enh: Use gdlib for preview generation by default #50
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| 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-latest | |
| 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: Upload photos | |
| 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 | |
| - name: Set pure-js mode | |
| run: | | |
| ./occ config:app:set --value ${{ matrix.pure-js-mode }} recognize tensorflow.purejs | |
| - name: Set faces.enabled | |
| run: | | |
| ./occ config:app:set --value true recognize faces.enabled | |
| - 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/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') | |
| } | |
| " |