Update AdminController.php platform check #93
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name: Cluster-faces command test | |
on: | |
pull_request: | |
paths: | |
- 'lib/**' | |
- 'src/**' | |
push: | |
branches: | |
- master | |
paths: | |
- 'lib/**' | |
- 'src/**' | |
env: | |
APP_NAME: recognize | |
jobs: | |
php: | |
runs-on: ubuntu-20.04 | |
strategy: | |
# do not stop on another job's failure | |
fail-fast: false | |
matrix: | |
php-versions: ['8.2'] | |
databases: ['sqlite'] | |
server-versions: ['master'] | |
pure-js-mode: ['false'] | |
name: Test cluster-faces command on ${{ matrix.server-versions }} wasm:${{ matrix.pure-js-mode }} | |
env: | |
MYSQL_PORT: 4444 | |
PGSQL_PORT: 4445 | |
services: | |
mysql: | |
image: mariadb:10.5 | |
ports: | |
- 4444:3306/tcp | |
env: | |
MYSQL_ROOT_PASSWORD: rootpassword | |
options: --health-cmd="mysqladmin ping" --health-interval 5s --health-timeout 2s --health-retries 5 | |
postgres: | |
image: postgres | |
ports: | |
- 4445:5432/tcp | |
env: | |
POSTGRES_USER: root | |
POSTGRES_PASSWORD: rootpassword | |
POSTGRES_DB: nextcloud | |
options: --health-cmd pg_isready --health-interval 5s --health-timeout 2s --health-retries 5 | |
steps: | |
- name: Checkout server | |
uses: actions/checkout@v2 | |
with: | |
repository: nextcloud/server | |
ref: ${{ matrix.server-versions }} | |
- name: Checkout submodules | |
shell: bash | |
run: | | |
auth_header="$(git config --local --get http.https://github.com/.extraheader)" | |
git submodule sync --recursive | |
git -c "http.extraheader=$auth_header" -c protocol.version=2 submodule update --init --force --recursive --depth=1 | |
- name: install ssl-cert | |
if: env.ACT # Skip this on normal GitHub Actions | |
run: sudo apt update && sudo apt install -y ssl-cert | |
- name: Set up php ${{ matrix.php-versions }} | |
uses: shivammathur/setup-php@v2 | |
with: | |
php-version: ${{ matrix.php-versions }} | |
tools: phpunit | |
extensions: mbstring, iconv, fileinfo, intl, sqlite, pdo_mysql, pdo_sqlite, pgsql, pdo_pgsql, gd, zip | |
- name: Checkout app | |
uses: actions/checkout@v2 | |
with: | |
path: apps/${{ env.APP_NAME }} | |
- name: Read package.json node and npm engines version | |
uses: skjnldsv/[email protected] | |
id: versions | |
with: | |
path: apps/${{ env.APP_NAME }} | |
fallbackNode: '^12' | |
fallbackNpm: '^6' | |
- name: Set up node ${{ steps.versions.outputs.nodeVersion }} | |
uses: actions/setup-node@v2 | |
with: | |
node-version: ${{ steps.versions.outputs.nodeVersion }} | |
- name: Set up npm ${{ steps.versions.outputs.npmVersion }} | |
run: npm i -g npm@"${{ steps.versions.outputs.npmVersion }}" | |
- name: install make wget unzip | |
if: env.ACT # Skip this on normal GitHub Actions | |
run: sudo apt update && sudo apt install -y make wget unzip | |
- name: Install app | |
working-directory: apps/${{ env.APP_NAME }} | |
run: | | |
composer install --no-dev | |
make all | |
make remove-binaries | |
make remove-devdeps | |
- name: Set up Nextcloud and install app | |
if: ${{ matrix.databases != 'pgsql'}} | |
run: | | |
sleep 25 | |
mkdir data | |
./occ maintenance:install --verbose --database=${{ matrix.databases }} --database-name=nextcloud --database-host=127.0.0.1 --database-port=$MYSQL_PORT --database-user=root --database-pass=rootpassword --admin-user admin --admin-pass password | |
./occ app:enable -vvv -f ${{ env.APP_NAME }} | |
php -S localhost:8080 & | |
- name: Set up Nextcloud and install app | |
if: ${{ matrix.databases == 'pgsql'}} | |
run: | | |
sleep 25 | |
mkdir data | |
./occ maintenance:install --verbose --database=${{ matrix.databases }} --database-name=nextcloud --database-host=127.0.0.1 --database-port=$PGSQL_PORT --database-user=root --database-pass=rootpassword --admin-user admin --admin-pass password | |
./occ app:enable -vvv -f ${{ env.APP_NAME }} | |
php -S localhost:8080 & | |
- name: Install | |
run: | | |
./occ app:enable -vvv ${{ env.APP_NAME }} | |
- name: Remove unnecessary models to make space | |
run: | | |
rm -rf apps/recognize/models | |
- uses: actions/cache/restore@v3 | |
id: photos-cache | |
with: | |
path: data/admin/files/ | |
key: https://cloud.marcelklehr.de/s/PkNYbmKnwMiQMFD/download/IMDb-Face.zip | |
- name: Upload photos | |
if: steps.photos-cache.outputs.cache-hit != 'true' | |
run: | | |
mkdir -p data/admin/files/ | |
cd data/admin/files | |
wget https://cloud.marcelklehr.de/s/PkNYbmKnwMiQMFD/download/IMDb-Face.zip | |
unzip IMDb-Face.zip | |
rm IMDb-Face.zip | |
- uses: actions/cache/save@v3 | |
with: | |
path: data/admin/files/ | |
key: https://cloud.marcelklehr.de/s/PkNYbmKnwMiQMFD/download/IMDb-Face.zip | |
- name: Set config | |
run: | | |
./occ config:app:set --value ${{ matrix.pure-js-mode }} recognize tensorflow.purejs | |
./occ config:app:set --value true recognize faces.enabled | |
# only use one core. GH actions has 2 | |
./occ config:app:set --value 1 recognize tensorflow.cores | |
- uses: actions/cache/restore@v3 | |
id: db-cache | |
with: | |
path: data/nextcloud.db | |
key: ${{ runner.os }}-${{ matrix.server-versions }}-${{ hashFiles('data/admin/files/**', 'apps/recognize/src/classifier_faces.js', 'apps/recognize/lib/Classifiers/Classifier.php', 'apps/recognize/lib/Classifiers/Images/ClusteringFaceClassifier.php') }}-${{ matrix.pure-js-mode }} | |
- name: Run classifier | |
if: steps.db-cache.outputs.cache-hit != 'true' | |
env: | |
GITHUB_REF: ${{ github.ref }} | |
run: | | |
./occ files:scan admin | |
./occ recognize:classify | |
- uses: actions/cache/save@v3 | |
with: | |
path: data/nextcloud.db | |
key: ${{ steps.db-cache.outputs.cache-primary-key }} | |
- name: Reduce space | |
run: | | |
for dirname in data/admin/files/IMDb-Face/*; do truncate -s 0 "${dirname}/*"; done | |
- name: install sqlite3 | |
if: env.ACT # Skip this on normal GitHub Actions | |
run: sudo apt update && sudo apt install -y sqlite3 | |
- name: Create detection summary | |
run: | | |
sqlite3 data/nextcloud.db "select x, y, path from oc_recognize_face_detections d LEFT JOIN oc_filecache c ON c.fileid = d.file_id where user_id = 'admin' ORDER BY path;" > out.txt | |
- uses: actions/cache/restore@v3 | |
id: clustering-cache | |
with: | |
path: out.json | |
key: ${{ runner.os }}-${{ hashFiles('out.txt', 'apps/recognize/src/classifier_faces.js', 'apps/recognize/lib/Classifiers/Classifier.php', 'apps/recognize/lib/Classifiers/Images/ClusteringFaceClassifier.php', 'apps/recognize/lib/Clustering/**', 'apps/recognize/lib/Dav/**', 'apps/recognize/lib/Service/FaceClusterAnalyzer.php', 'apps/recognize/lib/Command/ClusterFaces.php') }}-${{ matrix.pure-js-mode }} | |
- name: Run clustering | |
if: steps.clustering-cache.outputs.cache-hit != 'true' | |
run: | | |
./occ recognize:cluster-faces -b 10000 | |
./occ recognize:cluster-faces -b 10000 | |
./occ recognize:cluster-faces -b 10000 | |
./occ recognize:cluster-faces -b 10000 | |
./occ recognize:cluster-faces -b 10000 | |
./occ recognize:cluster-faces -b 10000 | |
- name: install python3 python3-pip jq curl | |
if: steps.clustering-cache.outputs.cache-hit != 'true' && env.ACT # Skip this on normal GitHub Actions | |
run: sudo apt update && sudo apt install -y python3 python3-pip jq curl | |
- name: Install xq | |
if: steps.clustering-cache.outputs.cache-hit != 'true' | |
run: | | |
pip install yq | |
- name: Download face assignments | |
if: steps.clustering-cache.outputs.cache-hit != 'true' | |
run: | | |
curl -u 'admin:password' --request PROPFIND 'http://localhost:8080/remote.php/dav/recognize/admin/faces/' --header 'Depth: 2' --data '<?xml version="1.0"?> | |
<d:propfind xmlns:d="DAV:" | |
xmlns:oc="http://owncloud.org/ns" | |
xmlns:nc="http://nextcloud.org/ns" | |
xmlns:ocs="http://open-collaboration-services.org/ns"> | |
<d:prop> | |
<d:getcontentlength /> | |
<d:getcontenttype /> | |
<d:getetag /> | |
<d:getlastmodified /> | |
<d:resourcetype /> | |
<nc:face-detections /> | |
<nc:file-metadata-size /> | |
<nc:has-preview /> | |
<nc:realpath /> | |
<oc:favorite /> | |
<oc:fileid /> | |
<oc:permissions /> | |
<nc:nbItems /> | |
</d:prop> | |
</d:propfind>' > out.xml | |
cat out.xml | |
- name: Parse face assignments | |
if: steps.clustering-cache.outputs.cache-hit != 'true' | |
run: | | |
cat out.xml | xq '.["d:multistatus"]["d:response"] | map(select(.["d:href"] | test("faces/.+?/.+?"))) | map({"href": .["d:href"], "realpath": .["d:propstat"][0]["d:prop"]["nc:realpath"], "face-detections": .["d:propstat"][0]["d:prop"]["nc:face-detections"] | fromjson | map({userId, x, y, height, width, clusterId}) })' > out.json | |
cat out.json | |
- uses: actions/cache/save@v3 | |
with: | |
path: out.json | |
key: ${{ steps.clustering-cache.outputs.cache-primary-key }} | |
- name: Download IMDb-Face.csv | |
working-directory: apps/${{ env.APP_NAME }}/tests/res | |
run: | | |
wget https://cloud.marcelklehr.de/s/ZKe7MY7gZRRxBPq/download/IMDb-Face-csv.zip | |
unzip IMDb-Face-csv.zip | |
rm IMDb-Face-csv.zip | |
- name: Analyse face assignments | |
run: | | |
node -e " | |
const COLUMN_NAME = 0 | |
const COLUMN_URL = 5 | |
const COLUMN_RECT = 3 | |
const COLUMN_DIMS = 4 | |
const csv = fs.readFileSync(__dirname + '/apps/recognize/tests/res/IMDb-Face.csv') | |
.toString('utf8') | |
.split('\n') | |
.map(line => line.split(',')) | |
// remove csv header | |
csv.shift() | |
const names = [...new Set(csv.map(image => image[COLUMN_NAME])).values()] | |
const selectedNames = names.slice(0, 2000) | |
const limitedCsv = selectedNames.flatMap(name => { | |
return csv.filter(line => line[COLUMN_NAME] === name) | |
}) | |
const allDetections = fs.readFileSync(__dirname + '/out.txt').toString('utf8').trim().split('\n').map(line => line.split('|')) | |
const json = require(__dirname + '/out.json'); | |
const facesByCluster = json | |
.reduce((acc, face) => { | |
const clusterId = parseInt(face.href.split('/')[6]); | |
acc[clusterId] = [...(acc[clusterId] ?? []), face.realpath.split('/')[4]]; | |
return acc | |
}, {}); | |
const targetFaces = json | |
.filter(face => { | |
return limitedCsv | |
.some(entry => { | |
if (entry[COLUMN_NAME] === face.realpath.split('/')[4] && entry[COLUMN_URL].split('/').pop() === face.realpath.split('/').pop()) { | |
let dims = entry[COLUMN_DIMS].split(' ').map(i => parseInt(i)) | |
dims = {x: dims[1], y: dims[0]} | |
const rect = entry[COLUMN_RECT].split(' ').map(i => parseInt(i)) | |
return Math.abs(face['face-detections'][0].x - rect[0] / dims.x) < 0.05 && Math.abs(face['face-detections'][0].y - rect[1] / dims.y) < 0.05 | |
} | |
return false | |
}) | |
}) | |
const targetFacesPerIdentity = targetFaces.reduce((acc, face) => { | |
const name = face.realpath.split('/')[4] | |
acc[name] = acc[name] ?? [] | |
acc[name].push(face) | |
return acc | |
},{}) | |
const targetFacesByCluster = targetFaces | |
.reduce((acc, face) => { | |
const clusterId = parseInt(face.href.split('/')[6]); | |
acc[clusterId] = [...(acc[clusterId] ?? []), face.realpath.split('/')[4]]; | |
return acc | |
}, {}); | |
console.log(facesByCluster); | |
console.log(targetFacesByCluster); | |
const clusterTargetAccuracies = Object.entries(targetFacesByCluster) | |
.filter(([clusterId, names]) => names.length > 1) | |
.map(([clusterId, names]) => | |
[...new Set(names).values()] | |
.map(name1 => | |
names.filter(name2 => name1 === name2).length | |
).sort().reverse()[0] / names.length | |
); | |
const clusterAccuracies = Object.entries(facesByCluster) | |
.map(([clusterId, names]) => | |
[...new Set(names).values()] | |
.map(name1 => | |
names.filter(name2 => name1 === name2).length | |
).sort().reverse()[0] / names.length | |
); | |
const clusteredFaces = Object.entries(facesByCluster) | |
.map(([clusterId, names]) => names.length) | |
.reduce((acc, val) => acc+val, 0) | |
const clusteredTargetFaces = Object.entries(targetFacesByCluster) | |
.map(([clusterId, names]) => names.length) | |
.reduce((acc, val) => acc+val, 0) | |
const clusteredTargetFacesByIdentity = Object.entries(targetFacesByCluster) | |
.map(([clusterId, names]) => | |
[...new Set(names).values()] | |
.map(name1 => | |
[name1, names.filter(name2 => name1 === name2).length] | |
).sort(([name1, size1], [name2, size2]) => size1 - size2).reverse()[0] | |
) | |
.filter(([name,size]) => size > 1) | |
.reduce((acc, [name, size]) => { | |
acc[name] = (acc[name] ?? 0) + size | |
return acc | |
}, Object.fromEntries(Object.entries(targetFacesPerIdentity).map(([key]) => [key, 0]))) | |
console.log(targetFacesPerIdentity) | |
console.log(clusteredTargetFacesByIdentity) | |
const averageTargetFacesPerIdentity = Object.entries(targetFacesPerIdentity).reduce((acc, [name, detections]) => acc+detections.length, 0) / Object.entries(targetFacesPerIdentity).length | |
const averageClusteredTargetFacesByIdentity = Object.entries(clusteredTargetFacesByIdentity).reduce((acc, [name, size]) => acc+size, 0) / Object.entries(clusteredTargetFacesByIdentity).length | |
const clusteredTargetFacesByIdentityRate = Object.entries(clusteredTargetFacesByIdentity) | |
.reduce((acc, [name, size]) => acc + size / targetFacesPerIdentity[name].length, 0) / Object.entries(clusteredTargetFacesByIdentity).length | |
const identitiesWithPhotos = $(find data/admin/files/IMDb-Face -type d ! -empty | wc -l) | |
const identitiesWithDetections = Object.entries(targetFacesPerIdentity).length | |
const identitiesWithEnoughDetections = Object.entries(targetFacesPerIdentity).filter(([name, detections]) => detections.length > 1).length | |
const identitiesWithClusters = Object.entries(clusteredTargetFacesByIdentity).filter(([name, size]) => size > 1).length | |
const identitiesWithClustersRate = identitiesWithClusters / identitiesWithEnoughDetections | |
const detectedFaces = $(sqlite3 data/nextcloud.db "select count(*) from oc_recognize_face_detections where user_id = 'admin';") | |
const detectedTargetFaces = allDetections.filter(detection => { | |
if(detection.length < 3) return false | |
const x = Number(detection[0]) | |
const y = Number(detection[1]) | |
const path = detection[2] | |
return limitedCsv | |
.some(entry => { | |
if (entry[COLUMN_NAME] === path.split('/')[2] && entry[COLUMN_URL].split('/').pop().split('.jpg')[0] === path.split('/').pop().split('.jpg')[0]) { | |
let dims = entry[COLUMN_DIMS].split(' ').map(i => parseInt(i)) | |
dims = {x: dims[1], y: dims[0]} | |
const rect = entry[COLUMN_RECT].split(' ').map(i => parseInt(i)) | |
return Math.abs(x - rect[0] / dims.x) < 0.05 && Math.abs(y - rect[1] / dims.y) < 0.05 | |
} | |
return false | |
}) | |
}).length | |
const totalPhotos = $(ls data/admin/files/IMDb-Face/* | wc -l) | |
const detectedFacesRate = detectedFaces / totalPhotos | |
const clusteredTargetFacesRate = clusteredTargetFaces / detectedTargetFaces | |
const clusteredFacesRate = clusteredFaces / detectedFaces | |
const averageClusterAccuracy = clusterAccuracies.reduce((acc, val) => acc+val, 0)/clusterAccuracies.length | |
const averageClusterTargetAccuracy = clusterTargetAccuracies.reduce((acc, val) => acc+val, 0)/clusterTargetAccuracies.length | |
const targettedShitClusterRate = clusterTargetAccuracies.filter((val) => val < 0.5).length/clusterTargetAccuracies.length | |
const shitClusterRate = clusterAccuracies.filter((val) => val < 0.5).length/clusterAccuracies.length | |
console.log({ clusterAccuracies }); | |
console.log({ clusterTargetAccuracies }); | |
console.log({ totalPhotos }); | |
console.log({ detectedFaces }); | |
console.log({ detectedFacesRate }); | |
console.log({ detectedTargetFaces }); | |
console.log({ clusteredFaces }); | |
console.log({ clusteredFacesRate }) | |
console.log({ clusteredTargetFaces }) | |
console.log({ clusteredTargetFacesRate }) | |
console.log({ averageTargetFacesPerIdentity }) | |
console.log({ averageClusteredTargetFacesByIdentity }) | |
console.log({ clusteredTargetFacesByIdentityRate }) | |
console.log({ identitiesWithPhotos }) | |
console.log({ identitiesWithDetections }) | |
console.log({ identitiesWithEnoughDetections }) | |
console.log({ identitiesWithClusters }) | |
console.log({ identitiesWithClustersRate }) | |
console.log({ shitClusterRate }) | |
console.log({ targettedShitClusterRate }) | |
console.log({ averageClusterAccuracy }) | |
console.log({ averageClusterTargetAccuracy }) | |
console.log({ weightedAccuracy: averageClusterAccuracy * clusteredFacesRate }) | |
console.log({ weightedTargetAccuracy: averageClusterTargetAccuracy * clusteredTargetFacesRate }) | |
const combinedScore = (averageClusterTargetAccuracy * identitiesWithClustersRate * clusteredTargetFacesByIdentityRate * clusteredTargetFacesRate) ** (1/4) | |
console.log({ combinedScore, minCombinedScore: 0.6 }) | |
if (combinedScore < 0.6 || combinedScore > 1.0) { | |
console.log('Benchmark result: Bad') | |
process.exit(1) | |
} else { | |
console.log('Benchmark result: Good') | |
} | |
" |