migrate code from googleapis/nodejs-video-intelligence

.github/workflows/video-intelligence.yaml

@@ -0,0 +1,67 @@
+name: video-intelligence
+on:
+  push:
+    branches:
+    - main
+    paths:
+    - 'video-intelligence/**'
+  pull_request:
+    paths:
+    - 'video-intelligence/**'
+  pull_request_target:
+    types: [labeled]
+  schedule:
+  - cron:  '0 0 * * 0'
+jobs:
+  test:
+    if: ${{ github.event.action != 'labeled' || github.event.label.name == 'actions:force-run' }}
+    runs-on: ubuntu-latest
+    timeout-minutes: 60
+    permissions:
+      contents: 'write'
+      pull-requests: 'write'
+      id-token: 'write'
+    steps:
+    - uses: actions/checkout@v3
+      with:
+        ref: ${{github.event.pull_request.head.ref}}
+        repository: ${{github.event.pull_request.head.repo.full_name}}
+    - uses: google-github-actions/auth@v1.0.0
+      with:
+        workload_identity_provider: 'projects/1046198160504/locations/global/workloadIdentityPools/github-actions-pool/providers/github-actions-provider'
+        service_account: 'kokoro-system-test@long-door-651.iam.gserviceaccount.com'
+        create_credentials_file: 'true'
+        access_token_lifetime: 600s
+    - uses: actions/setup-node@v3
+      with:
+        node-version: 14
+    - run: npm install
+      working-directory: video-intelligence
+    - run: npm test
+      working-directory: video-intelligence
+      env:
+        MOCHA_REPORTER_SUITENAME: video-intelligence
+        MOCHA_REPORTER_OUTPUT: video_intelligence_sponge_log.xml
+        MOCHA_REPORTER: xunit
+    - if: ${{ github.event.action == 'labeled' && github.event.label.name == 'actions:force-run' }}
+      uses: actions/github-script@v6
+      with:
+        github-token: ${{ secrets.GITHUB_TOKEN }}
+        script: |
+          try {
+            await github.rest.issues.removeLabel({
+              name: 'actions:force-run',
+              owner: 'GoogleCloudPlatform',
+              repo: 'nodejs-docs-samples',
+              issue_number: context.payload.pull_request.number
+            });
+          } catch (e) {
+            if (!e.message.includes('Label does not exist')) {
+              throw e;
+            }
+          }
+    - if: ${{ github.event_name == 'schedule' && always() }}
+      run: |
+        curl https://github.com/googleapis/repo-automation-bots/releases/download/flakybot-1.1.0/flakybot -o flakybot -s -L
+        chmod +x ./flakybot
+        ./flakybot --repo GoogleCloudPlatform/nodejs-docs-samples --commit_hash ${{github.sha}} --build_url https://github.com/${{github.repository}}/actions/runs/${{github.run_id}}

.github/workflows/workflows.json

@@ -56,6 +56,7 @@
   "datastore/functions",
   "scheduler",
   "talent",
+  "video-intelligence",
   "contact-center-insights",
   "workflows"
 ]

video-intelligence/.eslintrc.yml

@@ -0,0 +1,3 @@
+---
+rules:
+  no-console: off

video-intelligence/analyze-face-detection-gcs.js

@@ -0,0 +1,81 @@
+// Copyright 2020 Google LLC
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+'use strict';
+
+function main(gcsUri = 'YOUR_STORAGE_URI') {
+  // [START video_detect_faces_gcs]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const gcsUri = 'GCS URI of the video to analyze, e.g. gs://my-bucket/my-video.mp4';
+
+  // Imports the Google Cloud Video Intelligence library + Node's fs library
+  const Video = require('@google-cloud/video-intelligence').v1;
+
+  // Creates a client
+  const video = new Video.VideoIntelligenceServiceClient();
+
+  async function detectFacesGCS() {
+    const request = {
+      inputUri: gcsUri,
+      features: ['FACE_DETECTION'],
+      videoContext: {
+        faceDetectionConfig: {
+          // Must set includeBoundingBoxes to true to get facial attributes.
+          includeBoundingBoxes: true,
+          includeAttributes: true,
+        },
+      },
+    };
+    // Detects faces in a video
+    // We get the first result because we only process 1 video
+    const [operation] = await video.annotateVideo(request);
+    const results = await operation.promise();
+    console.log('Waiting for operation to complete...');
+
+    // Gets annotations for video
+    const faceAnnotations =
+      results[0].annotationResults[0].faceDetectionAnnotations;
+
+    for (const {tracks} of faceAnnotations) {
+      console.log('Face detected:');
+
+      for (const {segment, timestampedObjects} of tracks) {
+        console.log(
+          `\tStart: ${segment.startTimeOffset.seconds}.` +
+            `${(segment.startTimeOffset.nanos / 1e6).toFixed(0)}s`
+        );
+        console.log(
+          `\tEnd: ${segment.endTimeOffset.seconds}.` +
+            `${(segment.endTimeOffset.nanos / 1e6).toFixed(0)}s`
+        );
+
+        // Each segment includes timestamped objects that
+        // include characteristics of the face detected.
+        const [firstTimestapedObject] = timestampedObjects;
+
+        for (const {name} of firstTimestapedObject.attributes) {
+          // Attributes include 'glasses', 'headwear', 'smiling'.
+          console.log(`\tAttribute: ${name}; `);
+        }
+      }
+    }
+  }
+
+  detectFacesGCS();
+  // [END video_detect_faces_gcs]
+}
+
+main(...process.argv.slice(2));

video-intelligence/analyze-face-detection.js

@@ -0,0 +1,84 @@
+// Copyright 2020 Google LLC
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+'use strict';
+
+function main(path = 'YOUR_LOCAL_FILE') {
+  // [START video_detect_faces]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const path = 'Local file to analyze, e.g. ./my-file.mp4';
+
+  // Imports the Google Cloud Video Intelligence library + Node's fs library
+  const Video = require('@google-cloud/video-intelligence').v1;
+  const fs = require('fs');
+
+  // Creates a client
+  const video = new Video.VideoIntelligenceServiceClient();
+
+  // Reads a local video file and converts it to base64
+  const file = fs.readFileSync(path);
+  const inputContent = file.toString('base64');
+
+  async function detectFaces() {
+    const request = {
+      inputContent: inputContent,
+      features: ['FACE_DETECTION'],
+      videoContext: {
+        faceDetectionConfig: {
+          // Must set includeBoundingBoxes to true to get facial attributes.
+          includeBoundingBoxes: true,
+          includeAttributes: true,
+        },
+      },
+    };
+    // Detects faces in a video
+    // We get the first result because we only process 1 video
+    const [operation] = await video.annotateVideo(request);
+    const results = await operation.promise();
+    console.log('Waiting for operation to complete...');
+
+    // Gets annotations for video
+    const faceAnnotations =
+      results[0].annotationResults[0].faceDetectionAnnotations;
+    for (const {tracks} of faceAnnotations) {
+      console.log('Face detected:');
+      for (const {segment, timestampedObjects} of tracks) {
+        console.log(
+          `\tStart: ${segment.startTimeOffset.seconds}` +
+            `.${(segment.startTimeOffset.nanos / 1e6).toFixed(0)}s`
+        );
+        console.log(
+          `\tEnd: ${segment.endTimeOffset.seconds}.` +
+            `${(segment.endTimeOffset.nanos / 1e6).toFixed(0)}s`
+        );
+
+        // Each segment includes timestamped objects that
+        // include characteristics of the face detected.
+        const [firstTimestapedObject] = timestampedObjects;
+
+        for (const {name} of firstTimestapedObject.attributes) {
+          // Attributes include 'glasses', 'headwear', 'smiling'.
+          console.log(`\tAttribute: ${name}; `);
+        }
+      }
+    }
+  }
+
+  detectFaces();
+  // [END video_detect_faces]
+}
+
+main(...process.argv.slice(2));

video-intelligence/analyze-person-detection-gcs.js

@@ -0,0 +1,89 @@
+// Copyright 2020 Google LLC
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+'use strict';
+
+function main(gcsUri = 'YOUR_STORAGE_URI') {
+  // [START video_detect_person_gcs]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const gcsUri = 'GCS URI of the video to analyze, e.g. gs://my-bucket/my-video.mp4';
+
+  // Imports the Google Cloud Video Intelligence library + Node's fs library
+  const Video = require('@google-cloud/video-intelligence').v1;
+
+  // Creates a client
+  const video = new Video.VideoIntelligenceServiceClient();
+
+  async function detectPersonGCS() {
+    const request = {
+      inputUri: gcsUri,
+      features: ['PERSON_DETECTION'],
+      videoContext: {
+        personDetectionConfig: {
+          // Must set includeBoundingBoxes to true to get poses and attributes.
+          includeBoundingBoxes: true,
+          includePoseLandmarks: true,
+          includeAttributes: true,
+        },
+      },
+    };
+    // Detects faces in a video
+    // We get the first result because we only process 1 video
+    const [operation] = await video.annotateVideo(request);
+    const results = await operation.promise();
+    console.log('Waiting for operation to complete...');
+
+    // Gets annotations for video
+    const personAnnotations =
+      results[0].annotationResults[0].personDetectionAnnotations;
+
+    for (const {tracks} of personAnnotations) {
+      console.log('Person detected:');
+
+      for (const {segment, timestampedObjects} of tracks) {
+        console.log(
+          `\tStart: ${segment.startTimeOffset.seconds}` +
+            `.${(segment.startTimeOffset.nanos / 1e6).toFixed(0)}s`
+        );
+        console.log(
+          `\tEnd: ${segment.endTimeOffset.seconds}.` +
+            `${(segment.endTimeOffset.nanos / 1e6).toFixed(0)}s`
+        );
+
+        // Each segment includes timestamped objects that
+        // include characteristic--e.g. clothes, posture
+        // of the person detected.
+        const [firstTimestampedObject] = timestampedObjects;
+
+        // Attributes include unique pieces of clothing, poses (i.e., body
+        // landmarks) of the person detected.
+        for (const {name, value} of firstTimestampedObject.attributes) {
+          console.log(`\tAttribute: ${name}; Value: ${value}`);
+        }
+
+        // Landmarks in person detection include body parts.
+        for (const {name, point} of firstTimestampedObject.landmarks) {
+          console.log(`\tLandmark: ${name}; Vertex: ${point.x}, ${point.y}`);
+        }
+      }
+    }
+  }
+
+  detectPersonGCS();
+  // [END video_detect_person_gcs]
+}
+
+main(...process.argv.slice(2));