradle Coverage
run: ./gradlew jacocoTestReport --max-workers 1
- name: Publish Coverage Report
uses: codecov/codecov-action@v3
with:
file: ./photon-server/build/reports/jacoco/test/jacocoTestReport.xml
- name: Publish Core Coverage Report
uses: codecov/codecov-action@v3
with:
file: ./photon-core/build/reports/jacoco/test/jacocoTestReport.xml
build-offline-docs:
name: "Build Offline Docs"
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
with:
repository: 'PhotonVision/photonvision-docs.git'
ref: master
- uses: actions/setup-python@v5
with:
python-version: '3.9'
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install sphinx sphinx_rtd_theme sphinx-tabs sphinxext-opengraph doc8
pip install -r requirements.txt
- name: Build the docs
run: |
make html
- uses: actions/upload-artifact@master
with:
name: built-docs
path: build/html
build-photonlib-host:
env:
MACOSX_DEPLOYMENT_TARGET: 12
@@ -184,149 +75,7 @@ jobs:
- name: Publish
run: |
chmod +x gradlew
./gradlew photon-lib:publish
./gradlew photon-lib:publish photon-targeting:publish
env:
ARTIFACTORY_API_KEY: ${{ secrets.ARTIFACTORY_API_KEY }}
if: github.event_name == 'push'
build-package:
needs: [build-client, build-gradle, build-offline-docs]
strategy:
fail-fast: false
matrix:
include:
- os: windows-latest
artifact-name: Win64
architecture: x64
arch-override: none
- os: macos-latest
artifact-name: macOS
architecture: x64
arch-override: none
- os: ubuntu-latest
artifact-name: Linux
architecture: x64
arch-override: none
- os: macos-latest
artifact-name: macOSArm
architecture: x64
arch-override: macarm64
- os: ubuntu-latest
artifact-name: LinuxArm32
architecture: x64
arch-override: linuxarm32
- os: ubuntu-latest
artifact-name: LinuxArm64
architecture: x64
arch-override: linuxarm64
runs-on: ${{ matrix.os }}
name: "Build fat JAR - ${{ matrix.artifact-name }}"
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Install Java 17
uses: actions/setup-java@v4
with:
java-version: 17
distribution: temurin
- run: |
rm -rf photon-server/src/main/resources/web/*
mkdir -p photon-server/src/main/resources/web/docs
if: ${{ (matrix.os) != 'windows-latest' }}
- run: |
del photon-server\src\main\resources\web\*.*
mkdir photon-server\src\main\resources\web\docs
if: ${{ (matrix.os) == 'windows-latest' }}
- uses: actions/download-artifact@v4
with:
name: built-client
path: photon-server/src/main/resources/web/
- uses: actions/download-artifact@v4
with:
name: built-docs
path: photon-server/src/main/resources/web/docs
- run: |
chmod +x gradlew
./gradlew photon-server:shadowJar --max-workers 2 -PArchOverride=${{ matrix.arch-override }}
if: ${{ (matrix.arch-override != 'none') }}
- run: |
chmod +x gradlew
./gradlew photon-server:shadowJar --max-workers 2
if: ${{ (matrix.arch-override == 'none') }}
- uses: actions/upload-artifact@v4
with:
name: jar-${{ matrix.artifact-name }}
path: photon-server/build/libs
build-image:
needs: [build-package]
if: ${{ github.event_name != 'pull_request' }}
strategy:
fail-fast: false
matrix:
include:
- os: ubuntu-latest
artifact-name: LinuxArm64
image_suffix: RaspberryPi
image_url: https://github.com/PhotonVision/photon-image-modifier/releases/download/v2024.0.4/photonvision_raspi.img.xz
- os: ubuntu-latest
artifact-name: LinuxArm64
image_suffix: limelight2
image_url: https://github.com/PhotonVision/photon-image-modifier/releases/download/v2024.0.4/photonvision_limelight.img.xz
- os: ubuntu-latest
artifact-name: LinuxArm64
image_suffix: orangepi5
image_url: https://github.com/PhotonVision/photon-image-modifier/releases/download/v2024.0.4/photonvision_opi5.img.xz
runs-on: ${{ matrix.os }}
name: "Build image - ${{ matrix.image_url }}"
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- uses: actions/download-artifact@v4
with:
name: jar-${{ matrix.artifact-name }}
# TODO- replace with the arm-runner action and run this inside of the chroot. but this works for now.
- name: Generate image
run: |
chmod +x scripts/generatePiImage.sh
./scripts/generatePiImage.sh ${{ matrix.image_url }} ${{ matrix.image_suffix }}
- uses: actions/upload-artifact@v4
name: Upload image
with:
name: image-${{ matrix.image_suffix }}
path: photonvision*.xz
release:
needs: [build-package, build-image]
runs-on: ubuntu-22.04
steps:
# Download literally every single artifact. This also downloads client and docs,
# but the filtering below won't pick these up (I hope)
- uses: actions/download-artifact@v4
- run: find
# Push to dev release
- uses: pyTooling/Actions/releaser@r0
with:
token: ${{ secrets.GITHUB_TOKEN }}
tag: 'Dev'
rm: true
files: |
**/*.xz
**/*.jar
if: github.event_name == 'push'
# Upload all jars and xz archives
- uses: softprops/action-gh-release@v1
with:
files: |
**/*.xz
**/*.jar
if: startsWith(github.ref, 'refs/tags/v')
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

View File

@@ -1,92 +0,0 @@
name: Documentation
on:
push:
# For now, run on all commits to master
branches: [ master ]
# and also all tags starting with v
tags:
- 'v*'
# Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages
permissions:
contents: read
pages: write
id-token: write
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
build-client:
name: "PhotonClient Build"
defaults:
run:
working-directory: photon-client
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: 18
- name: Install Dependencies
run: npm ci
- name: Build Production Client
run: npm run build-demo
- uses: actions/upload-artifact@v4
with:
name: built-client
path: photon-client/dist/
run_docs:
runs-on: "ubuntu-22.04"
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Fetch tags
run: git fetch --tags --force
- name: Install Java 17
uses: actions/setup-java@v3
with:
java-version: 17
distribution: temurin
- name: Build javadocs/doxygen
run: |
chmod +x gradlew
./gradlew docs:generateJavaDocs docs:doxygen
- uses: actions/upload-artifact@v4
with:
name: built-docs
path: docs/build/docs
release:
needs: [build-client, run_docs]
environment:
name: github-pages
url: ${{ steps.deployment.outputs.page_url }}
runs-on: ubuntu-22.04
steps:
# Download literally every single artifact.
- uses: actions/download-artifact@v4
- run: find .
- name: Setup Pages
uses: actions/configure-pages@v4
- name: Upload artifact
uses: actions/upload-pages-artifact@v3
with:
# Upload entire repository
path: '.'
- name: Deploy to GitHub Pages
id: deployment
uses: actions/deploy-pages@v4

View File

@@ -1,88 +0,0 @@
name: Lint and Format
on:
push:
branches: [ master ]
tags:
- 'v*'
pull_request:
branches: [ master ]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.ref }}
cancel-in-progress: true
jobs:
wpiformat:
name: "wpiformat"
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v3
- name: Fetch all history and metadata
run: |
git fetch --prune --unshallow
git checkout -b pr
git branch -f master origin/master
- name: Set up Python 3.8
uses: actions/setup-python@v4
with:
python-version: 3.8
- name: Install wpiformat
run: pip3 install wpiformat
- name: Run
run: wpiformat
- name: Check output
run: git --no-pager diff --exit-code HEAD
- name: Generate diff
run: git diff HEAD > wpiformat-fixes.patch
if: ${{ failure() }}
- uses: actions/upload-artifact@v3
with:
name: wpiformat fixes
path: wpiformat-fixes.patch
if: ${{ failure() }}
javaformat:
name: "Java Formatting"
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v3
with:
fetch-depth: 0
- uses: actions/setup-java@v3
with:
java-version: 17
distribution: temurin
- run: |
chmod +x gradlew
./gradlew spotlessCheck
client-lint-format:
name: "PhotonClient Lint and Formatting"
defaults:
run:
working-directory: photon-client
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v3
- name: Setup Node.js
uses: actions/setup-node@v3
with:
node-version: 18
- name: Install Dependencies
run: npm ci
- name: Check Linting
run: npm run lint-ci
- name: Check Formatting
run: npm run format-ci
server-index:
name: "Check server index.html not changed"
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v3
- name: Fetch all history and metadata
run: |
git fetch --prune --unshallow
git checkout -b pr
git branch -f master origin/master
- name: Check index.html not changed
run: git --no-pager diff --exit-code origin/master photon-server/src/main/resources/web/index.html

View File

@@ -1,60 +0,0 @@
name: Build and Distribute PhotonLibPy
permissions:
id-token: write # IMPORTANT: this permission is mandatory for trusted publishing
on:
push:
branches: [ master ]
tags:
- 'v*'
pull_request:
branches: [ master ]
jobs:
buildAndDeploy:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: 3.11
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install setuptools wheel pytest
- name: Build wheel
working-directory: ./photon-lib/py
run: |
python setup.py sdist bdist_wheel
- name: Run Unit Tests
working-directory: ./photon-lib/py
run: |
pip install --no-cache-dir dist/*.whl
pytest
- name: Upload artifacts
uses: actions/upload-artifact@master
with:
name: dist
path: ./photon-lib/py/dist/
- name: Publish package distributions to TestPyPI
# Only upload on tags
if: startsWith(github.ref, 'refs/tags/v')
uses: pypa/gh-action-pypi-publish@release/v1
with:
packages_dir: ./photon-lib/py/dist/
permissions:
id-token: write # IMPORTANT: this permission is mandatory for trusted publishing

View File

@@ -18,6 +18,7 @@ modifiableFileExclude {
\.dll$
\.webp$
\.ico$
\.rknn$
gradlew
}

View File

@@ -1,8 +1,10 @@
import edu.wpi.first.toolchain.*
plugins {
id "com.diffplug.spotless" version "6.22.0"
id "com.diffplug.spotless" version "6.24.0"
id "edu.wpi.first.NativeUtils" version "2024.6.1" apply false
id "edu.wpi.first.wpilib.repositories.WPILibRepositoriesPlugin" version "2020.2"
id "edu.wpi.first.GradleRIO" version "2024.1.1"
id "edu.wpi.first.GradleRIO" version "2024.2.1"
id 'edu.wpi.first.WpilibTools' version '1.3.0'
id 'com.google.protobuf' version '0.9.4' apply false
}
@@ -11,8 +13,9 @@ allprojects {
repositories {
mavenCentral()
mavenLocal()
maven { url = "https://maven.photonvision.org/repository/internal/" }
maven { url = "https://maven.photonvision.org/repository/snapshots/" }
maven { url = "https://maven.photonvision.org/releases" }
maven { url = "https://maven.photonvision.org/snapshots" }
maven { url = "https://jogamp.org/deployment/maven/" }
}
wpilibRepositories.addAllReleaseRepositories(it)
wpilibRepositories.addAllDevelopmentRepositories(it)
@@ -22,15 +25,17 @@ allprojects {
apply from: "versioningHelper.gradle"
ext {
wpilibVersion = "2024.1.1"
wpilibVersion = "2024.2.1"
wpimathVersion = wpilibVersion
openCVversion = "4.8.0-2"
joglVersion = "2.4.0-rc-20200307"
javalinVersion = "5.6.2"
photonGlDriverLibVersion = "dev-v2023.1.0-9-g75fc678"
rknnVersion = "dev-v2024.0.0-64-gc0836a6"
frcYear = "2024"
mrcalVersion = "dev-v2024.0.0-7-gc976aaa";
pubVersion = versionString
isDev = pubVersion.startsWith("dev")
@@ -46,6 +51,10 @@ ext {
println("Building for platform " + jniPlatform + " wpilib: " + wpilibNativeName)
println("Using Wpilib: " + wpilibVersion)
println("Using OpenCV: " + openCVversion)
photonMavenURL = 'https://maven.photonvision.org/' + (isDev ? 'snapshots' : 'releases');
println("Publishing Photonlib to " + photonMavenURL)
}
spotless {
@@ -96,3 +105,7 @@ spotless {
wrapper {
gradleVersion '8.4'
}
ext.getCurrentArch = {
return NativePlatforms.desktop
}

View File

@@ -1,4 +1,4 @@
<!DOCTYPE html>
<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />

View File

@@ -31,7 +31,7 @@
"eslint": "^8.56.0",
"eslint-plugin-vue": "^9.19.2",
"npm-run-all": "^4.1.5",
"prettier": "^3.1.1",
"prettier": "3.2.2",
"sass": "~1.32",
"sass-loader": "^13.3.2",
"terser": "^5.14.2",
@@ -3917,9 +3917,9 @@
}
},
"node_modules/prettier": {
"version": "3.1.1",
"resolved": "https://registry.npmjs.org/prettier/-/prettier-3.1.1.tgz",
"integrity": "sha512-22UbSzg8luF4UuZtzgiUOfcGM8s4tjBv6dJRT7j275NXsy2jb4aJa4NNveul5x4eqlF1wuhuR2RElK71RvmVaw==",
"version": "3.2.2",
"resolved": "https://registry.npmjs.org/prettier/-/prettier-3.2.2.tgz",
"integrity": "sha512-HTByuKZzw7utPiDO523Tt2pLtEyK7OibUD9suEJQrPUCYQqrHr74GGX6VidMrovbf/I50mPqr8j/II6oBAuc5A==",
"dev": true,
"bin": {
"prettier": "bin/prettier.cjs"

View File

@@ -27,17 +27,17 @@
},
"devDependencies": {
"@rushstack/eslint-patch": "^1.3.2",
"@vue/eslint-config-prettier": "^9.0.0",
"@vue/eslint-config-typescript": "^12.0.0",
"prettier": "^3.1.1",
"@types/node": "^16.11.45",
"@types/three": "^0.160.0",
"@vitejs/plugin-vue2": "^2.3.1",
"@vue/eslint-config-prettier": "^9.0.0",
"@vue/eslint-config-typescript": "^12.0.0",
"@vue/tsconfig": "^0.5.1",
"deepmerge": "^4.3.1",
"eslint": "^8.56.0",
"eslint-plugin-vue": "^9.19.2",
"npm-run-all": "^4.1.5",
"prettier": "3.2.2",
"sass": "~1.32",
"sass-loader": "^13.3.2",
"terser": "^5.14.2",

View File

@@ -25,15 +25,10 @@ const getUniqueVideoFormatsByResolution = (): VideoFormat[] => {
const calib = useCameraSettingsStore().getCalibrationCoeffs(format.resolution);
if (calib !== undefined) {
// Is this the right formula for RMS error? who knows! not me!
const perViewSumSquareReprojectionError = calib.observations.flatMap((it) =>
it.reprojectionErrors.flatMap((it2) => [it2.x, it2.y])
);
// For each error, square it, sum the squares, and divide by total points N
format.mean = Math.sqrt(
perViewSumSquareReprojectionError.map((it) => Math.pow(it, 2)).reduce((a, b) => a + b, 0) /
perViewSumSquareReprojectionError.length
);
if (calib.meanErrors.length)
format.mean = calib.meanErrors.reduce((a, b) => a + b, 0) / calib.meanErrors.length;
else format.mean = NaN;
format.horizontalFOV =
2 * Math.atan2(format.resolution.width / 2, calib.cameraIntrinsics.data[0]) * (180 / Math.PI);
@@ -109,7 +104,7 @@ const downloadCalibBoard = () => {
const yPos = chessboardStartY + squareY * squareSizeIn.value;
// Only draw the odd squares to create the chessboard pattern
if ((xPos + yPos + 0.25) % 2 === 0) {
if (squareY % 2 != squareX % 2) {
doc.rect(xPos, yPos, squareSizeIn.value, squareSizeIn.value, "F");
}
}
@@ -263,7 +258,7 @@ const setSelectedVideoFormat = (format: VideoFormat) => {
>
<td>{{ getResolutionString(value.resolution) }}</td>
<td>
{{ value.mean !== undefined ? (isNaN(value.mean) ? "NaN" : value.mean.toFixed(2) + "px") : "-" }}
{{ value.mean !== undefined ? (isNaN(value.mean) ? "Unknown" : value.mean.toFixed(2) + "px") : "-" }}
</td>
<td>{{ value.horizontalFOV !== undefined ? value.horizontalFOV.toFixed(2) + "°" : "-" }}</td>
<td>{{ value.verticalFOV !== undefined ? value.verticalFOV.toFixed(2) + "°" : "-" }}</td>
@@ -311,7 +306,7 @@ const setSelectedVideoFormat = (format: VideoFormat) => {
/>
<pv-number-input
v-model="patternWidth"
label="Board Width (in)"
label="Board Width (squares)"
tooltip="Width of the board in dots or chessboard squares"
:disabled="isCalibrating"
:rules="[(v) => v >= 4 || 'Width must be at least 4']"
@@ -319,7 +314,7 @@ const setSelectedVideoFormat = (format: VideoFormat) => {
/>
<pv-number-input
v-model="patternHeight"
label="Board Height (in)"
label="Board Height (squares)"
tooltip="Height of the board in dots or chessboard squares"
:disabled="isCalibrating"
:rules="[(v) => v >= 4 || 'Height must be at least 4']"

View File

@@ -1,51 +1,19 @@
<script setup lang="ts">
import type { BoardObservation, CameraCalibrationResult, VideoFormat } from "@/types/SettingTypes";
import type { CameraCalibrationResult, VideoFormat } from "@/types/SettingTypes";
import { useCameraSettingsStore } from "@/stores/settings/CameraSettingsStore";
import { useStateStore } from "@/stores/StateStore";
import { ref } from "vue";
import loadingImage from "@/assets/images/loading.svg";
import { computed, inject, ref } from "vue";
import { getResolutionString, parseJsonFile } from "@/lib/PhotonUtils";
const props = defineProps<{
videoFormat: VideoFormat;
}>();
const getMeanFromView = (o: BoardObservation) => {
// Is this the right formula for RMS error? who knows! not me!
const perViewSumSquareReprojectionError = o.reprojectionErrors.flatMap((it2) => [it2.x, it2.y]);
// For each error, square it, sum the squares, and divide by total points N
return Math.sqrt(
perViewSumSquareReprojectionError.map((it) => Math.pow(it, 2)).reduce((a, b) => a + b, 0) /
perViewSumSquareReprojectionError.length
);
const exportCalibration = ref();
const openExportCalibrationPrompt = () => {
exportCalibration.value.click();
};
// Import and export functions
const downloadCalibration = () => {
const calibData = useCameraSettingsStore().getCalibrationCoeffs(props.videoFormat.resolution);
if (calibData === undefined) {
useStateStore().showSnackbarMessage({
color: "error",
message:
"Calibration data isn't available for the requested resolution, please calibrate the requested resolution first"
});
return;
}
const camUniqueName = useCameraSettingsStore().currentCameraSettings.uniqueName;
const filename = `photon_calibration_${camUniqueName}_${calibData.resolution.width}x${calibData.resolution.height}.json`;
const fileData = JSON.stringify(calibData);
const element = document.createElement("a");
element.style.display = "none";
element.setAttribute("href", "data:text/plain;charset=utf-8," + encodeURIComponent(fileData));
element.setAttribute("download", filename);
document.body.appendChild(element);
element.click();
document.body.removeChild(element);
};
const importCalibrationFromPhotonJson = ref();
const openUploadPhotonCalibJsonPrompt = () => {
importCalibrationFromPhotonJson.value.click();
@@ -97,19 +65,28 @@ const importCalibration = async () => {
};
interface ObservationDetails {
snapshotSrc: any;
mean: number;
index: number;
}
const currentCalibrationCoeffs = computed<CameraCalibrationResult | undefined>(() =>
useCameraSettingsStore().getCalibrationCoeffs(props.videoFormat.resolution)
);
const getObservationDetails = (): ObservationDetails[] | undefined => {
return useCameraSettingsStore()
.getCalibrationCoeffs(props.videoFormat.resolution)
?.observations.map((o, i) => ({
index: i,
mean: parseFloat(getMeanFromView(o).toFixed(2)),
snapshotSrc: o.includeObservationInCalibration ? "data:image/png;base64," + o.snapshotData.data : loadingImage
}));
const coefficients = currentCalibrationCoeffs.value;
return coefficients?.meanErrors.map((m, i) => ({
index: i,
mean: parseFloat(m.toFixed(2))
}));
};
const exportCalibrationURL = computed<string>(() =>
useCameraSettingsStore().getCalJSONUrl(inject("backendHost") as string, props.videoFormat.resolution)
);
const calibrationImageURL = (index: number) =>
useCameraSettingsStore().getCalImageUrl(inject<string>("backendHost") as string, props.videoFormat.resolution, index);
</script>
<template>
@@ -140,19 +117,22 @@ const getObservationDetails = (): ObservationDetails[] | undefined => {
<v-btn
color="secondary"
class="mt-4"
:disabled="useCameraSettingsStore().getCalibrationCoeffs(props.videoFormat.resolution) === undefined"
:disabled="!currentCalibrationCoeffs"
style="width: 100%"
@click="downloadCalibration"
@click="openExportCalibrationPrompt"
>
<v-icon left>mdi-export</v-icon>
<span>Export</span>
</v-btn>
<a
ref="exportCalibration"
style="color: black; text-decoration: none; display: none"
:href="exportCalibrationURL"
target="_blank"
/>
</v-col>
</v-row>
<v-row
v-if="useCameraSettingsStore().getCalibrationCoeffs(props.videoFormat.resolution) !== undefined"
class="pt-2"
>
<v-row v-if="currentCalibrationCoeffs" class="pt-2">
<v-card-subtitle>Calibration Details</v-card-subtitle>
<v-simple-table dense style="width: 100%" class="pl-2 pr-2">
<template #default>
@@ -231,7 +211,9 @@ const getObservationDetails = (): ObservationDetails[] | undefined => {
</tr>
<tr>
<td>Horizontal FOV</td>
<td>{{ videoFormat.horizontalFOV !== undefined ? videoFormat.horizontalFOV.toFixed(2) + "°" : "-" }}</td>
<td>
{{ videoFormat.horizontalFOV !== undefined ? videoFormat.horizontalFOV.toFixed(2) + "°" : "-" }}
</td>
</tr>
<tr>
<td>Vertical FOV</td>
@@ -242,11 +224,7 @@ const getObservationDetails = (): ObservationDetails[] | undefined => {
<td>{{ videoFormat.diagonalFOV !== undefined ? videoFormat.diagonalFOV.toFixed(2) + "°" : "-" }}</td>
</tr>
<!-- Board warp, only shown for mrcal-calibrated cameras -->
<tr
v-if="
useCameraSettingsStore().getCalibrationCoeffs(props.videoFormat.resolution)?.calobjectWarp?.length === 2
"
>
<tr v-if="currentCalibrationCoeffs?.calobjectWarp?.length === 2">
<td>Board warp, X/Y</td>
<td>
{{
@@ -278,7 +256,7 @@ const getObservationDetails = (): ObservationDetails[] | undefined => {
<template #expanded-item="{ headers, item }">
<td :colspan="headers.length">
<div style="display: flex; justify-content: center; width: 100%">
<img :src="item.snapshotSrc" alt="observation image" class="snapshot-preview pt-2 pb-2" />
<img :src="calibrationImageURL(item.index)" alt="observation image" class="snapshot-preview pt-2 pb-2" />
</div>
</td>
</template>

View File

@@ -7,6 +7,7 @@ import { computed, ref } from "vue";
import PvIcon from "@/components/common/pv-icon.vue";
import PvInput from "@/components/common/pv-input.vue";
import { PipelineType } from "@/types/PipelineTypes";
import { useSettingsStore } from "@/stores/settings/GeneralSettingsStore";
const changeCurrentCameraIndex = (index: number) => {
useCameraSettingsStore().setCurrentCameraIndex(index, true);
@@ -24,6 +25,9 @@ const changeCurrentCameraIndex = (index: number) => {
case PipelineType.Aruco:
pipelineType.value = WebsocketPipelineType.Aruco;
break;
case PipelineType.ObjectDetection:
pipelineType.value = WebsocketPipelineType.ObjectDetection;
break;
}
};
@@ -121,6 +125,18 @@ const cancelPipelineNameEdit = () => {
const showPipelineCreationDialog = ref(false);
const newPipelineName = ref("");
const newPipelineType = ref<WebsocketPipelineType>(useCameraSettingsStore().currentWebsocketPipelineType);
const validNewPipelineTypes = computed(() => {
const pipelineTypes = [
{ name: "Reflective", value: WebsocketPipelineType.Reflective },
{ name: "Colored Shape", value: WebsocketPipelineType.ColoredShape },
{ name: "AprilTag", value: WebsocketPipelineType.AprilTag },
{ name: "Aruco", value: WebsocketPipelineType.Aruco }
];
if (useSettingsStore().general.rknnSupported) {
pipelineTypes.push({ name: "Object Detection", value: WebsocketPipelineType.ObjectDetection });
}
return pipelineTypes;
});
const showCreatePipelineDialog = () => {
newPipelineName.value = "";
newPipelineType.value = useCameraSettingsStore().currentWebsocketPipelineType;
@@ -154,6 +170,9 @@ const pipelineTypesWrapper = computed<{ name: string; value: number }[]>(() => {
{ name: "AprilTag", value: WebsocketPipelineType.AprilTag },
{ name: "Aruco", value: WebsocketPipelineType.Aruco }
];
if (useSettingsStore().general.rknnSupported) {
pipelineTypes.push({ name: "Object Detection", value: WebsocketPipelineType.ObjectDetection });
}
if (useCameraSettingsStore().isDriverMode) {
pipelineTypes.push({ name: "Driver Mode", value: WebsocketPipelineType.DriverMode });
@@ -208,6 +227,9 @@ useCameraSettingsStore().$subscribe((mutation, state) => {
case PipelineType.Aruco:
pipelineType.value = WebsocketPipelineType.Aruco;
break;
case PipelineType.ObjectDetection:
pipelineType.value = WebsocketPipelineType.ObjectDetection;
break;
}
});
</script>
@@ -350,12 +372,7 @@ useCameraSettingsStore().$subscribe((mutation, state) => {
:select-cols="12 - 3"
label="Tracking Type"
tooltip="Pipeline type, which changes the type of processing that will happen on input frames"
:items="[
{ name: 'Reflective', value: WebsocketPipelineType.Reflective },
{ name: 'Colored Shape', value: WebsocketPipelineType.ColoredShape },
{ name: 'AprilTag', value: WebsocketPipelineType.AprilTag },
{ name: 'Aruco', value: WebsocketPipelineType.Aruco }
]"
:items="validNewPipelineTypes"
/>
</v-card-text>
<v-divider />

View File

@@ -8,6 +8,7 @@ import ThresholdTab from "@/components/dashboard/tabs/ThresholdTab.vue";
import ContoursTab from "@/components/dashboard/tabs/ContoursTab.vue";
import AprilTagTab from "@/components/dashboard/tabs/AprilTagTab.vue";
import ArucoTab from "@/components/dashboard/tabs/ArucoTab.vue";
import ObjectDetectionTab from "@/components/dashboard/tabs/ObjectDetectionTab.vue";
import OutputTab from "@/components/dashboard/tabs/OutputTab.vue";
import TargetsTab from "@/components/dashboard/tabs/TargetsTab.vue";
import PnPTab from "@/components/dashboard/tabs/PnPTab.vue";
@@ -40,6 +41,10 @@ const allTabs = Object.freeze({
tabName: "Aruco",
component: ArucoTab
},
objectDetectionTab: {
tabName: "Object Detection",
component: ObjectDetectionTab
},
outputTab: {
tabName: "Output",
component: OutputTab
@@ -75,6 +80,7 @@ const getTabGroups = (): ConfigOption[][] => {
allTabs.contoursTab,
allTabs.apriltagTab,
allTabs.arucoTab,
allTabs.objectDetectionTab,
allTabs.outputTab
],
[allTabs.targetsTab, allTabs.pnpTab, allTabs.map3dTab]
@@ -82,14 +88,21 @@ const getTabGroups = (): ConfigOption[][] => {
} else if (lgAndDown) {
return [
[allTabs.inputTab],
[allTabs.thresholdTab, allTabs.contoursTab, allTabs.apriltagTab, allTabs.arucoTab, allTabs.outputTab],
[
allTabs.thresholdTab,
allTabs.contoursTab,
allTabs.apriltagTab,
allTabs.arucoTab,
allTabs.objectDetectionTab,
allTabs.outputTab
],
[allTabs.targetsTab, allTabs.pnpTab, allTabs.map3dTab]
];
} else if (xl) {
return [
[allTabs.inputTab],
[allTabs.thresholdTab],
[allTabs.contoursTab, allTabs.apriltagTab, allTabs.arucoTab, allTabs.outputTab],
[allTabs.contoursTab, allTabs.apriltagTab, allTabs.arucoTab, allTabs.objectDetectionTab, allTabs.outputTab],
[allTabs.targetsTab, allTabs.pnpTab, allTabs.map3dTab]
];
}
@@ -103,17 +116,20 @@ const tabGroups = computed<ConfigOption[][]>(() => {
const allow3d = useCameraSettingsStore().currentPipelineSettings.solvePNPEnabled;
const isAprilTag = useCameraSettingsStore().currentWebsocketPipelineType === WebsocketPipelineType.AprilTag;
const isAruco = useCameraSettingsStore().currentWebsocketPipelineType === WebsocketPipelineType.Aruco;
const isObjectDetection =
useCameraSettingsStore().currentWebsocketPipelineType === WebsocketPipelineType.ObjectDetection;
return getTabGroups()
.map((tabGroup) =>
tabGroup.filter(
(tabConfig) =>
!(!allow3d && tabConfig.tabName === "3D") && //Filter out 3D tab any time 3D isn't calibrated
!((!allow3d || isAprilTag || isAruco) && tabConfig.tabName === "PnP") && //Filter out the PnP config tab if 3D isn't available, or we're doing AprilTags
!((isAprilTag || isAruco) && tabConfig.tabName === "Threshold") && //Filter out threshold tab if we're doing AprilTags
!((isAprilTag || isAruco) && tabConfig.tabName === "Contours") && //Filter out contours if we're doing AprilTags
!((!allow3d || isAprilTag || isAruco || isObjectDetection) && tabConfig.tabName === "PnP") && //Filter out the PnP config tab if 3D isn't available, or we're doing AprilTags
!((isAprilTag || isAruco || isObjectDetection) && tabConfig.tabName === "Threshold") && //Filter out threshold tab if we're doing AprilTags
!((isAprilTag || isAruco || isObjectDetection) && tabConfig.tabName === "Contours") && //Filter out contours if we're doing AprilTags
!(!isAprilTag && tabConfig.tabName === "AprilTag") && //Filter out apriltag unless we actually are doing AprilTags
!(!isAruco && tabConfig.tabName === "Aruco") //Filter out aruco unless we actually are doing Aruco
!(!isAruco && tabConfig.tabName === "Aruco") &&
!(!isObjectDetection && tabConfig.tabName === "Object Detection") //Filter out aruco unless we actually are doing Aruco
)
)
.filter((it) => it.length); // Remove empty tab groups

View File

@@ -14,13 +14,12 @@ const currentPipelineSettings = computed<ActivePipelineSettings>(
() => useCameraSettingsStore().currentPipelineSettings
);
const interactiveCols = computed(
() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
)
? 9
: 8;
const interactiveCols = computed(() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
? 9
: 8
);
</script>
<template>

View File

@@ -14,13 +14,12 @@ const currentPipelineSettings = computed<ActivePipelineSettings>(
() => useCameraSettingsStore().currentPipelineSettings
);
const interactiveCols = computed(
() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
)
? 9
: 8;
const interactiveCols = computed(() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
? 9
: 8
);
</script>
<template>

View File

@@ -49,13 +49,12 @@ const contourRadius = computed<[number, number]>({
}
});
const interactiveCols = computed(
() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
)
? 9
: 8;
const interactiveCols = computed(() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
? 9
: 8
);
</script>
<template>

View File

@@ -63,13 +63,12 @@ const handleStreamResolutionChange = (value: number) => {
);
};
const interactiveCols = computed(
() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
)
? 9
: 8;
const interactiveCols = computed(() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
? 9
: 8
);
</script>
<template>

View File

@@ -0,0 +1,83 @@
<script setup lang="ts">
import { useCameraSettingsStore } from "@/stores/settings/CameraSettingsStore";
import { type ActivePipelineSettings, PipelineType } from "@/types/PipelineTypes";
import PvSlider from "@/components/common/pv-slider.vue";
import { computed, getCurrentInstance } from "vue";
import { useStateStore } from "@/stores/StateStore";
// TODO fix pipeline typing in order to fix this, the store settings call should be able to infer that only valid pipeline type settings are exposed based on pre-checks for the entire config section
// Defer reference to store access method
const currentPipelineSettings = computed<ActivePipelineSettings>(
() => useCameraSettingsStore().currentPipelineSettings
);
// TODO fix pv-range-slider so that store access doesn't need to be deferred
const contourArea = computed<[number, number]>({
get: () => Object.values(useCameraSettingsStore().currentPipelineSettings.contourArea) as [number, number],
set: (v) => (useCameraSettingsStore().currentPipelineSettings.contourArea = v)
});
const contourRatio = computed<[number, number]>({
get: () => Object.values(useCameraSettingsStore().currentPipelineSettings.contourRatio) as [number, number],
set: (v) => (useCameraSettingsStore().currentPipelineSettings.contourRatio = v)
});
const interactiveCols = computed(() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
? 9
: 8
);
</script>
<template>
<div v-if="currentPipelineSettings.pipelineType === PipelineType.ObjectDetection">
<pv-slider
v-model="currentPipelineSettings.confidence"
class="pt-2"
:slider-cols="interactiveCols"
label="Confidence"
tooltip="The minimum confidence for a detection to be considered valid. Bigger numbers mean fewer but more probable detections are allowed through."
:min="0"
:max="1"
:step="0.01"
@input="(value) => useCameraSettingsStore().changeCurrentPipelineSetting({ confidence: value }, false)"
/>
<pv-range-slider
v-model="contourArea"
label="Area"
:min="0"
:max="100"
:slider-cols="interactiveCols"
:step="0.01"
@input="(value) => useCameraSettingsStore().changeCurrentPipelineSetting({ contourArea: value }, false)"
/>
<pv-range-slider
v-model="contourRatio"
label="Ratio (W/H)"
tooltip="Min and max ratio between the width and height of a contour's bounding rectangle"
:min="0"
:max="100"
:slider-cols="interactiveCols"
:step="0.01"
@input="(value) => useCameraSettingsStore().changeCurrentPipelineSetting({ contourRatio: value }, false)"
/>
<pv-select
v-model="useCameraSettingsStore().currentPipelineSettings.contourTargetOrientation"
label="Target Orientation"
tooltip="Used to determine how to calculate target landmarks, as well as aspect ratio"
:items="['Portrait', 'Landscape']"
:select-cols="interactiveCols"
@input="
(value) => useCameraSettingsStore().changeCurrentPipelineSetting({ contourTargetOrientation: value }, false)
"
/>
<pv-select
v-model="currentPipelineSettings.contourSortMode"
label="Target Sort"
tooltip="Chooses the sorting mode used to determine the 'best' targets to provide to user code"
:select-cols="interactiveCols"
:items="['Largest', 'Smallest', 'Highest', 'Lowest', 'Rightmost', 'Leftmost', 'Centermost']"
@input="(value) => useCameraSettingsStore().changeCurrentPipelineSetting({ contourSortMode: value }, false)"
/>
</div>
</template>

View File

@@ -46,13 +46,12 @@ const currentPipelineSettings = computed<ActivePipelineSettings>(
() => useCameraSettingsStore().currentPipelineSettings
);
const interactiveCols = computed(
() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
)
? 9
: 8;
const interactiveCols = computed(() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
? 9
: 8
);
</script>
<template>

View File

@@ -6,13 +6,12 @@ import PvSlider from "@/components/common/pv-slider.vue";
import { computed, getCurrentInstance } from "vue";
import { useStateStore } from "@/stores/StateStore";
const interactiveCols = computed(
() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
)
? 9
: 8;
const interactiveCols = computed(() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
? 9
: 8
);
</script>
<template>

View File

@@ -48,6 +48,10 @@ const resetCurrentBuffer = () => {
>
Fiducial ID
</th>
<template v-if="currentPipelineSettings.pipelineType === PipelineType.ObjectDetection">
<th class="text-center white--text">Class</th>
<th class="text-center white--text">Confidence</th>
</template>
<template v-if="!useCameraSettingsStore().currentPipelineSettings.solvePNPEnabled">
<th class="text-center white--text">Pitch &theta;&deg;</th>
<th class="text-center white--text">Yaw &theta;&deg;</th>
@@ -85,6 +89,18 @@ const resetCurrentBuffer = () => {
>
{{ target.fiducialId }}
</td>
<td
v-if="currentPipelineSettings.pipelineType === PipelineType.ObjectDetection"
class="text-center white--text"
>
{{ useStateStore().currentPipelineResults?.classNames[target.classId] }}
</td>
<td
v-if="currentPipelineSettings.pipelineType === PipelineType.ObjectDetection"
class="text-center white--text"
>
{{ target.confidence.toFixed(2) }}
</td>
<template v-if="!useCameraSettingsStore().currentPipelineSettings.solvePNPEnabled">
<td class="text-center">{{ target.pitch.toFixed(2) }}&deg;</td>
<td class="text-center">{{ target.yaw.toFixed(2) }}&deg;</td>

View File

@@ -124,13 +124,12 @@ onBeforeUnmount(() => {
cameraStream.removeEventListener("click", handleStreamClick);
});
const interactiveCols = computed(
() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
)
? 9
: 8;
const interactiveCols = computed(() =>
(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
? 9
: 8
);
</script>
<template>

View File

@@ -27,42 +27,54 @@ const generalMetrics = computed<MetricItem[]>(() => [
value: useSettingsStore().general.gpuAcceleration || "Unknown"
}
]);
const platformMetrics = computed<MetricItem[]>(() => [
{
header: "CPU Temp",
value: useSettingsStore().metrics.cpuTemp === undefined ? "Unknown" : `${useSettingsStore().metrics.cpuTemp}°C`
},
{
header: "CPU Usage",
value: useSettingsStore().metrics.cpuUtil === undefined ? "Unknown" : `${useSettingsStore().metrics.cpuUtil}%`
},
{
header: "CPU Memory Usage",
value:
useSettingsStore().metrics.ramUtil === undefined || useSettingsStore().metrics.cpuMem === undefined
? "Unknown"
: `${useSettingsStore().metrics.ramUtil || "Unknown"}MB of ${useSettingsStore().metrics.cpuMem}MB`
},
{
header: "GPU Memory Usage",
value:
useSettingsStore().metrics.gpuMemUtil === undefined || useSettingsStore().metrics.gpuMem === undefined
? "Unknown"
: `${useSettingsStore().metrics.gpuMemUtil}MB of ${useSettingsStore().metrics.gpuMem}MB`
},
{
header: "CPU Throttling",
value: useSettingsStore().metrics.cpuThr || "Unknown"
},
{
header: "CPU Uptime",
value: useSettingsStore().metrics.cpuUptime || "Unknown"
},
{
header: "Disk Usage",
value: useSettingsStore().metrics.diskUtilPct || "Unknown"
const platformMetrics = computed<MetricItem[]>(() => {
const stats = [
{
header: "CPU Temp",
value: useSettingsStore().metrics.cpuTemp === undefined ? "Unknown" : `${useSettingsStore().metrics.cpuTemp}°C`
},
{
header: "CPU Usage",
value: useSettingsStore().metrics.cpuUtil === undefined ? "Unknown" : `${useSettingsStore().metrics.cpuUtil}%`
},
{
header: "CPU Memory Usage",
value:
useSettingsStore().metrics.ramUtil === undefined || useSettingsStore().metrics.cpuMem === undefined
? "Unknown"
: `${useSettingsStore().metrics.ramUtil || "Unknown"}MB of ${useSettingsStore().metrics.cpuMem}MB`
},
{
header: "GPU Memory Usage",
value:
useSettingsStore().metrics.gpuMemUtil === undefined || useSettingsStore().metrics.gpuMem === undefined
? "Unknown"
: `${useSettingsStore().metrics.gpuMemUtil}MB of ${useSettingsStore().metrics.gpuMem}MB`
},
{
header: "CPU Throttling",
value: useSettingsStore().metrics.cpuThr || "Unknown"
},
{
header: "CPU Uptime",
value: useSettingsStore().metrics.cpuUptime || "Unknown"
},
{
header: "Disk Usage",
value: useSettingsStore().metrics.diskUtilPct || "Unknown"
}
];
if (useSettingsStore().metrics.npuUsage) {
stats.push({
header: "NPU Usage",
value: useSettingsStore().metrics.npuUsage || "Unknown"
});
}
]);
return stats;
});
const metricsLastFetched = ref("Never");
const fetchMetrics = () => {

View File

@@ -5,12 +5,11 @@ import PvInput from "@/components/common/pv-input.vue";
import PvRadio from "@/components/common/pv-radio.vue";
import PvSwitch from "@/components/common/pv-switch.vue";
import PvSelect from "@/components/common/pv-select.vue";
import { NetworkConnectionType, type NetworkSettings } from "@/types/SettingTypes";
import { type ConfigurableNetworkSettings, NetworkConnectionType } from "@/types/SettingTypes";
import { useStateStore } from "@/stores/StateStore";
// Copy object to remove reference to store
const tempSettingsStruct = ref<NetworkSettings>(Object.assign({}, useSettingsStore().network));
const tempSettingsStruct = ref<ConfigurableNetworkSettings>(Object.assign({}, useSettingsStore().network));
const resetTempSettingsStruct = () => {
tempSettingsStruct.value = Object.assign({}, useSettingsStore().network);
};
@@ -58,7 +57,6 @@ const settingsHaveChanged = (): boolean => {
a.runNTServer !== b.runNTServer ||
a.shouldManage !== b.shouldManage ||
a.shouldPublishProto !== b.shouldPublishProto ||
a.canManage !== b.canManage ||
a.networkManagerIface !== b.networkManagerIface ||
a.setStaticCommand !== b.setStaticCommand ||
a.setDHCPcommand !== b.setDHCPcommand
@@ -91,7 +89,10 @@ const saveGeneralSettings = () => {
});
// Update the local settings cause the backend checked their validity. Assign is to deref value
useSettingsStore().network = Object.assign({}, tempSettingsStruct.value);
useSettingsStore().network = {
...useSettingsStore().network,
...Object.assign({}, tempSettingsStruct.value)
};
})
.catch((error) => {
resetTempSettingsStruct();
@@ -162,42 +163,63 @@ watchEffect(() => {
The NetworkTables Server Address is not set or is invalid. NetworkTables is unable to connect.
</v-banner>
<pv-radio
v-show="!useSettingsStore().network.networkingDisabled"
v-model="tempSettingsStruct.connectionType"
label="IP Assignment Mode"
tooltip="DHCP will make the radio (router) automatically assign an IP address; this may result in an IP address that changes across reboots. Static IP assignment means that you pick the IP address and it won't change."
:input-cols="12 - 4"
:list="['DHCP', 'Static']"
:disabled="!(tempSettingsStruct.shouldManage && tempSettingsStruct.canManage)"
:disabled="
!tempSettingsStruct.shouldManage ||
!useSettingsStore().network.canManage ||
useSettingsStore().network.networkingDisabled
"
/>
<pv-input
v-show="!useSettingsStore().network.networkingDisabled"
v-if="tempSettingsStruct.connectionType === NetworkConnectionType.Static"
v-model="tempSettingsStruct.staticIp"
:input-cols="12 - 4"
label="Static IP"
:rules="[(v) => isValidIPv4(v) || 'Invalid IPv4 address']"
:disabled="!(tempSettingsStruct.shouldManage && tempSettingsStruct.canManage)"
:disabled="
!tempSettingsStruct.shouldManage ||
!useSettingsStore().network.canManage ||
useSettingsStore().network.networkingDisabled
"
/>
<pv-input
v-show="!useSettingsStore().network.networkingDisabled"
v-model="tempSettingsStruct.hostname"
label="Hostname"
:input-cols="12 - 4"
:rules="[(v) => isValidHostname(v) || 'Invalid hostname']"
:disabled="!(tempSettingsStruct.shouldManage && tempSettingsStruct.canManage)"
:disabled="
!tempSettingsStruct.shouldManage ||
!useSettingsStore().network.canManage ||
useSettingsStore().network.networkingDisabled
"
/>
<v-divider class="pb-3" />
<span style="font-weight: 700">Advanced Networking</span>
<pv-switch
v-show="!useSettingsStore().network.networkingDisabled"
v-model="tempSettingsStruct.shouldManage"
:disabled="!tempSettingsStruct.canManage"
:disabled="!useSettingsStore().network.canManage || useSettingsStore().network.networkingDisabled"
label="Manage Device Networking"
tooltip="If enabled, Photon will manage device hostname and network settings."
:label-cols="4"
class="pt-2"
/>
<pv-select
v-show="!useSettingsStore().network.networkingDisabled"
v-model="currentNetworkInterfaceIndex"
label="NetworkManager interface"
:disabled="!(tempSettingsStruct.shouldManage && tempSettingsStruct.canManage)"
:disabled="
!tempSettingsStruct.shouldManage ||
!useSettingsStore().network.canManage ||
useSettingsStore().network.networkingDisabled
"
:select-cols="12 - 4"
tooltip="Name of the interface PhotonVision should manage the IP address of"
:items="useSettingsStore().networkInterfaceNames"
@@ -206,7 +228,8 @@ watchEffect(() => {
v-show="
!useSettingsStore().networkInterfaceNames.length &&
tempSettingsStruct.shouldManage &&
tempSettingsStruct.canManage
useSettingsStore().network.canManage &&
!useSettingsStore().network.networkingDisabled
"
rounded
color="red"

View File

@@ -416,6 +416,23 @@ export const useCameraSettingsStore = defineStore("cameraSettings", {
cameraIndex: number = useStateStore().currentCameraIndex
): CameraCalibrationResult | undefined {
return this.cameras[cameraIndex].completeCalibrations.find((v) => resolutionsAreEqual(v.resolution, resolution));
},
getCalImageUrl(host: string, resolution: Resolution, idx: number, cameraIdx = useStateStore().currentCameraIndex) {
const url = new URL(`http://${host}/api/utils/getCalSnapshot`);
url.searchParams.set("width", Math.round(resolution.width).toFixed(0));
url.searchParams.set("height", Math.round(resolution.height).toFixed(0));
url.searchParams.set("snapshotIdx", Math.round(idx).toFixed(0));
url.searchParams.set("cameraIdx", Math.round(cameraIdx).toFixed(0));
return url.href;
},
getCalJSONUrl(host: string, resolution: Resolution, cameraIdx = useStateStore().currentCameraIndex) {
const url = new URL(`http://${host}/api/utils/getCalibrationJSON`);
url.searchParams.set("width", Math.round(resolution.width).toFixed(0));
url.searchParams.set("height", Math.round(resolution.height).toFixed(0));
url.searchParams.set("cameraIdx", Math.round(cameraIdx).toFixed(0));
return url.href;
}
}
});

View File

@@ -27,7 +27,8 @@ export const useSettingsStore = defineStore("settings", {
gpuAcceleration: undefined,
hardwareModel: undefined,
hardwarePlatform: undefined,
mrCalWorking: true
mrCalWorking: true,
rknnSupported: false
},
network: {
ntServerAddress: "",
@@ -58,7 +59,8 @@ export const useSettingsStore = defineStore("settings", {
gpuMemUtil: undefined,
cpuThr: undefined,
cpuUptime: undefined,
diskUtilPct: undefined
diskUtilPct: undefined,
npuUsage: undefined
},
currentFieldLayout: {
field: {
@@ -90,7 +92,8 @@ export const useSettingsStore = defineStore("settings", {
gpuMemUtil: data.gpuMemUtil || undefined,
cpuThr: data.cpuThr || undefined,
cpuUptime: data.cpuUptime || undefined,
diskUtilPct: data.diskUtilPct || undefined
diskUtilPct: data.diskUtilPct || undefined,
npuUsage: data.npuUsage || undefined
};
},
updateGeneralSettingsFromWebsocket(data: WebsocketSettingsUpdate) {
@@ -99,7 +102,8 @@ export const useSettingsStore = defineStore("settings", {
hardwareModel: data.general.hardwareModel || undefined,
hardwarePlatform: data.general.hardwarePlatform || undefined,
gpuAcceleration: data.general.gpuAcceleration || undefined,
mrCalWorking: data.general.mrCalWorking
mrCalWorking: data.general.mrCalWorking,
rknnSupported: data.general.rknnSupported
};
this.lighting = data.lighting;
this.network = data.networkSettings;

View File

@@ -54,6 +54,8 @@ export interface PhotonTarget {
ambiguity: number;
// -1 if not set
fiducialId: number;
confidence: number;
classId: number;
// undefined if 3d isn't enabled
pose?: Transform3d;
}
@@ -70,4 +72,6 @@ export interface PipelineResult {
targets: PhotonTarget[];
// undefined if multitag failed or non-tag pipeline
multitagResult?: MultitagResult;
// Object detection class names -- empty if not doing object detection
classNames: string[];
}

View File

@@ -5,7 +5,8 @@ export enum PipelineType {
Reflective = 2,
ColoredShape = 3,
AprilTag = 4,
Aruco = 5
Aruco = 5,
ObjectDetection = 6
}
export enum AprilTagFamily {
@@ -281,14 +282,39 @@ export const DefaultArucoPipelineSettings: ArucoPipelineSettings = {
doSingleTargetAlways: false
};
export interface ObjectDetectionPipelineSettings extends PipelineSettings {
pipelineType: PipelineType.ObjectDetection;
confidence: number;
nms: number;
box_thresh: number;
}
export type ConfigurableObjectDetectionPipelineSettings = Partial<
Omit<ObjectDetectionPipelineSettings, "pipelineType">
> &
ConfigurablePipelineSettings;
export const DefaultObjectDetectionPipelineSettings: ObjectDetectionPipelineSettings = {
...DefaultPipelineSettings,
pipelineType: PipelineType.ObjectDetection,
cameraGain: 20,
targetModel: TargetModel.InfiniteRechargeHighGoalOuter,
ledMode: true,
outputShowMultipleTargets: false,
cameraExposure: 6,
confidence: 0.9,
nms: 0.45,
box_thresh: 0.25
};
export type ActivePipelineSettings =
| ReflectivePipelineSettings
| ColoredShapePipelineSettings
| AprilTagPipelineSettings
| ArucoPipelineSettings;
| ArucoPipelineSettings
| ObjectDetectionPipelineSettings;
export type ActiveConfigurablePipelineSettings =
| ConfigurableReflectivePipelineSettings
| ConfigurableColoredShapePipelineSettings
| ConfigurableAprilTagPipelineSettings
| ConfigurableArucoPipelineSettings;
| ConfigurableArucoPipelineSettings
| ConfigurableObjectDetectionPipelineSettings;

View File

@@ -7,6 +7,7 @@ export interface GeneralSettings {
hardwareModel?: string;
hardwarePlatform?: string;
mrCalWorking: boolean;
rknnSupported: boolean;
}
export interface MetricData {
@@ -19,6 +20,7 @@ export interface MetricData {
cpuThr?: string;
cpuUptime?: string;
diskUtilPct?: string;
npuUsage?: string;
}
export enum NetworkConnectionType {
@@ -44,9 +46,13 @@ export interface NetworkSettings {
setStaticCommand?: string;
setDHCPcommand?: string;
networkInterfaceNames: NetworkInterfaceType[];
networkingDisabled: boolean;
}
export type ConfigurableNetworkSettings = Omit<NetworkSettings, "canManage" | "networkInterfaceNames">;
export type ConfigurableNetworkSettings = Omit<
NetworkSettings,
"canManage" | "networkInterfaceNames" | "networkingDisabled"
>;
export interface LightingSettings {
supported: boolean;
@@ -133,6 +139,9 @@ export interface CameraCalibrationResult {
distCoeffs: JsonMatOfDouble;
observations: BoardObservation[];
calobjectWarp?: number[];
// We might have to omit observations for bandwith, so backend will send us this
numSnapshots: number;
meanErrors: number[];
}
export enum ValidQuirks {
@@ -250,7 +259,9 @@ export const PlaceholderCameraSettings: CameraSettings = {
snapshotName: "img0.png",
snapshotData: { rows: 480, cols: 640, type: CvType.CV_8U, data: "" }
}
]
],
numSnapshots: 1,
meanErrors: [123.45]
}
],
pipelineNicknames: ["Placeholder Pipeline"],

View File

@@ -101,5 +101,6 @@ export enum WebsocketPipelineType {
Reflective = 0,
ColoredShape = 1,
AprilTag = 2,
Aruco = 3
Aruco = 3,
ObjectDetection = 4
}

View File

@@ -10,25 +10,22 @@ export default defineConfig({
plugins: [
Vue2(),
Components({
resolvers: [
VuetifyResolver()
],
resolvers: [VuetifyResolver()],
dts: true,
transformer: "vue2",
types: [{
from: "vue-router",
names: ["RouterLink", "RouterView"]
}],
types: [
{
from: "vue-router",
names: ["RouterLink", "RouterView"]
}
],
version: 2.7
})
],
css: {
preprocessorOptions: {
sass: {
additionalData: [
"@import \"@/assets/styles/variables.scss\"",
""
].join("\n")
additionalData: ["@import \"@/assets/styles/variables.scss\"", ""].join("\n")
}
}
},

View File

@@ -1,7 +1,31 @@
plugins {
id 'edu.wpi.first.WpilibTools' version '1.3.0'
}
import java.nio.file.Path
apply from: "${rootDir}/shared/common.gradle"
wpilibTools.deps.wpilibVersion = wpi.versions.wpilibVersion.get()
def nativeConfigName = 'wpilibNatives'
def nativeConfig = configurations.create(nativeConfigName)
def nativeTasks = wpilibTools.createExtractionTasks {
configurationName = nativeConfigName
}
nativeTasks.addToSourceSetResources(sourceSets.main)
nativeConfig.dependencies.add wpilibTools.deps.wpilib("wpimath")
nativeConfig.dependencies.add wpilibTools.deps.wpilib("wpinet")
nativeConfig.dependencies.add wpilibTools.deps.wpilib("wpiutil")
nativeConfig.dependencies.add wpilibTools.deps.wpilib("ntcore")
nativeConfig.dependencies.add wpilibTools.deps.wpilib("cscore")
nativeConfig.dependencies.add wpilibTools.deps.wpilib("apriltag")
nativeConfig.dependencies.add wpilibTools.deps.wpilib("hal")
nativeConfig.dependencies.add wpilibTools.deps.wpilibOpenCv("frc" + wpi.frcYear.get(), wpi.versions.opencvVersion.get())
dependencies {
// JOGL stuff (currently we only distribute for aarch64, which is Pi 4)
implementation "org.jogamp.gluegen:gluegen-rt:$joglVersion"
@@ -13,7 +37,8 @@ dependencies {
implementation 'org.zeroturnaround:zt-zip:1.14'
implementation "org.xerial:sqlite-jdbc:3.41.0.0"
implementation "org.photonvision:rknn_jni-jni:$rknnVersion:linuxarm64"
implementation "org.photonvision:rknn_jni-java:$rknnVersion"
implementation "org.photonvision:photon-libcamera-gl-driver-jni:$photonGlDriverLibVersion:linuxarm64"
implementation "org.photonvision:photon-libcamera-gl-driver-java:$photonGlDriverLibVersion"

View File

@@ -50,6 +50,10 @@ public class ConfigManager {
private final Thread settingsSaveThread;
private long saveRequestTimestamp = -1;
// special case flag to disable flushing settings to disk at shutdown. Avoids the jvm shutdown
// hook overwriting the settings we just uploaded
private boolean flushOnShutdown = true;
enum ConfigSaveStrategy {
SQL,
LEGACY,
@@ -296,4 +300,26 @@ public class ConfigManager {
}
}
}
/** Get (and create if not present) the subfolder where ML models are stored */
public File getModelsDirectory() {
var ret = new File(configDirectoryFile, "models");
if (!ret.exists()) ret.mkdirs();
return ret;
}
/**
* Disable flushing settings to disk as part of our JVM exit hook. Used to prevent uploading all
* settings from getting its new configs overwritten at program exit and before theyre all loaded.
*/
public void disableFlushOnShutdown() {
this.flushOnShutdown = false;
}
public void onJvmExit() {
if (flushOnShutdown) {
logger.info("Force-flushing settings...");
saveToDisk();
}
}
}

View File

@@ -0,0 +1,104 @@
/*
* Copyright (C) Photon Vision.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
package org.photonvision.common.configuration;
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.List;
import org.photonvision.common.logging.LogGroup;
import org.photonvision.common.logging.Logger;
import org.photonvision.rknn.RknnJNI;
public class NeuralNetworkModelManager {
private static NeuralNetworkModelManager INSTANCE;
private static final Logger logger = new Logger(NeuralNetworkModelManager.class, LogGroup.Config);
private final String MODEL_NAME = "note-640-640-yolov5s.rknn";
private final RknnJNI.ModelVersion modelVersion = RknnJNI.ModelVersion.YOLO_V5;
private File defaultModelFile;
private List<String> labels;
public static NeuralNetworkModelManager getInstance() {
if (INSTANCE == null) {
INSTANCE = new NeuralNetworkModelManager();
}
return INSTANCE;
}
/**
* Perform initial setup and extract default model from JAR to the filesystem
*
* @param modelsFolder Where models live
*/
public void initialize(File modelsFolder) {
var modelResourcePath = "/models/" + MODEL_NAME;
this.defaultModelFile = new File(modelsFolder, MODEL_NAME);
extractResource(modelResourcePath, defaultModelFile);
File labelsFile = new File(modelsFolder, "labels_v5.txt");
var labelResourcePath = "/models/" + labelsFile.getName();
extractResource(labelResourcePath, labelsFile);
try {
labels = Files.readAllLines(Paths.get(labelsFile.getPath()));
} catch (IOException e) {
logger.error("Error reading labels.txt", e);
}
}
private void extractResource(String resourcePath, File outputFile) {
try (var in = NeuralNetworkModelManager.class.getResourceAsStream(resourcePath)) {
if (in == null) {
logger.error("Failed to find jar resource at " + resourcePath);
return;
}
if (!outputFile.exists()) {
try (FileOutputStream fos = new FileOutputStream(outputFile)) {
int read = -1;
byte[] buffer = new byte[1024];
while ((read = in.read(buffer)) != -1) {
fos.write(buffer, 0, read);
}
} catch (IOException e) {
logger.error("Error extracting resource to " + outputFile.toPath().toString(), e);
}
} else {
logger.info(
"File " + outputFile.toPath().toString() + " already exists. Skipping extraction.");
}
} catch (IOException e) {
logger.error("Error finding jar resource " + resourcePath, e);
}
}
public File getDefaultRknnModel() {
return defaultModelFile;
}
public List<String> getLabels() {
return labels;
}
public RknnJNI.ModelVersion getModelVersion() {
return modelVersion;
}
}

View File

@@ -25,11 +25,13 @@ import java.util.Map;
import java.util.stream.Collectors;
import org.photonvision.PhotonVersion;
import org.photonvision.common.hardware.Platform;
import org.photonvision.common.networking.NetworkManager;
import org.photonvision.common.networking.NetworkUtils;
import org.photonvision.common.util.SerializationUtils;
import org.photonvision.jni.RknnDetectorJNI;
import org.photonvision.mrcal.MrCalJNILoader;
import org.photonvision.raspi.LibCameraJNILoader;
import org.photonvision.vision.calibration.CameraCalibrationCoefficients;
import org.photonvision.vision.calibration.UICameraCalibrationCoefficients;
import org.photonvision.vision.camera.QuirkyCamera;
import org.photonvision.vision.processes.VisionModule;
import org.photonvision.vision.processes.VisionModuleManager;
@@ -120,16 +122,10 @@ public class PhotonConfiguration {
// Hack active interfaces into networkSettings
var netConfigMap = networkConfig.toHashMap();
netConfigMap.put("networkInterfaceNames", NetworkUtils.getAllWiredInterfaces());
netConfigMap.put("networkingDisabled", NetworkManager.getInstance().networkingIsDisabled);
settingsSubmap.put("networkSettings", netConfigMap);
map.put(
"cameraSettings",
VisionModuleManager.getInstance().getModules().stream()
.map(VisionModule::toUICameraConfig)
.map(SerializationUtils::objectToHashMap)
.collect(Collectors.toList()));
var lightingConfig = new UILightingConfig();
lightingConfig.brightness = hardwareSettings.ledBrightnessPercentage;
lightingConfig.supported = !hardwareConfig.ledPins.isEmpty();
@@ -142,7 +138,8 @@ public class PhotonConfiguration {
LibCameraJNILoader.isSupported()
? "Zerocopy Libcamera Working"
: ""); // TODO add support for other types of GPU accel
generalSubmap.put("mrCalWorking", MrCalJNILoader.isWorking());
generalSubmap.put("mrCalWorking", MrCalJNILoader.getInstance().isLoaded());
generalSubmap.put("rknnSupported", RknnDetectorJNI.getInstance().isLoaded());
generalSubmap.put("hardwareModel", hardwareConfig.deviceName);
generalSubmap.put("hardwarePlatform", Platform.getPlatformName());
settingsSubmap.put("general", generalSubmap);
@@ -177,7 +174,7 @@ public class PhotonConfiguration {
public HashMap<Integer, HashMap<String, Object>> videoFormatList;
public int outputStreamPort;
public int inputStreamPort;
public List<CameraCalibrationCoefficients> calibrations;
public List<UICameraCalibrationCoefficients> calibrations;
public boolean isFovConfigurable = true;
public QuirkyCamera cameraQuirks;
public boolean isCSICamera;

View File

@@ -26,6 +26,7 @@ import org.photonvision.common.logging.LogGroup;
import org.photonvision.common.logging.Logger;
import org.photonvision.common.util.SerializationUtils;
import org.photonvision.vision.pipeline.result.CVPipelineResult;
import org.photonvision.vision.pipeline.result.CalibrationPipelineResult;
public class UIDataPublisher implements CVPipelineResultConsumer {
private static final Logger logger = new Logger(UIDataPublisher.class, LogGroup.VisionModule);
@@ -41,17 +42,24 @@ public class UIDataPublisher implements CVPipelineResultConsumer {
public void accept(CVPipelineResult result) {
long now = System.currentTimeMillis();
// only update the UI at 15hz
// only update the UI at 10hz
if (lastUIResultUpdateTime + 1000.0 / 10.0 > now) return;
var dataMap = new HashMap<String, Object>();
dataMap.put("fps", result.fps);
dataMap.put("latency", result.getLatencyMillis());
var uiTargets = new ArrayList<HashMap<String, Object>>(result.targets.size());
for (var t : result.targets) {
uiTargets.add(t.toHashMap());
// We don't actually need to send targets during calibration and it can take up a lot (up to
// 1.2Mbps for 60 snapshots) of target results with no pitch/yaw/etc set
if (!(result instanceof CalibrationPipelineResult)) {
for (var t : result.targets) {
uiTargets.add(t.toHashMap());
}
}
dataMap.put("targets", uiTargets);
dataMap.put("classNames", result.objectDetectionClassNames);
// Only send Multitag Results if they are present, similar to 3d pose
if (result.multiTagResult.estimatedPose.isPresent) {

View File

@@ -145,8 +145,7 @@ public class HardwareManager {
logger.info("Shutting down LEDs...");
if (visionLED != null) visionLED.setState(false);
logger.info("Force-flushing settings...");
ConfigManager.getInstance().saveToDisk();
ConfigManager.getInstance().onJvmExit();
}
public boolean restartDevice() {

View File

@@ -43,6 +43,7 @@ public enum Platform {
true,
OSType.LINUX,
true), // Raspberry Pi 3/4 with a 64-bit image
LINUX_RK3588_64("Linux AARCH 64-bit with RK3588", "linuxarm64", false, OSType.LINUX, true),
LINUX_AARCH64(
"Linux AARCH64", "linuxarm64", false, OSType.LINUX, true), // Jetson Nano, Jetson TX2
@@ -94,6 +95,10 @@ public enum Platform {
return currentPlatform.osType == OSType.LINUX;
}
public static boolean isRK3588() {
return Platform.isOrangePi() || Platform.isCoolPi4b();
}
public static boolean isRaspberryPi() {
return currentPlatform.isPi;
}
@@ -186,7 +191,11 @@ public enum Platform {
return LINUX_32;
} else if (RuntimeDetector.isArm64()) {
// TODO - os detection needed?
return LINUX_AARCH64;
if (isOrangePi()) {
return LINUX_RK3588_64;
} else {
return LINUX_AARCH64;
}
} else if (RuntimeDetector.isArm32()) {
return LINUX_ARM32;
} else {
@@ -204,6 +213,14 @@ public enum Platform {
return fileHasText("/proc/cpuinfo", "Raspberry Pi");
}
private static boolean isOrangePi() {
return fileHasText("/proc/device-tree/model", "Orange Pi 5");
}
private static boolean isCoolPi4b() {
return fileHasText("/proc/device-tree/model", "CoolPi 4B");
}
private static boolean isJetsonSBC() {
// https://forums.developer.nvidia.com/t/how-to-recognize-jetson-nano-device/146624
return fileHasText("/proc/device-tree/model", "NVIDIA Jetson");

View File

@@ -28,6 +28,7 @@ import org.photonvision.common.hardware.metrics.cmds.CmdBase;
import org.photonvision.common.hardware.metrics.cmds.FileCmds;
import org.photonvision.common.hardware.metrics.cmds.LinuxCmds;
import org.photonvision.common.hardware.metrics.cmds.PiCmds;
import org.photonvision.common.hardware.metrics.cmds.RK3588Cmds;
import org.photonvision.common.logging.LogGroup;
import org.photonvision.common.logging.Logger;
import org.photonvision.common.util.ShellExec;
@@ -44,6 +45,8 @@ public class MetricsManager {
cmds = new FileCmds();
} else if (Platform.isRaspberryPi()) {
cmds = new PiCmds(); // Pi's can use a hardcoded command set
} else if (Platform.isRK3588()) {
cmds = new RK3588Cmds(); // RK3588 chipset hardcoded command set
} else if (Platform.isLinux()) {
cmds = new LinuxCmds(); // Linux/Unix platforms assume a nominal command set
} else {
@@ -89,6 +92,10 @@ public class MetricsManager {
return safeExecute(cmds.cpuThrottleReasonCmd);
}
public String getNpuUsage() {
return safeExecute(cmds.npuUsageCommand);
}
private String gpuMemSave = null;
public String getGPUMemorySplit() {
@@ -125,6 +132,7 @@ public class MetricsManager {
metrics.put("ramUtil", this.getUsedRam());
metrics.put("gpuMemUtil", this.getMallocedMemory());
metrics.put("diskUtilPct", this.getUsedDiskPct());
metrics.put("npuUsage", this.getNpuUsage());
DataChangeService.getInstance().publishEvent(OutgoingUIEvent.wrappedOf("metrics", metrics));
}

View File

@@ -29,6 +29,8 @@ public class CmdBase {
// GPU
public String gpuMemoryCommand = "";
public String gpuMemUsageCommand = "";
// NPU
public String npuUsageCommand = "";
// RAM
public String ramUsageCommand = "";
// Disk

View File

@@ -22,7 +22,7 @@ import org.photonvision.common.configuration.HardwareConfig;
public class LinuxCmds extends CmdBase {
public void initCmds(HardwareConfig config) {
// CPU
cpuMemoryCommand = "free -m | awk 'FNR == 2 {print $3}'";
cpuMemoryCommand = "free -m | awk 'FNR == 2 {print $2}'";
// TODO: boards have lots of thermal devices. Hard to pick the CPU

View File

@@ -25,7 +25,6 @@ public class PiCmds extends LinuxCmds {
super.initCmds(config);
// CPU
cpuMemoryCommand = "free -m | awk 'FNR == 2 {print $2}'";
cpuTemperatureCommand = "sed 's/.\\{3\\}$/.&/' /sys/class/thermal/thermal_zone0/temp";
cpuThrottleReasonCmd =
"if (( $(( $(vcgencmd get_throttled | grep -Eo 0x[0-9a-fA-F]*) & 0x01 )) != 0x00 )); then echo \"LOW VOLTAGE\"; "

View File

@@ -0,0 +1,50 @@
/*
* Copyright (C) Photon Vision.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
package org.photonvision.common.hardware.metrics.cmds;
import org.photonvision.common.configuration.HardwareConfig;
public class RK3588Cmds extends LinuxCmds {
/** Applies pi-specific commands, ignoring any input configuration */
public void initCmds(HardwareConfig config) {
super.initCmds(config);
// CPU Temperature
/* The RK3588 chip has 7 thermal zones that can be accessed via:
* /sys/class/thermal/thermal_zoneX/temp
* where X is an interger from 0 to 6.
*
* || Zone || Location || Comments ||
* | 0 | soc | soc thermal (near the center of the chip) |
* | 1 | bigcore0 | CPU Big Core A76_0/1 (CPU4 and CPU5) |
* | 2 | bigcore1 | CPU Big Core A76_2/3 (CPU6 and CPU7) |
* | 3 | littlecore | CPU Small Core A55_0/1/2/3 (CPU0, CPU1, CPU2, and CPU3) |
* | 4 | center | also called PD_CENTER |
* | 5 | gpu | GPU |
* | 6 | npu | NPU |
*
* Sources:
* - http://forum.armsom.org/t/topic/51/3
* - https://lore.kernel.org/lkml/7276280.TLKafQO6qx@archbook/
*/
cpuTemperatureCommand =
"cat /sys/class/thermal/thermal_zone1/temp | awk '{printf \"%.1f\", $1/1000}'";
npuUsageCommand = "cat /sys/kernel/debug/rknpu/load | sed 's/NPU load://; s/^ *//; s/ *$//'";
}
}

View File

@@ -144,6 +144,24 @@ public class TestUtils {
}
}
public enum WPI2024Images {
kBackAmpZone_117in,
kSpeakerCenter_143in;
public static double FOV = 68.5;
public final Path path;
Path getPath() {
var filename = this.toString().substring(1);
return Path.of("2024", filename + ".jpg");
}
WPI2024Images() {
this.path = getPath();
}
}
public enum WPI2023Apriltags {
k162_36_Angle,
k162_36_Straight,

View File

@@ -26,12 +26,15 @@ import org.photonvision.common.logging.LogGroup;
import org.photonvision.common.logging.Logger;
public abstract class PhotonJNICommon {
static boolean libraryLoaded = false;
public abstract boolean isLoaded();
public abstract void setLoaded(boolean state);
protected static Logger logger = null;
protected static synchronized void forceLoad(Class<?> clazz, List<String> libraries)
throws IOException {
if (libraryLoaded) return;
protected static synchronized void forceLoad(
PhotonJNICommon instance, Class<?> clazz, List<String> libraries) throws IOException {
if (instance.isLoaded()) return;
if (logger == null) logger = new Logger(clazz, LogGroup.Camera);
for (var libraryName : libraries) {
@@ -42,7 +45,7 @@ public abstract class PhotonJNICommon {
var in = clazz.getResourceAsStream("/nativelibraries/" + arch_name + "/" + nativeLibName);
if (in == null) {
libraryLoaded = false;
instance.setLoaded(false);
return;
}
@@ -69,15 +72,11 @@ public abstract class PhotonJNICommon {
break;
}
}
libraryLoaded = true;
instance.setLoaded(true);
}
protected static synchronized void forceLoad(Class<?> clazz, String libraryName)
throws IOException {
forceLoad(clazz, List.of(libraryName));
}
public static boolean isWorking() {
return libraryLoaded;
protected static synchronized void forceLoad(
PhotonJNICommon instance, Class<?> clazz, String libraryName) throws IOException {
forceLoad(instance, clazz, List.of(libraryName));
}
}

View File

@@ -0,0 +1,137 @@
/*
* Copyright (C) Photon Vision.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
package org.photonvision.jni;
import java.io.IOException;
import java.util.Arrays;
import java.util.List;
import java.util.concurrent.CopyOnWriteArrayList;
import java.util.stream.Collectors;
import org.photonvision.common.logging.LogGroup;
import org.photonvision.common.logging.Logger;
import org.photonvision.common.util.TestUtils;
import org.photonvision.rknn.RknnJNI;
import org.photonvision.rknn.RknnJNI.RknnResult;
import org.photonvision.vision.opencv.CVMat;
import org.photonvision.vision.pipe.impl.NeuralNetworkPipeResult;
public class RknnDetectorJNI extends PhotonJNICommon {
private static final Logger logger = new Logger(RknnDetectorJNI.class, LogGroup.General);
private boolean isLoaded;
private static RknnDetectorJNI instance = null;
private RknnDetectorJNI() {
isLoaded = false;
}
public static RknnDetectorJNI getInstance() {
if (instance == null) instance = new RknnDetectorJNI();
return instance;
}
public static synchronized void forceLoad() throws IOException {
TestUtils.loadLibraries();
forceLoad(getInstance(), RknnDetectorJNI.class, List.of("rga", "rknnrt", "rknn_jni"));
}
@Override
public boolean isLoaded() {
return isLoaded;
}
@Override
public void setLoaded(boolean state) {
isLoaded = state;
}
public static class RknnObjectDetector {
long objPointer = -1;
private List<String> labels;
private final Object lock = new Object();
private static final CopyOnWriteArrayList<Long> detectors = new CopyOnWriteArrayList<>();
public RknnObjectDetector(String modelPath, List<String> labels, RknnJNI.ModelVersion version) {
synchronized (lock) {
objPointer = RknnJNI.create(modelPath, labels.size(), version.ordinal(), -1);
detectors.add(objPointer);
System.out.println(
"Created " + objPointer + "! Detectors: " + Arrays.toString(detectors.toArray()));
}
this.labels = labels;
}
public List<String> getClasses() {
return labels;
}
/**
* Detect forwards using this model
*
* @param in The image to process
* @param nmsThresh Non-maximum supression threshold. Probably should not change
* @param boxThresh Minimum confidence for a box to be added. Basically just confidence
* threshold
*/
public List<NeuralNetworkPipeResult> detect(CVMat in, double nmsThresh, double boxThresh) {
RknnResult[] ret;
synchronized (lock) {
// We can technically be asked to detect and the lock might be acquired _after_ release has
// been called. This would mean objPointer would be invalid which would call everything to
// explode.
if (objPointer > 0) {
ret = RknnJNI.detect(objPointer, in.getMat().getNativeObjAddr(), nmsThresh, boxThresh);
} else {
logger.warn("Detect called after destroy -- giving up");
return List.of();
}
}
if (ret == null) {
return List.of();
}
return List.of(ret).stream()
.map(it -> new NeuralNetworkPipeResult(it.rect, it.class_id, it.conf))
.collect(Collectors.toList());
}
public void release() {
synchronized (lock) {
if (objPointer > 0) {
RknnJNI.destroy(objPointer);
detectors.remove(objPointer);
System.out.println(
"Killed " + objPointer + "! Detectors: " + Arrays.toString(detectors.toArray()));
objPointer = -1;
} else {
logger.error("RKNN Detector has already been destroyed!");
}
}
}
}
// public static void createRknnDetector() {
// objPointer =
// RknnJNI.create(
// NeuralNetworkModelManager.getInstance()
// .getDefaultRknnModel()
// .getAbsolutePath()
// .toString(),
// NeuralNetworkModelManager.getInstance().getLabels().size());
// }
}

View File

@@ -24,6 +24,19 @@ import org.photonvision.common.util.TestUtils;
import org.photonvision.jni.PhotonJNICommon;
public class MrCalJNILoader extends PhotonJNICommon {
private boolean isLoaded;
private static MrCalJNILoader instance = null;
private MrCalJNILoader() {
isLoaded = false;
}
public static synchronized MrCalJNILoader getInstance() {
if (instance == null) instance = new MrCalJNILoader();
return instance;
}
public static synchronized void forceLoad() throws IOException {
// Force load opencv
TestUtils.loadLibraries();
@@ -32,6 +45,7 @@ public class MrCalJNILoader extends PhotonJNICommon {
if (Platform.isWindows()) {
// Order is correct to match dependencies of libraries
forceLoad(
MrCalJNILoader.getInstance(),
MrCalJNILoader.class,
List.of(
"libamd",
@@ -40,17 +54,28 @@ public class MrCalJNILoader extends PhotonJNICommon {
"libccolamd",
"openblas",
"libgcc_s_seh-1",
"libquadmath-0",
"libgfortran-5",
"liblapack",
"libcholmod",
"mrcal_jni"));
} else {
// Nothing else to do on linux
forceLoad(MrCalJNILoader.class, List.of("mrcal_jni"));
forceLoad(MrCalJNILoader.getInstance(), MrCalJNILoader.class, List.of("mrcal_jni"));
}
if (!MrCalJNILoader.isWorking()) {
if (!MrCalJNILoader.getInstance().isLoaded()) {
throw new IOException("Unable to load mrcal JNI!");
}
}
@Override
public boolean isLoaded() {
return isLoaded;
}
@Override
public void setLoaded(boolean state) {
isLoaded = state;
}
}

View File

@@ -24,7 +24,7 @@ import java.util.List;
import org.opencv.core.Point;
import org.opencv.core.Point3;
public final class BoardObservation {
public final class BoardObservation implements Cloneable {
// Expected feature 3d location in the camera frame
@JsonProperty("locationInObjectSpace")
public List<Point3> locationInObjectSpace;
@@ -68,4 +68,33 @@ public final class BoardObservation {
this.snapshotName = snapshotName;
this.snapshotData = snapshotData;
}
@Override
public String toString() {
return "BoardObservation [locationInObjectSpace="
+ locationInObjectSpace
+ ", locationInImageSpace="
+ locationInImageSpace
+ ", reprojectionErrors="
+ reprojectionErrors
+ ", optimisedCameraToObject="
+ optimisedCameraToObject
+ ", includeObservationInCalibration="
+ includeObservationInCalibration
+ ", snapshotName="
+ snapshotName
+ ", snapshotData="
+ snapshotData
+ "]";
}
@Override
public BoardObservation clone() {
try {
return (BoardObservation) super.clone();
} catch (CloneNotSupportedException e) {
System.err.println("Guhhh clone buh");
return null;
}
}
}

View File

@@ -191,8 +191,8 @@ public class CameraCalibrationCoefficients implements Releasable {
+ cameraIntrinsics
+ ", distCoeffs="
+ distCoeffs
+ ", observations="
+ observations
+ ", observationslen="
+ observations.size()
+ ", calobjectWarp="
+ Arrays.toString(calobjectWarp)
+ ", intrinsicsArr="
@@ -201,4 +201,16 @@ public class CameraCalibrationCoefficients implements Releasable {
+ Arrays.toString(distCoeffsArr)
+ "]";
}
public UICameraCalibrationCoefficients cloneWithoutObservations() {
return new UICameraCalibrationCoefficients(
resolution,
cameraIntrinsics,
distCoeffs,
calobjectWarp,
observations,
calobjectSize,
calobjectSpacing,
lensmodel);
}
}

View File

@@ -76,4 +76,17 @@ public class JsonImageMat implements Releasable {
public void release() {
if (wrappedMat != null) wrappedMat.release();
}
@Override
public String toString() {
return "JsonImageMat [rows="
+ rows
+ ", cols="
+ cols
+ ", type="
+ type
+ ", datalen="
+ data.length()
+ "]";
}
}

View File

@@ -40,7 +40,7 @@ public class JsonMatOfDouble implements Releasable {
@JsonIgnore private Mat wrappedMat = null;
@JsonIgnore private Matrix wpilibMat = null;
private MatOfDouble wrappedMatOfDouble;
@JsonIgnore private MatOfDouble wrappedMatOfDouble;
public JsonMatOfDouble(int rows, int cols, double[] data) {
this(rows, cols, CvType.CV_64FC1, data);

View File

@@ -0,0 +1,59 @@
/*
* Copyright (C) Photon Vision.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
package org.photonvision.vision.calibration;
import java.util.List;
import java.util.stream.Collectors;
import org.opencv.core.Size;
public class UICameraCalibrationCoefficients extends CameraCalibrationCoefficients {
public int numSnapshots;
public List<Double> meanErrors;
public UICameraCalibrationCoefficients(
Size resolution,
JsonMatOfDouble cameraIntrinsics,
JsonMatOfDouble distCoeffs,
double[] calobjectWarp,
List<BoardObservation> observations,
Size calobjectSize,
double calobjectSpacing,
CameraLensModel lensmodel) {
// yeet observations, keep all else
super(
resolution,
cameraIntrinsics,
distCoeffs,
calobjectWarp,
List.of(),
calobjectSize,
calobjectSpacing,
lensmodel);
this.numSnapshots = observations.size();
this.meanErrors =
observations.stream()
.map(
it2 ->
it2.reprojectionErrors.stream()
.mapToDouble(it -> Math.sqrt(it.x * it.x + it.y * it.y))
.average()
.orElse(0))
.collect(Collectors.toList());
}
}

View File

@@ -395,6 +395,7 @@ public class USBCameraSource extends VisionSource {
// Sort by resolution
var sortedList =
videoModesList.stream()
.distinct() // remove redundant video mode entries
.sorted(((a, b) -> (b.width + b.height) - (a.width + a.height)))
.collect(Collectors.toList());
Collections.reverse(sortedList);

View File

@@ -47,6 +47,16 @@ public class Contour implements Releasable {
this.mat = mat;
}
public Contour(Rect2d box) {
// no easy way to convert a Rect2d to Mat, diy it. Order is tl tr br bl
this.mat =
new MatOfPoint(
box.tl(),
new Point(box.x + box.width, box.y),
box.br(),
new Point(box.x, box.y + box.height));
}
public MatOfPoint2f getMat2f() {
if (mat2f == null) {
mat2f = new MatOfPoint2f(mat.toArray());

View File

@@ -25,15 +25,15 @@ public enum ContourSortMode {
Comparator.comparingDouble(PotentialTarget::getArea)
.reversed()), // reversed so that zero index has the largest size
Smallest(Largest.getComparator().reversed()),
Highest(Comparator.comparingDouble(rect -> rect.getMinAreaRect().center.y)),
Highest(Comparator.comparingDouble(tgt -> tgt.getMinAreaRect().center.y)),
Lowest(Highest.getComparator().reversed()),
Leftmost(Comparator.comparingDouble(target -> target.getMinAreaRect().center.x * -1)),
Leftmost(Comparator.comparingDouble(tgt -> tgt.getMinAreaRect().center.x * -1)),
Rightmost(Leftmost.getComparator().reversed()),
Centermost(
Comparator.comparingDouble(
rect ->
(Math.pow(rect.getMinAreaRect().center.y, 2)
+ Math.pow(rect.getMinAreaRect().center.x, 2))));
tgt ->
(Math.pow(tgt.getMinAreaRect().center.y, 2)
+ Math.pow(tgt.getMinAreaRect().center.x, 2))));
private final Comparator<PotentialTarget> m_comparator;

View File

@@ -33,6 +33,10 @@ public abstract class CVPipe<I, O, P> {
this.params = params;
}
public P getParams() {
return this.params;
}
/**
* Runs the process for the pipe.
*

View File

@@ -44,6 +44,13 @@ public class ArucoDetectionPipe
@Override
protected List<ArucoDetectionResult> process(CVMat in) {
var imgMat = in.getMat();
// Sanity check -- image should not be empty
if (imgMat.empty()) {
// give up is best we can do here
return List.of();
}
var detections = photonDetector.detect(imgMat);
// manually do corner refinement ourselves
if (params.useCornerRefinement) {

View File

@@ -77,7 +77,7 @@ public class Calibrate3dPipe
CameraCalibrationCoefficients ret;
var start = System.nanoTime();
if (MrCalJNILoader.isWorking() && params.useMrCal) {
if (MrCalJNILoader.getInstance().isLoaded() && params.useMrCal) {
logger.debug("Calibrating with mrcal!");
ret = calibrateMrcal(in);
} else {

View File

@@ -15,7 +15,7 @@
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
package org.photonvision.vision.pipeline;
package org.photonvision.vision.pipe.impl;
import edu.wpi.first.math.util.Units;
import java.util.ArrayList;
@@ -36,10 +36,10 @@ import org.photonvision.vision.frame.FrameThresholdType;
import org.photonvision.vision.opencv.CVMat;
import org.photonvision.vision.opencv.ImageRotationMode;
import org.photonvision.vision.pipe.CVPipe.CVPipeResult;
import org.photonvision.vision.pipe.impl.CalculateFPSPipe;
import org.photonvision.vision.pipe.impl.Calibrate3dPipe;
import org.photonvision.vision.pipe.impl.FindBoardCornersPipe;
import org.photonvision.vision.pipe.impl.FindBoardCornersPipe.FindBoardCornersPipeResult;
import org.photonvision.vision.pipeline.CVPipeline;
import org.photonvision.vision.pipeline.Calibration3dPipelineSettings;
import org.photonvision.vision.pipeline.UICalibrationData;
import org.photonvision.vision.pipeline.result.CVPipelineResult;
import org.photonvision.vision.pipeline.result.CalibrationPipelineResult;

View File

@@ -22,6 +22,7 @@ import java.util.List;
import org.apache.commons.lang3.tuple.Pair;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.imgproc.Imgproc;
import org.photonvision.common.util.ColorHelper;
import org.photonvision.vision.frame.FrameDivisor;
@@ -31,22 +32,44 @@ import org.photonvision.vision.target.TrackedTarget;
public class DrawCalibrationPipe
extends MutatingPipe<
Pair<Mat, List<TrackedTarget>>, DrawCalibrationPipe.DrawCalibrationPipeParams> {
Scalar[] chessboardColors =
new Scalar[] {
ColorHelper.colorToScalar(Color.RED, 0.4),
ColorHelper.colorToScalar(Color.ORANGE, 0.4),
ColorHelper.colorToScalar(Color.GREEN, 0.4),
ColorHelper.colorToScalar(Color.BLUE, 0.4),
ColorHelper.colorToScalar(Color.MAGENTA, 0.4),
};
@Override
protected Void process(Pair<Mat, List<TrackedTarget>> in) {
var image = in.getLeft();
var imgSz = image.size();
var diag = Math.hypot(imgSz.width, imgSz.height);
// heuristic: about 4px at a diagonal of 750px, or .5%, 'looks good'. keep it at least 3px at
// worst tho
int r = (int) Math.max(diag * 4.0 / 750.0, 3);
int thickness = (int) Math.max(diag * 1.0 / 600.0, 1);
int i = 0;
for (var target : in.getRight()) {
for (var c : target.getTargetCorners()) {
c =
new Point(
c.x / params.divisor.value.doubleValue(), c.y / params.divisor.value.doubleValue());
var r = 4;
var r2 = r / Math.sqrt(2);
var color = ColorHelper.colorToScalar(Color.RED, 0.4);
Imgproc.circle(image, c, r, color, 1);
Imgproc.line(image, new Point(c.x - r2, c.y - r2), new Point(c.x + r2, c.y + r2), color);
Imgproc.line(image, new Point(c.x + r2, c.y - r2), new Point(c.x - r2, c.y + r2), color);
var color = chessboardColors[i % chessboardColors.length];
Imgproc.circle(image, c, r, color, thickness);
Imgproc.line(
image, new Point(c.x - r2, c.y - r2), new Point(c.x + r2, c.y + r2), color, thickness);
Imgproc.line(
image, new Point(c.x + r2, c.y - r2), new Point(c.x - r2, c.y + r2), color, thickness);
}
i++;
}
return null;

View File

@@ -0,0 +1,89 @@
/*
* Copyright (C) Photon Vision.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
package org.photonvision.vision.pipe.impl;
import java.util.ArrayList;
import java.util.List;
import org.photonvision.common.util.numbers.DoubleCouple;
import org.photonvision.vision.frame.FrameStaticProperties;
import org.photonvision.vision.pipe.CVPipe;
public class FilterObjectDetectionsPipe
extends CVPipe<
List<NeuralNetworkPipeResult>,
List<NeuralNetworkPipeResult>,
FilterObjectDetectionsPipe.FilterContoursParams> {
List<NeuralNetworkPipeResult> m_filteredContours = new ArrayList<>();
@Override
protected List<NeuralNetworkPipeResult> process(List<NeuralNetworkPipeResult> in) {
m_filteredContours.clear();
for (var contour : in) {
filterContour(contour);
}
return m_filteredContours;
}
private void filterContour(NeuralNetworkPipeResult contour) {
var boc = contour.box;
// Area filtering
double areaPercentage = boc.area() / params.getFrameStaticProperties().imageArea * 100.0;
double minAreaPercentage = params.getArea().getFirst();
double maxAreaPercentage = params.getArea().getSecond();
if (areaPercentage < minAreaPercentage || areaPercentage > maxAreaPercentage) return;
// Aspect ratio filtering; much simpler since always axis-aligned
double aspectRatio = boc.width / boc.height;
if (aspectRatio < params.getRatio().getFirst() || aspectRatio > params.getRatio().getSecond())
return;
m_filteredContours.add(contour);
}
public static class FilterContoursParams {
private final DoubleCouple m_area;
private final DoubleCouple m_ratio;
private final FrameStaticProperties m_frameStaticProperties;
public final boolean isLandscape;
public FilterContoursParams(
DoubleCouple area,
DoubleCouple ratio,
FrameStaticProperties camProperties,
boolean isLandscape) {
this.m_area = area;
this.m_ratio = ratio;
this.m_frameStaticProperties = camProperties;
this.isLandscape = isLandscape;
}
public DoubleCouple getArea() {
return m_area;
}
public DoubleCouple getRatio() {
return m_ratio;
}
public FrameStaticProperties getFrameStaticProperties() {
return m_frameStaticProperties;
}
}
}

View File

@@ -0,0 +1,32 @@
/*
* Copyright (C) Photon Vision.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
package org.photonvision.vision.pipe.impl;
import org.opencv.core.Rect2d;
public class NeuralNetworkPipeResult {
public NeuralNetworkPipeResult(Rect2d box2, Integer classIdx, Float confidence) {
box = box2;
this.classIdx = classIdx;
this.confidence = confidence;
}
public final int classIdx;
public final Rect2d box;
public final double confidence;
}

View File

@@ -0,0 +1,70 @@
/*
* Copyright (C) Photon Vision.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
package org.photonvision.vision.pipe.impl;
import java.util.List;
import org.photonvision.common.configuration.NeuralNetworkModelManager;
import org.photonvision.jni.RknnDetectorJNI.RknnObjectDetector;
import org.photonvision.vision.opencv.CVMat;
import org.photonvision.vision.opencv.Releasable;
import org.photonvision.vision.pipe.CVPipe;
public class RknnDetectionPipe
extends CVPipe<CVMat, List<NeuralNetworkPipeResult>, RknnDetectionPipe.RknnDetectionPipeParams>
implements Releasable {
private RknnObjectDetector detector;
public RknnDetectionPipe() {
// For now this is hard-coded to defaults. Should be refactored into set pipe params, though.
// And ideally a little wrapper helper for only changing native stuff on content change created.
this.detector =
new RknnObjectDetector(
NeuralNetworkModelManager.getInstance().getDefaultRknnModel().getAbsolutePath(),
NeuralNetworkModelManager.getInstance().getLabels(),
NeuralNetworkModelManager.getInstance().getModelVersion());
}
@Override
protected List<NeuralNetworkPipeResult> process(CVMat in) {
var frame = in.getMat();
// Make sure we don't get a weird empty frame
if (frame.empty()) {
return List.of();
}
return detector.detect(in, params.nms, params.confidence);
}
public static class RknnDetectionPipeParams {
public double confidence;
public double nms;
public int max_detections;
public RknnDetectionPipeParams() {}
}
public List<String> getClassNames() {
return detector.getClasses();
}
@Override
public void release() {
detector.release();
}
}

View File

@@ -42,6 +42,7 @@ public class SortContoursPipe
if (params.getSortMode() != ContourSortMode.Centermost) {
m_sortedContours.sort(params.getSortMode().getComparator());
} else {
// we need knowledge of camera properties to calculate this distance -- do it ourselves
m_sortedContours.sort(Comparator.comparingDouble(this::calcSquareCenterDistance));
}
}
@@ -50,10 +51,10 @@ public class SortContoursPipe
m_sortedContours.subList(0, Math.min(in.size(), params.getMaxTargets())));
}
private double calcSquareCenterDistance(PotentialTarget rect) {
private double calcSquareCenterDistance(PotentialTarget tgt) {
return Math.sqrt(
Math.pow(params.getCamProperties().centerX - rect.getMinAreaRect().center.x, 2)
+ Math.pow(params.getCamProperties().centerY - rect.getMinAreaRect().center.y, 2));
Math.pow(params.getCamProperties().centerX - tgt.getMinAreaRect().center.x, 2)
+ Math.pow(params.getCamProperties().centerY - tgt.getMinAreaRect().center.y, 2));
}
public static class SortContoursParams {

View File

@@ -21,9 +21,13 @@ import org.photonvision.vision.camera.QuirkyCamera;
import org.photonvision.vision.frame.Frame;
import org.photonvision.vision.frame.FrameStaticProperties;
import org.photonvision.vision.frame.FrameThresholdType;
import org.photonvision.vision.opencv.Releasable;
import org.photonvision.vision.pipeline.result.CVPipelineResult;
public abstract class CVPipeline<R extends CVPipelineResult, S extends CVPipelineSettings> {
public abstract class CVPipeline<R extends CVPipelineResult, S extends CVPipelineSettings>
implements Releasable {
static final int MAX_MULTI_TARGET_RESULTS = 10;
protected S settings;
protected FrameStaticProperties frameStaticProperties;
protected QuirkyCamera cameraQuirks;
@@ -75,4 +79,11 @@ public abstract class CVPipeline<R extends CVPipelineResult, S extends CVPipelin
return result;
}
/**
* Release any native memory associated with this pipeline. Called by pipelinemanager at pipeline
* switch. Stubbed out, but override if needed.
*/
@Override
public void release() {}
}

View File

@@ -32,7 +32,8 @@ import org.photonvision.vision.opencv.ImageRotationMode;
@JsonSubTypes.Type(value = ReflectivePipelineSettings.class),
@JsonSubTypes.Type(value = DriverModePipelineSettings.class),
@JsonSubTypes.Type(value = AprilTagPipelineSettings.class),
@JsonSubTypes.Type(value = ArucoPipelineSettings.class)
@JsonSubTypes.Type(value = ArucoPipelineSettings.class),
@JsonSubTypes.Type(value = ObjectDetectionPipelineSettings.class)
})
public class CVPipelineSettings implements Cloneable {
public int pipelineIndex = 0;

View File

@@ -109,7 +109,7 @@ public class ColoredShapePipeline
SortContoursPipe.SortContoursParams sortContoursParams =
new SortContoursPipe.SortContoursParams(
settings.contourSortMode,
settings.outputShowMultipleTargets ? 5 : 1,
settings.outputShowMultipleTargets ? MAX_MULTI_TARGET_RESULTS : 1,
frameStaticProperties); // TODO don't hardcode?
sortContoursPipe.setParams(sortContoursParams);

View File

@@ -0,0 +1,135 @@
/*
* Copyright (C) Photon Vision.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
package org.photonvision.vision.pipeline;
import java.util.List;
import java.util.stream.Collectors;
import org.photonvision.vision.frame.Frame;
import org.photonvision.vision.frame.FrameThresholdType;
import org.photonvision.vision.opencv.DualOffsetValues;
import org.photonvision.vision.pipe.CVPipe.CVPipeResult;
import org.photonvision.vision.pipe.impl.*;
import org.photonvision.vision.pipe.impl.RknnDetectionPipe.RknnDetectionPipeParams;
import org.photonvision.vision.pipeline.result.CVPipelineResult;
import org.photonvision.vision.target.PotentialTarget;
import org.photonvision.vision.target.TargetOrientation;
import org.photonvision.vision.target.TrackedTarget;
public class ObjectDetectionPipeline
extends CVPipeline<CVPipelineResult, ObjectDetectionPipelineSettings> {
private final CalculateFPSPipe calculateFPSPipe = new CalculateFPSPipe();
private final RknnDetectionPipe rknnPipe = new RknnDetectionPipe();
private final SortContoursPipe sortContoursPipe = new SortContoursPipe();
private final Collect2dTargetsPipe collect2dTargetsPipe = new Collect2dTargetsPipe();
private final FilterObjectDetectionsPipe filterContoursPipe = new FilterObjectDetectionsPipe();
private static final FrameThresholdType PROCESSING_TYPE = FrameThresholdType.NONE;
public ObjectDetectionPipeline() {
super(PROCESSING_TYPE);
settings = new ObjectDetectionPipelineSettings();
}
public ObjectDetectionPipeline(ObjectDetectionPipelineSettings settings) {
super(PROCESSING_TYPE);
this.settings = settings;
}
@Override
protected void setPipeParamsImpl() {
// this needs to be based off of the current backend selected!!
var params = new RknnDetectionPipeParams();
params.confidence = settings.confidence;
params.nms = settings.nms;
rknnPipe.setParams(params);
DualOffsetValues dualOffsetValues =
new DualOffsetValues(
settings.offsetDualPointA,
settings.offsetDualPointAArea,
settings.offsetDualPointB,
settings.offsetDualPointBArea);
SortContoursPipe.SortContoursParams sortContoursParams =
new SortContoursPipe.SortContoursParams(
settings.contourSortMode,
settings.outputShowMultipleTargets ? MAX_MULTI_TARGET_RESULTS : 1,
frameStaticProperties);
sortContoursPipe.setParams(sortContoursParams);
var filterContoursParams =
new FilterObjectDetectionsPipe.FilterContoursParams(
settings.contourArea,
settings.contourRatio,
frameStaticProperties,
settings.contourTargetOrientation == TargetOrientation.Landscape);
filterContoursPipe.setParams(filterContoursParams);
Collect2dTargetsPipe.Collect2dTargetsParams collect2dTargetsParams =
new Collect2dTargetsPipe.Collect2dTargetsParams(
settings.offsetRobotOffsetMode,
settings.offsetSinglePoint,
dualOffsetValues,
settings.contourTargetOffsetPointEdge,
settings.contourTargetOrientation,
frameStaticProperties);
collect2dTargetsPipe.setParams(collect2dTargetsParams);
}
@Override
protected CVPipelineResult process(Frame input_frame, ObjectDetectionPipelineSettings settings) {
long sumPipeNanosElapsed = 0;
// ***************** change based on backend ***********************
CVPipeResult<List<NeuralNetworkPipeResult>> rknnResult = rknnPipe.run(input_frame.colorImage);
sumPipeNanosElapsed += rknnResult.nanosElapsed;
List<NeuralNetworkPipeResult> targetList;
var names = rknnPipe.getClassNames();
input_frame.colorImage.getMat().copyTo(input_frame.processedImage.getMat());
// ***************** change based on backend ***********************
var filterContoursResult = filterContoursPipe.run(rknnResult.output);
sumPipeNanosElapsed += filterContoursResult.nanosElapsed;
CVPipeResult<List<PotentialTarget>> sortContoursResult =
sortContoursPipe.run(
filterContoursResult.output.stream()
.map(shape -> new PotentialTarget(shape))
.collect(Collectors.toList()));
sumPipeNanosElapsed += sortContoursResult.nanosElapsed;
CVPipeResult<List<TrackedTarget>> collect2dTargetsResult =
collect2dTargetsPipe.run(sortContoursResult.output);
sumPipeNanosElapsed += collect2dTargetsResult.nanosElapsed;
var fpsResult = calculateFPSPipe.run(null);
var fps = fpsResult.output;
return new CVPipelineResult(
sumPipeNanosElapsed, fps, collect2dTargetsResult.output, input_frame, names);
}
@Override
public void release() {
rknnPipe.release();
}
}

View File

@@ -0,0 +1,34 @@
/*
* Copyright (C) Photon Vision.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
package org.photonvision.vision.pipeline;
public class ObjectDetectionPipelineSettings extends AdvancedPipelineSettings {
public double confidence;
public double nms; // non maximal suppression
public ObjectDetectionPipelineSettings() {
super();
this.pipelineType = PipelineType.ObjectDetection; // TODO: FIX this
this.outputShowMultipleTargets = true;
cameraExposure = 20;
cameraAutoExposure = false;
ledMode = false;
confidence = .9;
nms = .45;
}
}

View File

@@ -17,6 +17,8 @@
package org.photonvision.vision.pipeline;
import org.photonvision.vision.pipe.impl.Calibrate3dPipeline;
@SuppressWarnings("rawtypes")
public enum PipelineType {
Calib3d(-2, Calibrate3dPipeline.class),
@@ -24,7 +26,8 @@ public enum PipelineType {
Reflective(0, ReflectivePipeline.class),
ColoredShape(1, ColoredShapePipeline.class),
AprilTag(2, AprilTagPipeline.class),
Aruco(3, ArucoPipeline.class);
Aruco(3, ArucoPipeline.class),
ObjectDetection(4, ObjectDetectionPipeline.class);
public final int baseIndex;
public final Class clazz;

View File

@@ -64,29 +64,6 @@ public class ReflectivePipeline extends CVPipeline<CVPipelineResult, ReflectiveP
settings.offsetDualPointB,
settings.offsetDualPointBArea);
// var rotateImageParams = new
// RotateImagePipe.RotateImageParams(settings.inputImageRotationMode);
// rotateImagePipe.setParams(rotateImageParams);
// if (cameraQuirks.hasQuirk(CameraQuirk.PiCam) && LibCameraJNI.isSupported()) {
// LibCameraJNI.setThresholds(
// settings.hsvHue.getFirst() / 180d,
// settings.hsvSaturation.getFirst() / 255d,
// settings.hsvValue.getFirst() / 255d,
// settings.hsvHue.getSecond() / 180d,
// settings.hsvSaturation.getSecond() / 255d,
// settings.hsvValue.getSecond() / 255d);
// // LibCameraJNI.setInvertHue(settings.hueInverted);
// LibCameraJNI.setRotation(settings.inputImageRotationMode.value);
// // LibCameraJNI.setShouldCopyColor(settings.inputShouldShow);
// } else {
// var hsvParams =
// new HSVPipe.HSVParams(
// settings.hsvHue, settings.hsvSaturation, settings.hsvValue,
// settings.hueInverted);
// hsvPipe.setParams(hsvParams);
// }
var findContoursParams = new FindContoursPipe.FindContoursParams();
findContoursPipe.setParams(findContoursParams);
@@ -113,7 +90,7 @@ public class ReflectivePipeline extends CVPipeline<CVPipelineResult, ReflectiveP
var sortContoursParams =
new SortContoursPipe.SortContoursParams(
settings.contourSortMode,
settings.outputShowMultipleTargets ? 8 : 1, // TODO don't hardcode?
settings.outputShowMultipleTargets ? MAX_MULTI_TARGET_RESULTS : 1,
frameStaticProperties);
sortContoursPipe.setParams(sortContoursParams);

View File

@@ -32,10 +32,20 @@ public class CVPipelineResult implements Releasable {
public final List<TrackedTarget> targets;
public final Frame inputAndOutputFrame;
public MultiTargetPNPResult multiTagResult;
public final List<String> objectDetectionClassNames;
public CVPipelineResult(
double processingNanos, double fps, List<TrackedTarget> targets, Frame inputFrame) {
this(processingNanos, fps, targets, new MultiTargetPNPResult(), inputFrame);
this(processingNanos, fps, targets, new MultiTargetPNPResult(), inputFrame, List.of());
}
public CVPipelineResult(
double processingNanos,
double fps,
List<TrackedTarget> targets,
Frame inputFrame,
List<String> classNames) {
this(processingNanos, fps, targets, new MultiTargetPNPResult(), inputFrame, classNames);
}
public CVPipelineResult(
@@ -44,10 +54,21 @@ public class CVPipelineResult implements Releasable {
List<TrackedTarget> targets,
MultiTargetPNPResult multiTagResult,
Frame inputFrame) {
this(processingNanos, fps, targets, multiTagResult, inputFrame, List.of());
}
public CVPipelineResult(
double processingNanos,
double fps,
List<TrackedTarget> targets,
MultiTargetPNPResult multiTagResult,
Frame inputFrame,
List<String> classNames) {
this.processingNanos = processingNanos;
this.fps = fps;
this.targets = targets != null ? targets : Collections.emptyList();
this.multiTagResult = multiTagResult;
this.objectDetectionClassNames = classNames;
this.inputAndOutputFrame = inputFrame;
}
@@ -57,7 +78,7 @@ public class CVPipelineResult implements Releasable {
double fps,
List<TrackedTarget> targets,
MultiTargetPNPResult multiTagResult) {
this(processingNanos, fps, targets, multiTagResult, null);
this(processingNanos, fps, targets, multiTagResult, null, List.of());
}
public boolean hasTargets() {

View File

@@ -27,6 +27,7 @@ import org.photonvision.common.dataflow.DataChangeService;
import org.photonvision.common.dataflow.events.OutgoingUIEvent;
import org.photonvision.common.logging.LogGroup;
import org.photonvision.common.logging.Logger;
import org.photonvision.vision.pipe.impl.Calibrate3dPipeline;
import org.photonvision.vision.pipeline.*;
@SuppressWarnings({"rawtypes", "unused"})
@@ -41,7 +42,7 @@ public class PipelineManager {
protected final DriverModePipeline driverModePipeline = new DriverModePipeline();
/** Index of the currently active pipeline. Defaults to 0. */
private int currentPipelineIndex = 0;
private int currentPipelineIndex = DRIVERMODE_INDEX;
/** The currently active pipeline. */
private CVPipeline currentUserPipeline = driverModePipeline;
@@ -188,6 +189,11 @@ public class PipelineManager {
return;
}
// Cleanup potential old native resources before swapping over
if (currentUserPipeline != null) {
currentUserPipeline.release();
}
currentPipelineIndex = newIndex;
if (newIndex >= 0) {
var desiredPipelineSettings = userPipelineSettings.get(currentPipelineIndex);
@@ -212,6 +218,11 @@ public class PipelineManager {
logger.debug("Creating Aruco Pipeline");
currentUserPipeline = new ArucoPipeline((ArucoPipelineSettings) desiredPipelineSettings);
break;
case ObjectDetection:
logger.debug("Creating ObjectDetection Pipeline");
currentUserPipeline =
new ObjectDetectionPipeline(
(ObjectDetectionPipelineSettings) desiredPipelineSettings);
default:
// Can be calib3d or drivermode, both of which are special cases
break;
@@ -313,6 +324,12 @@ public class PipelineManager {
added.pipelineNickname = nickname;
return added;
}
case ObjectDetection:
{
var added = new ObjectDetectionPipelineSettings();
added.pipelineNickname = nickname;
return added;
}
default:
{
logger.error("Got invalid pipeline type: " + type);

View File

@@ -26,6 +26,7 @@ import java.util.HashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.function.BiConsumer;
import java.util.stream.Collectors;
import org.opencv.core.Size;
import org.photonvision.common.configuration.CameraConfiguration;
import org.photonvision.common.configuration.ConfigManager;
@@ -536,7 +537,10 @@ public class VisionModule {
ret.outputStreamPort = this.outputStreamPort;
ret.inputStreamPort = this.inputStreamPort;
ret.calibrations = visionSource.getSettables().getConfiguration().calibrations;
ret.calibrations =
visionSource.getSettables().getConfiguration().calibrations.stream()
.map(CameraCalibrationCoefficients::cloneWithoutObservations)
.collect(Collectors.toList());
ret.isFovConfigurable =
!(ConfigManager.getInstance().getConfig().getHardwareConfig().hasPresetFOV()

View File

@@ -98,8 +98,7 @@ public class VisionRunner {
var pipelineResult = pipeline.run(frame, cameraQuirks);
pipelineResultConsumer.accept(pipelineResult);
} catch (Exception ex) {
logger.error("Exception on loop " + loopCount);
ex.printStackTrace();
logger.error("Exception on loop " + loopCount, ex);
}
loopCount++;

View File

@@ -21,7 +21,9 @@ import java.util.List;
import org.opencv.core.RotatedRect;
import org.photonvision.vision.opencv.CVShape;
import org.photonvision.vision.opencv.Contour;
import org.photonvision.vision.opencv.ContourShape;
import org.photonvision.vision.opencv.Releasable;
import org.photonvision.vision.pipe.impl.NeuralNetworkPipeResult;
public class PotentialTarget implements Releasable {
@@ -29,6 +31,10 @@ public class PotentialTarget implements Releasable {
public final List<Contour> m_subContours;
public final CVShape shape;
// additional metadata about object detections we need to keep around
public final double confidence;
public final int clsId;
public PotentialTarget(Contour inputContour) {
this(inputContour, List.of());
}
@@ -41,12 +47,26 @@ public class PotentialTarget implements Releasable {
m_mainContour = inputContour;
m_subContours = new ArrayList<>(subContours);
this.shape = shape;
this.clsId = -1;
this.confidence = -1;
}
public PotentialTarget(Contour inputContour, CVShape shape) {
this(inputContour, List.of(), shape);
}
public PotentialTarget(NeuralNetworkPipeResult det) {
this.shape = new CVShape(new Contour(det.box), ContourShape.Quadrilateral);
this.m_mainContour = this.shape.getContour();
m_subContours = List.of();
this.clsId = det.classIdx;
this.confidence = det.confidence;
}
public PotentialTarget(CVShape cvShape) {
this(cvShape.getContour(), cvShape);
}
public RotatedRect getMinAreaRect() {
return m_mainContour.getMinAreaRect();
}
@@ -61,7 +81,7 @@ public class PotentialTarget implements Releasable {
for (var sc : m_subContours) {
sc.release();
}
m_subContours.clear();
if (!m_subContours.isEmpty()) m_subContours.clear();
if (shape != null) shape.release();
}
}

View File

@@ -65,12 +65,18 @@ public class TrackedTarget implements Releasable {
private Mat m_cameraRelativeTvec, m_cameraRelativeRvec;
private int m_classId = -1;
private double m_confidence = -1;
public TrackedTarget(
PotentialTarget origTarget, TargetCalculationParameters params, CVShape shape) {
this.m_mainContour = origTarget.m_mainContour;
this.m_subContours = origTarget.m_subContours;
this.m_shape = shape;
calculateValues(params);
this.m_classId = origTarget.clsId;
this.m_confidence = origTarget.confidence;
}
public TrackedTarget(
@@ -154,6 +160,20 @@ public class TrackedTarget implements Releasable {
m_robotOffsetPoint = new Point();
}
/**
* @return Returns the confidence of the detection ranging from 0 - 1.
*/
public double getConfidence() {
return m_confidence;
}
/**
* @return O-indexed class index for the detected object.
*/
public double getClassID() {
return m_classId;
}
public TrackedTarget(
ArucoDetectionResult result,
AprilTagPoseEstimate tagPose,
@@ -388,6 +408,8 @@ public class TrackedTarget implements Releasable {
ret.put("skew", getSkew());
ret.put("area", getArea());
ret.put("ambiguity", getPoseAmbiguity());
ret.put("confidence", m_confidence);
ret.put("classId", m_classId);
var bestCameraToTarget3d = getBestCameraToTarget3d();
if (bestCameraToTarget3d != null) {

View File

@@ -44,6 +44,7 @@ import org.photonvision.vision.frame.FrameDivisor;
import org.photonvision.vision.frame.FrameStaticProperties;
import org.photonvision.vision.frame.FrameThresholdType;
import org.photonvision.vision.opencv.CVMat;
import org.photonvision.vision.pipe.impl.Calibrate3dPipeline;
public class Calibrate3dPipeTest {
@BeforeAll

View File

@@ -1,9 +1,3 @@
plugins {
id 'edu.wpi.first.WpilibTools' version '1.3.0'
}
apply plugin: "edu.wpi.first.NativeUtils"
import java.nio.file.Path
ext {
@@ -13,9 +7,125 @@ ext {
generatedHeaders = "src/generate/native/include"
}
apply from: "${rootDir}/shared/javacpp/setupBuild.gradle"
apply plugin: 'cpp'
apply plugin: 'google-test-test-suite'
apply plugin: 'edu.wpi.first.NativeUtils'
apply from: "${rootDir}/shared/config.gradle"
apply from: "${rootDir}/shared/javacommon.gradle"
apply from: "${rootDir}/versioningHelper.gradle"
nativeUtils {
exportsConfigs {
"${nativeName}" {}
}
}
model {
components {
"${nativeName}"(NativeLibrarySpec) {
sources {
cpp {
source {
srcDirs 'src/main/native/cpp', "$buildDir/generated/source/proto/main/cpp"
include '**/*.cpp', '**/*.cc'
}
exportedHeaders {
srcDirs 'src/main/native/include', "$buildDir/generated/source/proto/main/cpp"
if (project.hasProperty('generatedHeaders')) {
srcDir generatedHeaders
}
include "**/*.h"
}
}
}
binaries.all {
it.tasks.withType(CppCompile) {
it.dependsOn generateProto
}
if(project.hasProperty('includePhotonTargeting')) {
lib project: ':photon-targeting', library: 'photontargeting', linkage: 'shared'
}
}
nativeUtils.useRequiredLibrary(it, "wpilib_shared")
nativeUtils.useRequiredLibrary(it, "apriltag_shared")
nativeUtils.useRequiredLibrary(it, "opencv_shared")
}
}
testSuites {
"${nativeName}Test"(GoogleTestTestSuiteSpec) {
for(NativeComponentSpec c : $.components) {
if (c.name == nativeName) {
testing c
break
}
}
sources {
cpp {
source {
srcDirs 'src/test/native/cpp'
include '**/*.cpp'
}
exportedHeaders {
srcDirs 'src/test/native/include', "$buildDir/generated/source/proto/main/cpp"
}
}
}
binaries.all {
it.tasks.withType(CppCompile) {
it.dependsOn generateProto
}
if(project.hasProperty('includePhotonTargeting')) {
lib project: ':photon-targeting', library: 'photontargeting', linkage: 'shared'
}
}
nativeUtils.useRequiredLibrary(it, "cscore_shared")
nativeUtils.useRequiredLibrary(it, "cameraserver_shared")
nativeUtils.useRequiredLibrary(it, "wpilib_executable_shared")
nativeUtils.useRequiredLibrary(it, "googletest_static")
nativeUtils.useRequiredLibrary(it, "apriltag_shared")
nativeUtils.useRequiredLibrary(it, "opencv_shared")
}
}
tasks {
def c = $.testSuites
project.tasks.create('runCpp', Exec) {
description = "Run the photon-lib executable"
def found = false
def systemArch = getCurrentArch()
c.each {
if (it in GoogleTestTestSuiteSpec && it.name == "${nativeName}Test") {
it.binaries.each {
if (!found) {
def arch = it.targetPlatform.name
if (arch == systemArch) {
dependsOn it.tasks.install
commandLine it.tasks.install.runScriptFile.get().asFile.toString()
def filePath = it.tasks.install.installDirectory.get().toString() + File.separatorChar + 'lib'
test.dependsOn it.tasks.install
test.systemProperty 'java.library.path', filePath
test.environment 'LD_LIBRARY_PATH', filePath
test.environment 'DYLD_LIBRARY_PATH', filePath
test.workingDir filePath
found = true
}
}
}
}
}
}
}
}
apply from: "${rootDir}/shared/javacpp/publish.gradle"
// Include the version file in the distributed sources
cppHeadersZip {
from('src/generate/native/include') {

View File

@@ -0,0 +1,26 @@
from dataclasses import dataclass
from typing import TYPE_CHECKING
from wpimath.geometry import Pose3d
from .photonTrackedTarget import PhotonTrackedTarget
if TYPE_CHECKING:
from .photonPoseEstimator import PoseStrategy
@dataclass
class EstimatedRobotPose:
"""An estimated pose based on pipeline result"""
estimatedPose: Pose3d
"""The estimated pose"""
timestampSeconds: float
"""The estimated time the frame used to derive the robot pose was taken"""
targetsUsed: list[PhotonTrackedTarget]
"""A list of the targets used to compute this pose"""
strategy: "PoseStrategy"
"""The strategy actually used to produce this pose"""

View File

@@ -4,7 +4,7 @@ import wpilib
class Packet:
def __init__(self, data: list[int]):
def __init__(self, data: bytes):
"""
* Constructs an empty packet.
*
@@ -30,7 +30,7 @@ class Packet:
matches the version of photonlib running in the robot code.
"""
def _getNextByte(self) -> int:
def _getNextByteAsInt(self) -> int:
retVal = 0x00
if not self.outOfBytes:
@@ -43,7 +43,7 @@ class Packet:
return retVal
def getData(self) -> list[int]:
def getData(self) -> bytes:
"""
* Returns the packet data.
*
@@ -51,7 +51,7 @@ class Packet:
"""
return self.packetData
def setData(self, data: list[int]):
def setData(self, data: bytes):
"""
* Sets the packet data.
*
@@ -65,7 +65,7 @@ class Packet:
# Read ints in from the data buffer
intList = []
for _ in range(numBytes):
intList.append(self._getNextByte())
intList.append(self._getNextByteAsInt())
# Interpret the bytes as a floating point number
value = struct.unpack(unpackFormat, bytes(intList))[0]

View File

@@ -4,7 +4,7 @@ from wpilib import Timer
import wpilib
from photonlibpy.packet import Packet
from photonlibpy.photonPipelineResult import PhotonPipelineResult
from photonlibpy.version import PHOTONVISION_VERSION, PHOTONLIB_VERSION
from photonlibpy.version import PHOTONVISION_VERSION, PHOTONLIB_VERSION # type: ignore[import-untyped]
class VisionLEDMode(Enum):
@@ -86,10 +86,11 @@ class PhotonCamera:
if len(byteList) < 1:
return retVal
else:
retVal.populateFromPacket(Packet(byteList))
pkt = Packet(byteList)
retVal.populateFromPacket(pkt)
# NT4 allows us to correct the timestamp based on when the message was sent
retVal.setTimestampSeconds(
timestamp / 1e-6 - retVal.getLatencyMillis() / 1e-3
timestamp / 1e6 - retVal.getLatencyMillis() / 1e3
)
return retVal

View File

@@ -17,7 +17,6 @@ class PhotonPipelineResult:
self.latencyMillis = packet.decodeDouble()
targetCount = packet.decode8()
print(f"targetCount = {targetCount}")
for _ in range(targetCount):
target = PhotonTrackedTarget()
target.createFromPacket(packet)
@@ -39,3 +38,6 @@ class PhotonPipelineResult:
def getTargets(self) -> list[PhotonTrackedTarget]:
return self.targets
def hasTargets(self) -> bool:
return len(self.targets) > 0

View File

@@ -0,0 +1,321 @@
import enum
from typing import Optional
import wpilib
from robotpy_apriltag import AprilTagFieldLayout
from wpimath.geometry import Transform3d, Pose3d, Pose2d
from .photonPipelineResult import PhotonPipelineResult
from .photonCamera import PhotonCamera
from .estimatedRobotPose import EstimatedRobotPose
class PoseStrategy(enum.Enum):
"""
Position estimation strategies that can be used by the PhotonPoseEstimator class.
"""
LOWEST_AMBIGUITY = enum.auto()
"""Choose the Pose with the lowest ambiguity."""
CLOSEST_TO_CAMERA_HEIGHT = enum.auto()
"""Choose the Pose which is closest to the camera height."""
CLOSEST_TO_REFERENCE_POSE = enum.auto()
"""Choose the Pose which is closest to a set Reference position."""
CLOSEST_TO_LAST_POSE = enum.auto()
"""Choose the Pose which is closest to the last pose calculated."""
AVERAGE_BEST_TARGETS = enum.auto()
"""Return the average of the best target poses using ambiguity as weight."""
MULTI_TAG_PNP_ON_COPROCESSOR = enum.auto()
"""
Use all visible tags to compute a single pose estimate on coprocessor.
This option needs to be enabled on the PhotonVision web UI as well.
"""
MULTI_TAG_PNP_ON_RIO = enum.auto()
"""
Use all visible tags to compute a single pose estimate.
This runs on the RoboRIO, and can take a lot of time.
"""
class PhotonPoseEstimator:
"""
The PhotonPoseEstimator class filters or combines readings from all the AprilTags visible at a
given timestamp on the field to produce a single robot in field pose, using the strategy set
below. Example usage can be found in our apriltagExample example project.
"""
def __init__(
self,
fieldTags: AprilTagFieldLayout,
strategy: PoseStrategy,
camera: PhotonCamera,
robotToCamera: Transform3d,
):
"""Create a new PhotonPoseEstimator.
:param fieldTags: A WPILib AprilTagFieldLayout linking AprilTag IDs to Pose3d objects
with respect to the FIRST field using the Field Coordinate System.
Note that setting the origin of this layout object will affect the
results from this class.
:param strategy: The strategy it should use to determine the best pose.
:param camera: PhotonCamera
:param robotToCamera: Transform3d from the center of the robot to the camera mount position (i.e.,
robot ➔ camera) in the Robot Coordinate System.
"""
self._fieldTags = fieldTags
self._primaryStrategy = strategy
self._camera = camera
self.robotToCamera = robotToCamera
self._multiTagFallbackStrategy = PoseStrategy.LOWEST_AMBIGUITY
self._reportedErrors: set[int] = set()
self._poseCacheTimestampSeconds = -1.0
self._lastPose: Optional[Pose3d] = None
self._referencePose: Optional[Pose3d] = None
# TODO: Implement HAL reporting
@property
def fieldTags(self) -> AprilTagFieldLayout:
"""Get the AprilTagFieldLayout being used by the PositionEstimator.
Note: Setting the origin of this layout will affect the results from this class.
:returns: the AprilTagFieldLayout
"""
return self._fieldTags
@fieldTags.setter
def fieldTags(self, fieldTags: AprilTagFieldLayout):
"""Set the AprilTagFieldLayout being used by the PositionEstimator.
Note: Setting the origin of this layout will affect the results from this class.
:param fieldTags: the AprilTagFieldLayout
"""
self._checkUpdate(self._fieldTags, fieldTags)
self._fieldTags = fieldTags
@property
def primaryStrategy(self) -> PoseStrategy:
"""Get the Position Estimation Strategy being used by the Position Estimator.
:returns: the strategy
"""
return self._primaryStrategy
@primaryStrategy.setter
def primaryStrategy(self, strategy: PoseStrategy):
"""Set the Position Estimation Strategy used by the Position Estimator.
:param strategy: the strategy to set
"""
self._checkUpdate(self._primaryStrategy, strategy)
self._primaryStrategy = strategy
@property
def multiTagFallbackStrategy(self) -> PoseStrategy:
return self._multiTagFallbackStrategy
@multiTagFallbackStrategy.setter
def multiTagFallbackStrategy(self, strategy: PoseStrategy):
"""Set the Position Estimation Strategy used in multi-tag mode when only one tag can be seen. Must
NOT be MULTI_TAG_PNP
:param strategy: the strategy to set
"""
self._checkUpdate(self._multiTagFallbackStrategy, strategy)
if (
strategy is PoseStrategy.MULTI_TAG_PNP_ON_COPROCESSOR
or strategy is PoseStrategy.MULTI_TAG_PNP_ON_RIO
):
wpilib.reportWarning(
"Fallback cannot be set to MULTI_TAG_PNP! Setting to lowest ambiguity",
False,
)
strategy = PoseStrategy.LOWEST_AMBIGUITY
self._multiTagFallbackStrategy = strategy
@property
def referencePose(self) -> Optional[Pose3d]:
"""Return the reference position that is being used by the estimator.
:returns: the referencePose
"""
return self._referencePose
@referencePose.setter
def referencePose(self, referencePose: Pose3d | Pose2d):
"""Update the stored reference pose for use when using the **CLOSEST_TO_REFERENCE_POSE**
strategy.
:param referencePose: the referencePose to set
"""
if isinstance(referencePose, Pose2d):
referencePose = Pose3d(referencePose)
self._checkUpdate(self._referencePose, referencePose)
self._referencePose = referencePose
@property
def lastPose(self) -> Optional[Pose3d]:
return self._lastPose
@lastPose.setter
def lastPose(self, lastPose: Pose3d | Pose2d):
"""Update the stored last pose. Useful for setting the initial estimate when using the
**CLOSEST_TO_LAST_POSE** strategy.
:param lastPose: the lastPose to set
"""
if isinstance(lastPose, Pose2d):
lastPose = Pose3d(lastPose)
self._checkUpdate(self._lastPose, lastPose)
self._lastPose = lastPose
def _invalidatePoseCache(self) -> None:
self._poseCacheTimestampSeconds = -1.0
def _checkUpdate(self, oldObj, newObj) -> None:
if oldObj != newObj and oldObj is not None and oldObj is not newObj:
self._invalidatePoseCache()
def update(
self, cameraResult: Optional[PhotonPipelineResult] = None
) -> Optional[EstimatedRobotPose]:
"""
Updates the estimated position of the robot. Returns empty if:
- The timestamp of the provided pipeline result is the same as in the previous call to
``update()``.
- No targets were found in the pipeline results.
:param cameraResult: The latest pipeline result from the camera
:returns: an :class:`EstimatedRobotPose` with an estimated pose, timestamp, and targets used to
create the estimate.
"""
if not cameraResult:
if not self._camera:
wpilib.reportError("[PhotonPoseEstimator] Missing camera!", False)
return None
cameraResult = self._camera.getLatestResult()
if cameraResult.timestampSec < 0:
return None
# If the pose cache timestamp was set, and the result is from the same
# timestamp, return an
# empty result
if (
self._poseCacheTimestampSeconds > 0.0
and abs(self._poseCacheTimestampSeconds - cameraResult.timestampSec) < 1e-6
):
return None
# Remember the timestamp of the current result used
self._poseCacheTimestampSeconds = cameraResult.timestampSec
# If no targets seen, trivial case -- return empty result
if not cameraResult.targets:
return None
return self._update(cameraResult, self._primaryStrategy)
def _update(
self, cameraResult: PhotonPipelineResult, strat: PoseStrategy
) -> Optional[EstimatedRobotPose]:
if strat is PoseStrategy.LOWEST_AMBIGUITY:
estimatedPose = self._lowestAmbiguityStrategy(cameraResult)
elif strat is PoseStrategy.MULTI_TAG_PNP_ON_COPROCESSOR:
estimatedPose = self._multiTagOnCoprocStrategy(cameraResult)
else:
wpilib.reportError(
"[PhotonPoseEstimator] Unknown Position Estimation Strategy!", False
)
return None
if not estimatedPose:
self._lastPose = None
return estimatedPose
def _multiTagOnCoprocStrategy(
self, result: PhotonPipelineResult
) -> Optional[EstimatedRobotPose]:
if result.multiTagResult.estimatedPose.isPresent:
best_tf = result.multiTagResult.estimatedPose.best
best = (
Pose3d()
.transformBy(best_tf) # field-to-camera
.relativeTo(self._fieldTags.getOrigin())
.transformBy(self.robotToCamera.inverse()) # field-to-robot
)
return EstimatedRobotPose(
best,
result.timestampSec,
result.targets,
PoseStrategy.MULTI_TAG_PNP_ON_COPROCESSOR,
)
else:
return self._update(result, self._multiTagFallbackStrategy)
def _lowestAmbiguityStrategy(
self, result: PhotonPipelineResult
) -> Optional[EstimatedRobotPose]:
"""
Return the estimated position of the robot with the lowest position ambiguity from a List of
pipeline results.
:param result: pipeline result
:returns: the estimated position of the robot in the FCS and the estimated timestamp of this
estimation.
"""
lowestAmbiguityTarget = None
lowestAmbiguityScore = 10.0
for target in result.targets:
targetPoseAmbiguity = target.poseAmbiguity
# Make sure the target is a Fiducial target.
if targetPoseAmbiguity != -1 and targetPoseAmbiguity < lowestAmbiguityScore:
lowestAmbiguityScore = targetPoseAmbiguity
lowestAmbiguityTarget = target
# Although there are confirmed to be targets, none of them may be fiducial
# targets.
if not lowestAmbiguityTarget:
return None
targetFiducialId = lowestAmbiguityTarget.fiducialId
targetPosition = self._fieldTags.getTagPose(targetFiducialId)
if not targetPosition:
self._reportFiducialPoseError(targetFiducialId)
return None
return EstimatedRobotPose(
targetPosition.transformBy(
lowestAmbiguityTarget.getBestCameraToTarget().inverse()
).transformBy(self.robotToCamera.inverse()),
result.timestampSec,
result.targets,
PoseStrategy.LOWEST_AMBIGUITY,
)
def _reportFiducialPoseError(self, fiducialId: int) -> None:
if fiducialId not in self._reportedErrors:
wpilib.reportError(
f"[PhotonPoseEstimator] Tried to get pose of unknown AprilTag: {fiducialId}",
False,
)
self._reportedErrors.add(fiducialId)

View File

@@ -16,10 +16,24 @@ m = re.search(
# which should be PEP440 compliant
if m:
versionString = m.group(0)
prefix = m.group(1)
maturity = m.group(2)
suffix = m.group(3).replace(".", "")
versionString = f"{prefix}.{maturity}.{suffix}"
# Hack -- for strings like v2024.1.1, do NOT add matruity/suffix
if len(m.group(2)) > 0:
print("using beta group matcher")
prefix = m.group(1)
maturity = m.group(2)
suffix = m.group(3).replace(".", "")
versionString = f"{prefix}.{maturity}.{suffix}"
else:
split = gitDescribeResult.split("-")
if len(split) == 3:
year, commits, sha = split
# Chop off leading v from "v2024.1.2", and use "post" for commits to master since
versionString = f"{year[1:]}post{commits}"
print("using dev release " + versionString)
else:
year = gitDescribeResult
versionString = year[1:]
print("using full release " + versionString)
else:
@@ -46,6 +60,7 @@ setup(
install_requires=[
"wpilib<2025,>=2024.0.0b2",
"robotpy-wpimath<2025,>=2024.0.0b2",
"robotpy-apriltag<2025,>=2024.0.0b2",
"pyntcore<2025,>=2024.0.0b2",
],
description=descriptionStr,

View File

@@ -0,0 +1,243 @@
from photonlibpy.multiTargetPNPResult import MultiTargetPNPResult, PNPResult
from photonlibpy.photonPipelineResult import PhotonPipelineResult
from photonlibpy.photonPoseEstimator import PhotonPoseEstimator, PoseStrategy
from photonlibpy.photonTrackedTarget import PhotonTrackedTarget, TargetCorner
from robotpy_apriltag import AprilTag, AprilTagFieldLayout
from wpimath.geometry import Pose3d, Rotation3d, Transform3d, Translation3d
class PhotonCameraInjector:
result: PhotonPipelineResult
def getLatestResult(self) -> PhotonPipelineResult:
return self.result
def setupCommon() -> AprilTagFieldLayout:
tagList = []
tagPoses = (
Pose3d(3, 3, 3, Rotation3d()),
Pose3d(5, 5, 5, Rotation3d()),
)
for id_, pose in enumerate(tagPoses):
aprilTag = AprilTag()
aprilTag.ID = id_
aprilTag.pose = pose
tagList.append(aprilTag)
fieldLength = 54 / 3.281 # 54 ft -> meters
fieldWidth = 27 / 3.281 # 24 ft -> meters
return AprilTagFieldLayout(tagList, fieldLength, fieldWidth)
def test_lowestAmbiguityStrategy():
aprilTags = setupCommon()
cameraOne = PhotonCameraInjector()
cameraOne.result = PhotonPipelineResult(
2,
11,
[
PhotonTrackedTarget(
3.0,
-4.0,
9.0,
4.0,
0,
Transform3d(Translation3d(1, 2, 3), Rotation3d(1, 2, 3)),
Transform3d(Translation3d(1, 2, 3), Rotation3d(1, 2, 3)),
[
TargetCorner(1, 2),
TargetCorner(3, 4),
TargetCorner(5, 6),
TargetCorner(7, 8),
],
[
TargetCorner(1, 2),
TargetCorner(3, 4),
TargetCorner(5, 6),
TargetCorner(7, 8),
],
0.7,
),
PhotonTrackedTarget(
3.0,
-4.0,
9.1,
6.7,
1,
Transform3d(Translation3d(4, 2, 3), Rotation3d(0, 0, 0)),
Transform3d(Translation3d(4, 2, 3), Rotation3d(1, 5, 3)),
[
TargetCorner(1, 2),
TargetCorner(3, 4),
TargetCorner(5, 6),
TargetCorner(7, 8),
],
[
TargetCorner(1, 2),
TargetCorner(3, 4),
TargetCorner(5, 6),
TargetCorner(7, 8),
],
0.3,
),
PhotonTrackedTarget(
9.0,
-2.0,
19.0,
3.0,
0,
Transform3d(Translation3d(1, 2, 3), Rotation3d(1, 2, 3)),
Transform3d(Translation3d(1, 2, 3), Rotation3d(1, 2, 3)),
[
TargetCorner(1, 2),
TargetCorner(3, 4),
TargetCorner(5, 6),
TargetCorner(7, 8),
],
[
TargetCorner(1, 2),
TargetCorner(3, 4),
TargetCorner(5, 6),
TargetCorner(7, 8),
],
0.4,
),
],
)
estimator = PhotonPoseEstimator(
aprilTags, PoseStrategy.LOWEST_AMBIGUITY, cameraOne, Transform3d()
)
estimatedPose = estimator.update()
pose = estimatedPose.estimatedPose
assertEquals(11, estimatedPose.timestampSeconds)
assertEquals(1, pose.x, 0.01)
assertEquals(3, pose.y, 0.01)
assertEquals(2, pose.z, 0.01)
def test_multiTagOnCoprocStrategy():
cameraOne = PhotonCameraInjector()
cameraOne.result = PhotonPipelineResult(
2,
11,
# There needs to be at least one target present for pose estimation to work
# Doesn't matter which/how many targets for this test
[
PhotonTrackedTarget(
3.0,
-4.0,
9.0,
4.0,
0,
Transform3d(Translation3d(1, 2, 3), Rotation3d(1, 2, 3)),
Transform3d(Translation3d(1, 2, 3), Rotation3d(1, 2, 3)),
[
TargetCorner(1, 2),
TargetCorner(3, 4),
TargetCorner(5, 6),
TargetCorner(7, 8),
],
[
TargetCorner(1, 2),
TargetCorner(3, 4),
TargetCorner(5, 6),
TargetCorner(7, 8),
],
0.7,
)
],
multiTagResult=MultiTargetPNPResult(
PNPResult(True, Transform3d(1, 3, 2, Rotation3d()))
),
)
estimator = PhotonPoseEstimator(
AprilTagFieldLayout(),
PoseStrategy.MULTI_TAG_PNP_ON_COPROCESSOR,
cameraOne,
Transform3d(),
)
estimatedPose = estimator.update()
pose = estimatedPose.estimatedPose
assertEquals(11, estimatedPose.timestampSeconds)
assertEquals(1, pose.x, 0.01)
assertEquals(3, pose.y, 0.01)
assertEquals(2, pose.z, 0.01)
def test_cacheIsInvalidated():
aprilTags = setupCommon()
cameraOne = PhotonCameraInjector()
result = PhotonPipelineResult(
2,
20,
[
PhotonTrackedTarget(
3.0,
-4.0,
9.0,
4.0,
0,
Transform3d(Translation3d(1, 2, 3), Rotation3d(1, 2, 3)),
Transform3d(Translation3d(1, 2, 3), Rotation3d(1, 2, 3)),
[
TargetCorner(1, 2),
TargetCorner(3, 4),
TargetCorner(5, 6),
TargetCorner(7, 8),
],
[
TargetCorner(1, 2),
TargetCorner(3, 4),
TargetCorner(5, 6),
TargetCorner(7, 8),
],
0.7,
)
],
)
estimator = PhotonPoseEstimator(
aprilTags, PoseStrategy.LOWEST_AMBIGUITY, cameraOne, Transform3d()
)
# Empty result, expect empty result
cameraOne.result = PhotonPipelineResult(timestampSec=1)
estimatedPose = estimator.update()
assert estimatedPose is None
# Set actual result
cameraOne.result = result
estimatedPose = estimator.update()
assert estimatedPose is not None
assertEquals(20, estimatedPose.timestampSeconds, 0.01)
assertEquals(20, estimator._poseCacheTimestampSeconds)
# And again -- pose cache should mean this is empty
cameraOne.result = result
estimatedPose = estimator.update()
assert estimatedPose is None
# Expect the old timestamp to still be here
assertEquals(20, estimator._poseCacheTimestampSeconds)
# Set new field layout -- right after, the pose cache timestamp should be -1
estimator.fieldTags = AprilTagFieldLayout([AprilTag()], 0, 0)
assertEquals(-1, estimator._poseCacheTimestampSeconds)
# Update should cache the current timestamp (20) again
cameraOne.result = result
estimatedPose = estimator.update()
assertEquals(20, estimatedPose.timestampSeconds, 0.01)
assertEquals(20, estimator._poseCacheTimestampSeconds)
def assertEquals(expected, actual, epsilon=0.0):
assert abs(expected - actual) <= epsilon

View File

@@ -8,7 +8,7 @@
"https://maven.photonvision.org/repository/internal",
"https://maven.photonvision.org/repository/snapshots"
],
"jsonUrl": "https://maven.photonvision.org/repository/internal/org/photonvision/PhotonLib-json/1.0/PhotonLib-json-1.0.json",
"jsonUrl": "https://maven.photonvision.org/repository/internal/org/photonvision/photonlib-json/1.0/photonlib-json-1.0.json",
"jniDependencies": [],
"cppDependencies": [
{

View File

@@ -408,8 +408,8 @@ public class PhotonPoseEstimator {
return Optional.empty();
}
if (estimatedPose.isEmpty()) {
lastPose = null;
if (estimatedPose.isPresent()) {
lastPose = estimatedPose.get().estimatedPose;
}
return estimatedPose;

View File

@@ -186,6 +186,9 @@ std::optional<EstimatedRobotPose> PhotonPoseEstimator::Update(
ret = std::nullopt;
}
if (ret) {
lastPose = ret.value().estimatedPose;
}
return ret;
}

View File

@@ -435,7 +435,7 @@ class PhotonCameraSim {
double minTargetAreaPercent;
frc::AprilTagFieldLayout tagLayout{
frc::LoadAprilTagLayoutField(frc::AprilTagField::k2023ChargedUp)};
frc::LoadAprilTagLayoutField(frc::AprilTagField::k2024Crescendo)};
cs::CvSource videoSimRaw;
cv::Mat videoSimFrameRaw{};

View File

@@ -26,31 +26,23 @@ package org.photonvision;
import static org.junit.jupiter.api.Assertions.*;
import edu.wpi.first.apriltag.jni.AprilTagJNI;
import edu.wpi.first.cscore.CameraServerCvJNI;
import edu.wpi.first.cscore.CameraServerJNI;
import edu.wpi.first.hal.JNIWrapper;
import edu.wpi.first.math.MathUtil;
import edu.wpi.first.math.geometry.Pose3d;
import edu.wpi.first.math.geometry.Rotation2d;
import edu.wpi.first.math.geometry.Rotation3d;
import edu.wpi.first.math.geometry.Transform3d;
import edu.wpi.first.math.geometry.Translation3d;
import edu.wpi.first.net.WPINetJNI;
import edu.wpi.first.networktables.NetworkTableInstance;
import edu.wpi.first.networktables.NetworkTablesJNI;
import edu.wpi.first.util.CombinedRuntimeLoader;
import edu.wpi.first.util.WPIUtilJNI;
import java.io.IOException;
import java.util.List;
import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.Test;
import org.opencv.core.Core;
import org.photonvision.estimation.CameraTargetRelation;
import org.photonvision.estimation.OpenCVHelp;
import org.photonvision.estimation.RotTrlTransform3d;
import org.photonvision.estimation.TargetModel;
import org.photonvision.simulation.SimCameraProperties;
import org.photonvision.simulation.VisionSystemSim;
import org.photonvision.simulation.VisionTargetSim;
public class OpenCVTest {
@@ -84,28 +76,8 @@ public class OpenCVTest {
private static final SimCameraProperties prop = new SimCameraProperties();
@BeforeAll
public static void setUp() {
JNIWrapper.Helper.setExtractOnStaticLoad(false);
WPIUtilJNI.Helper.setExtractOnStaticLoad(false);
NetworkTablesJNI.Helper.setExtractOnStaticLoad(false);
WPINetJNI.Helper.setExtractOnStaticLoad(false);
CameraServerJNI.Helper.setExtractOnStaticLoad(false);
CameraServerCvJNI.Helper.setExtractOnStaticLoad(false);
AprilTagJNI.Helper.setExtractOnStaticLoad(false);
try {
CombinedRuntimeLoader.loadLibraries(
VisionSystemSim.class,
"wpiutiljni",
"ntcorejni",
"wpinetjni",
"wpiHaljni",
Core.NATIVE_LIBRARY_NAME,
"cscorejni",
"apriltagjni");
} catch (Exception e) {
e.printStackTrace();
}
public static void setUp() throws IOException {
CameraServerCvJNI.forceLoad();
// NT live for debug purposes
NetworkTableInstance.getDefault().startServer();

View File

@@ -30,17 +30,11 @@ import static org.junit.jupiter.api.Assertions.assertTrue;
import edu.wpi.first.apriltag.AprilTag;
import edu.wpi.first.apriltag.AprilTagFieldLayout;
import edu.wpi.first.hal.JNIWrapper;
import edu.wpi.first.math.geometry.Pose3d;
import edu.wpi.first.math.geometry.Rotation3d;
import edu.wpi.first.math.geometry.Transform3d;
import edu.wpi.first.math.geometry.Translation3d;
import edu.wpi.first.math.util.Units;
import edu.wpi.first.net.WPINetJNI;
import edu.wpi.first.networktables.NetworkTablesJNI;
import edu.wpi.first.util.CombinedRuntimeLoader;
import edu.wpi.first.util.WPIUtilJNI;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Optional;
@@ -56,19 +50,6 @@ class PhotonPoseEstimatorTest {
@BeforeAll
public static void init() {
JNIWrapper.Helper.setExtractOnStaticLoad(false);
WPIUtilJNI.Helper.setExtractOnStaticLoad(false);
NetworkTablesJNI.Helper.setExtractOnStaticLoad(false);
WPINetJNI.Helper.setExtractOnStaticLoad(false);
try {
CombinedRuntimeLoader.loadLibraries(
PhotonPoseEstimatorTest.class, "wpiutiljni", "ntcorejni", "wpinetjni", "wpiHaljni");
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
List<AprilTag> tagList = new ArrayList<>(2);
tagList.add(new AprilTag(0, new Pose3d(3, 3, 3, new Rotation3d())));
tagList.add(new AprilTag(1, new Pose3d(5, 5, 5, new Rotation3d())));

View File

@@ -30,10 +30,6 @@ import static org.junit.jupiter.api.Assertions.assertTrue;
import edu.wpi.first.apriltag.AprilTag;
import edu.wpi.first.apriltag.AprilTagFieldLayout;
import edu.wpi.first.apriltag.jni.AprilTagJNI;
import edu.wpi.first.cscore.CameraServerCvJNI;
import edu.wpi.first.cscore.CameraServerJNI;
import edu.wpi.first.hal.JNIWrapper;
import edu.wpi.first.math.geometry.Pose2d;
import edu.wpi.first.math.geometry.Pose3d;
import edu.wpi.first.math.geometry.Rotation2d;
@@ -42,11 +38,7 @@ import edu.wpi.first.math.geometry.Transform3d;
import edu.wpi.first.math.geometry.Translation2d;
import edu.wpi.first.math.geometry.Translation3d;
import edu.wpi.first.math.util.Units;
import edu.wpi.first.net.WPINetJNI;
import edu.wpi.first.networktables.NetworkTableInstance;
import edu.wpi.first.networktables.NetworkTablesJNI;
import edu.wpi.first.util.CombinedRuntimeLoader;
import edu.wpi.first.util.WPIUtilJNI;
import java.util.ArrayList;
import java.util.List;
import java.util.stream.Stream;
@@ -58,7 +50,6 @@ import org.junit.jupiter.params.ParameterizedTest;
import org.junit.jupiter.params.provider.Arguments;
import org.junit.jupiter.params.provider.MethodSource;
import org.junit.jupiter.params.provider.ValueSource;
import org.opencv.core.Core;
import org.photonvision.estimation.TargetModel;
import org.photonvision.estimation.VisionEstimation;
import org.photonvision.simulation.PhotonCameraSim;
@@ -85,28 +76,6 @@ class VisionSystemSimTest {
@BeforeAll
public static void setUp() {
JNIWrapper.Helper.setExtractOnStaticLoad(false);
WPIUtilJNI.Helper.setExtractOnStaticLoad(false);
NetworkTablesJNI.Helper.setExtractOnStaticLoad(false);
WPINetJNI.Helper.setExtractOnStaticLoad(false);
CameraServerJNI.Helper.setExtractOnStaticLoad(false);
CameraServerCvJNI.Helper.setExtractOnStaticLoad(false);
AprilTagJNI.Helper.setExtractOnStaticLoad(false);
try {
CombinedRuntimeLoader.loadLibraries(
VisionSystemSim.class,
"wpiutiljni",
"ntcorejni",
"wpinetjni",
"wpiHaljni",
Core.NATIVE_LIBRARY_NAME,
"cscorejni",
"apriltagjni");
} catch (Exception e) {
e.printStackTrace();
}
// NT live for debug purposes
NetworkTableInstance.getDefault().startServer();

View File

@@ -26,14 +26,8 @@ package org.photonvision.estimation;
import edu.wpi.first.apriltag.AprilTagFieldLayout;
import edu.wpi.first.apriltag.AprilTagFields;
import edu.wpi.first.cscore.CameraServerCvJNI;
import edu.wpi.first.hal.JNIWrapper;
import edu.wpi.first.math.geometry.Transform3d;
import edu.wpi.first.net.WPINetJNI;
import edu.wpi.first.networktables.NetworkTableInstance;
import edu.wpi.first.networktables.NetworkTablesJNI;
import edu.wpi.first.util.CombinedRuntimeLoader;
import edu.wpi.first.util.WPIUtilJNI;
import edu.wpi.first.wpilibj.smartdashboard.Field2d;
import edu.wpi.first.wpilibj.smartdashboard.SmartDashboard;
import java.io.IOException;
@@ -44,25 +38,6 @@ import org.photonvision.PhotonPoseEstimator;
public class ApriltagWorkbenchTest {
@BeforeAll
public static void setUp() {
JNIWrapper.Helper.setExtractOnStaticLoad(false);
WPIUtilJNI.Helper.setExtractOnStaticLoad(false);
NetworkTablesJNI.Helper.setExtractOnStaticLoad(false);
WPINetJNI.Helper.setExtractOnStaticLoad(false);
CameraServerCvJNI.Helper.setExtractOnStaticLoad(false);
try {
CombinedRuntimeLoader.loadLibraries(
ApriltagWorkbenchTest.class,
"wpiutiljni",
"ntcorejni",
"wpinetjni",
"wpiHaljni",
"cscorejnicvstatic");
} catch (Exception e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
// No version check for testing
PhotonCamera.setVersionCheckEnabled(false);
}

View File

@@ -27,6 +27,7 @@ import java.util.stream.Collectors;
import org.apache.commons.cli.*;
import org.photonvision.common.configuration.CameraConfiguration;
import org.photonvision.common.configuration.ConfigManager;
import org.photonvision.common.configuration.NeuralNetworkModelManager;
import org.photonvision.common.dataflow.networktables.NetworkTablesManager;
import org.photonvision.common.hardware.HardwareManager;
import org.photonvision.common.hardware.PiVersion;
@@ -37,9 +38,11 @@ import org.photonvision.common.logging.Logger;
import org.photonvision.common.networking.NetworkManager;
import org.photonvision.common.util.TestUtils;
import org.photonvision.common.util.numbers.IntegerCouple;
import org.photonvision.jni.RknnDetectorJNI;
import org.photonvision.mrcal.MrCalJNILoader;
import org.photonvision.raspi.LibCameraJNILoader;
import org.photonvision.server.Server;
import org.photonvision.vision.apriltag.AprilTagFamily;
import org.photonvision.vision.camera.FileVisionSource;
import org.photonvision.vision.opencv.CVMat;
import org.photonvision.vision.opencv.ContourGroupingMode;
@@ -261,6 +264,34 @@ public class Main {
camConf2023.pipelineSettings = psList2023;
}
CameraConfiguration camConf2024 =
ConfigManager.getInstance().getConfig().getCameraConfigurations().get("WPI2024");
if (camConf2024 == null || true) {
camConf2024 =
new CameraConfiguration(
"WPI2024",
TestUtils.getResourcesFolderPath(true)
.resolve("testimages")
.resolve(TestUtils.WPI2024Images.kSpeakerCenter_143in.path)
.toString());
camConf2024.FOV = TestUtils.WPI2024Images.FOV;
// same camera as 2023
camConf2024.calibrations.add(TestUtils.get2023LifeCamCoeffs(true));
var pipeline2024 = new AprilTagPipelineSettings();
var path_split = Path.of(camConf2024.path).getFileName().toString();
pipeline2024.pipelineNickname = path_split.replace(".jpg", "");
pipeline2024.targetModel = TargetModel.kAprilTag6p5in_36h11;
pipeline2024.tagFamily = AprilTagFamily.kTag36h11;
pipeline2024.inputShouldShow = true;
pipeline2024.solvePNPEnabled = true;
var psList2024 = new ArrayList<CVPipelineSettings>();
psList2024.add(pipeline2024);
camConf2024.pipelineSettings = psList2024;
}
// Colored shape testing
var camConfShape =
ConfigManager.getInstance().getConfig().getCameraConfigurations().get("Shape");
@@ -290,12 +321,14 @@ public class Main {
var fvs2020 = new FileVisionSource(camConf2020);
var fvs2022 = new FileVisionSource(camConf2022);
var fvs2023 = new FileVisionSource(camConf2023);
var fvs2024 = new FileVisionSource(camConf2024);
collectedSources.add(fvs2023);
collectedSources.add(fvs2022);
collectedSources.add(fvsShape);
collectedSources.add(fvs2020);
collectedSources.add(fvs2019);
collectedSources.add(fvs2024);
// collectedSources.add(fvs2023);
// collectedSources.add(fvs2022);
// collectedSources.add(fvsShape);
// collectedSources.add(fvs2020);
// collectedSources.add(fvs2019);
ConfigManager.getInstance().unloadCameraConfigs();
VisionModuleManager.getInstance().addSources(collectedSources).forEach(VisionModule::start);
@@ -317,7 +350,15 @@ public class Main {
} catch (IOException e) {
logger.error("Failed to load libcamera-JNI!", e);
}
try {
if (Platform.isRK3588()) {
RknnDetectorJNI.forceLoad();
} else {
logger.error("Platform does not support RKNN based machine learning!");
}
} catch (IOException e) {
logger.error("Failed to load rknn-JNI!", e);
}
try {
MrCalJNILoader.forceLoad();
} catch (IOException e) {
@@ -333,7 +374,6 @@ public class Main {
} catch (ParseException e) {
logger.error("Failed to parse command-line options!", e);
}
CVMat.enablePrint(false);
PipelineProfiler.enablePrint(false);
@@ -368,6 +408,10 @@ public class Main {
NetworkTablesManager.getInstance()
.setConfig(ConfigManager.getInstance().getConfig().getNetworkConfig());
logger.info("Loading ML models");
NeuralNetworkModelManager.getInstance()
.initialize(ConfigManager.getInstance().getModelsDirectory());
if (!isTestMode) {
logger.debug("Loading VisionSourceManager...");
VisionSourceManager.getInstance()

View File

@@ -350,8 +350,7 @@ public class DataSocketHandler {
}
}
private void sendMessage(Object message, WsContext user) throws JsonProcessingException {
ByteBuffer b = ByteBuffer.wrap(objectMapper.writeValueAsBytes(message));
private void sendMessage(ByteBuffer b, WsContext user) throws JsonProcessingException {
if (user.session.isOpen()) {
user.send(b);
}
@@ -359,16 +358,18 @@ public class DataSocketHandler {
public void broadcastMessage(Object message, WsContext userToSkip)
throws JsonProcessingException {
ByteBuffer b = ByteBuffer.wrap(objectMapper.writeValueAsBytes(message));
if (userToSkip == null) {
for (WsContext user : users) {
sendMessage(message, user);
sendMessage(b, user);
}
} else {
var skipUserPort = ((InetSocketAddress) userToSkip.session.getRemoteAddress()).getPort();
for (WsContext user : users) {
var userPort = ((InetSocketAddress) user.session.getRemoteAddress()).getPort();
if (userPort != skipUserPort) {
sendMessage(message, user);
sendMessage(b, user);
}
}
}

View File

@@ -31,6 +31,9 @@ import java.util.HashMap;
import java.util.Optional;
import javax.imageio.ImageIO;
import org.apache.commons.io.FileUtils;
import org.opencv.core.MatOfByte;
import org.opencv.core.MatOfInt;
import org.opencv.imgcodecs.Imgcodecs;
import org.photonvision.common.configuration.ConfigManager;
import org.photonvision.common.configuration.NetworkConfig;
import org.photonvision.common.dataflow.DataChangeDestination;
@@ -94,6 +97,7 @@ public class RequestHandler {
ctx.status(200);
ctx.result("Successfully saved the uploaded settings zip, rebooting...");
logger.info("Successfully saved the uploaded settings zip, rebooting...");
ConfigManager.getInstance().disableFlushOnShutdown();
restartProgram();
} else {
ctx.status(500);
@@ -579,6 +583,77 @@ public class RequestHandler {
ctx.status(204);
}
public static void onCalibrationSnapshotRequest(Context ctx) {
logger.info(ctx.queryString().toString());
int idx = Integer.parseInt(ctx.queryParam("cameraIdx"));
var width = Integer.parseInt(ctx.queryParam("width"));
var height = Integer.parseInt(ctx.queryParam("height"));
var observationIdx = Integer.parseInt(ctx.queryParam("snapshotIdx"));
CameraCalibrationCoefficients calList =
VisionModuleManager.getInstance()
.getModule(idx)
.getStateAsCameraConfig()
.calibrations
.stream()
.filter(
it ->
Math.abs(it.resolution.width - width) < 1e-4
&& Math.abs(it.resolution.height - height) < 1e-4)
.findFirst()
.orElse(null);
if (calList == null || calList.observations.size() < observationIdx) {
ctx.status(404);
return;
}
// encode as jpeg to save even more space. reduces size of a 1280p image from 300k to 25k
var jpegBytes = new MatOfByte();
Imgcodecs.imencode(
".jpg",
calList.observations.get(observationIdx).snapshotData.getAsMat(),
jpegBytes,
new MatOfInt(Imgcodecs.IMWRITE_JPEG_QUALITY, 60));
ctx.result(jpegBytes.toArray());
jpegBytes.release();
ctx.status(200);
}
public static void onCalibrationExportRequest(Context ctx) {
logger.info(ctx.queryString().toString());
int idx = Integer.parseInt(ctx.queryParam("cameraIdx"));
var width = Integer.parseInt(ctx.queryParam("width"));
var height = Integer.parseInt(ctx.queryParam("height"));
var cc = VisionModuleManager.getInstance().getModule(idx).getStateAsCameraConfig();
CameraCalibrationCoefficients calList =
cc.calibrations.stream()
.filter(
it ->
Math.abs(it.resolution.width - width) < 1e-4
&& Math.abs(it.resolution.height - height) < 1e-4)
.findFirst()
.orElse(null);
if (calList == null) {
ctx.status(404);
return;
}
var filename = "photon_calibration_" + cc.uniqueName + "_" + width + "x" + height + ".json";
ctx.contentType("application/zip");
ctx.header("Content-Disposition", "attachment; filename=\"" + filename + "\"");
ctx.json(calList);
ctx.status(200);
}
public static void onImageSnapshotsRequest(Context ctx) {
var snapshots = new ArrayList<HashMap<String, Object>>();
var cameraDirs = ConfigManager.getInstance().getImageSavePath().toFile().listFiles();

View File

@@ -130,6 +130,8 @@ public class Server {
app.post("/api/utils/restartDevice", RequestHandler::onDeviceRestartRequest);
app.post("/api/utils/publishMetrics", RequestHandler::onMetricsPublishRequest);
app.get("/api/utils/getImageSnapshots", RequestHandler::onImageSnapshotsRequest);
app.get("/api/utils/getCalSnapshot", RequestHandler::onCalibrationSnapshotRequest);
app.get("/api/utils/getCalibrationJSON", RequestHandler::onCalibrationExportRequest);
// Calibration
app.post("/api/calibration/end", RequestHandler::onCalibrationEndRequest);
@@ -138,7 +140,6 @@ public class Server {
app.post("/api/calibration/importFromData", RequestHandler::onDataCalibrationImportRequest);
app.start(port);
System.out.println("hi");
}
/**

View File

@@ -0,0 +1 @@
note

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