Update samples due to changes (#1083)

Author: nnegrey

video/beta/README.md

@@ -36,15 +36,6 @@ export GOOGLE_APPLICATION_CREDENTIALS=/path/to/your-project-credentials.json
 
 After you have authorized, you can analyze videos.
 
-Detect Faces' Bounding Boxes
-```
-mvn exec:java -DDetect -Dexec.args="faces-bounding-boxes gs://YOUR_BUCKET/YOUR_VIDEO.mp4"
-```
-
-Detect Faces' Emotions
-```
-mvn exec:java -DDetect -Dexec.args="faces-emotions gs://YOUR_BUCKET/YOUR_VIDEO.mp4"
-```
 
 Video Transcription
 ```

video/beta/pom.xml

@@ -40,7 +40,7 @@
     <dependency>
       <groupId>com.google.cloud</groupId>
       <artifactId>google-cloud-video-intelligence</artifactId>
-      <version>0.41.0-beta</version>
+      <version>0.43.0-beta</version>
     </dependency>
     <!-- [END dependencies] -->
 

video/beta/src/main/java/com/example/video/Detect.java

@@ -20,13 +20,7 @@
 import com.google.cloud.videointelligence.v1p1beta1.AnnotateVideoProgress;
 import com.google.cloud.videointelligence.v1p1beta1.AnnotateVideoRequest;
 import com.google.cloud.videointelligence.v1p1beta1.AnnotateVideoResponse;
-import com.google.cloud.videointelligence.v1p1beta1.EmotionAttribute;
-import com.google.cloud.videointelligence.v1p1beta1.FaceConfig;
-import com.google.cloud.videointelligence.v1p1beta1.FaceDetectionAnnotation;
-import com.google.cloud.videointelligence.v1p1beta1.FaceDetectionFrame;
-import com.google.cloud.videointelligence.v1p1beta1.FaceSegment;
 import com.google.cloud.videointelligence.v1p1beta1.Feature;
-import com.google.cloud.videointelligence.v1p1beta1.NormalizedBoundingBox;
 import com.google.cloud.videointelligence.v1p1beta1.SpeechRecognitionAlternative;
 import com.google.cloud.videointelligence.v1p1beta1.SpeechTranscription;
 import com.google.cloud.videointelligence.v1p1beta1.SpeechTranscriptionConfig;
@@ -39,7 +33,7 @@
 
 public class Detect {
   /**
-   * Detects face's bounding boxes, emotions, and video transcription using the Video Intelligence
+   * Detects video transcription using the Video Intelligence
    * API
    * @param args specifies features to detect and the path to the video on Google Cloud Storage.
    */
@@ -64,7 +58,7 @@ public static void argsHelper(String[] args) throws Exception {
       System.out.printf(
           "\tjava %s \"<command>\" \"<path-to-video>\"\n"
               + "Commands:\n"
-              + "\tfaces-bounding-boxes | faces-emotions | speech-transcription\n"
+              + "\tspeech-transcription\n"
               + "Path:\n\tA URI for a Cloud Storage resource (gs://...)\n"
               + "Examples: ",
           Detect.class.getCanonicalName());
@@ -73,175 +67,11 @@ public static void argsHelper(String[] args) throws Exception {
     String command = args[0];
     String path = args.length > 1 ? args[1] : "";
 
-    if (command.equals("faces-bounding-boxes")) {
-      analyzeFacesBoundingBoxes(path);
-    }
-    if (command.equals("faces-emotions")) {
-      analyzeFaceEmotions(path);
-    }
     if (command.equals("speech-transcription")) {
       speechTranscription(path);
     }
   }
 
-
-  // [START video_face_bounding_boxes]
-  /**
-   * Detects faces' bounding boxes on the video at the provided Cloud Storage path.
-   *
-   * @param gcsUri the path to the video file to analyze.
-   */
-  public static void analyzeFacesBoundingBoxes(String gcsUri) throws Exception {
-    // Instantiate a com.google.cloud.videointelligence.v1p1beta1.VideoIntelligenceServiceClient
-    try (VideoIntelligenceServiceClient client = VideoIntelligenceServiceClient.create()) {
-      // Set the configuration to include bounding boxes
-      FaceConfig config = FaceConfig.newBuilder()
-          .setIncludeBoundingBoxes(true)
-          .build();
-
-      // Set the video context with the above configuration
-      VideoContext context = VideoContext.newBuilder()
-          .setFaceDetectionConfig(config)
-          .build();
-
-      // Create the request
-      AnnotateVideoRequest request = AnnotateVideoRequest.newBuilder()
-          .setInputUri(gcsUri)
-          .addFeatures(Feature.FACE_DETECTION)
-          .setVideoContext(context)
-          .build();
-
-      // asynchronously perform facial analysis on videos
-      OperationFuture<AnnotateVideoResponse, AnnotateVideoProgress> response =
-          client.annotateVideoAsync(request);
-
-      System.out.println("Waiting for operation to complete...");
-      boolean faceFound = false;
-      // Display the results
-      for (VideoAnnotationResults results : response.get(900, TimeUnit.SECONDS)
-          .getAnnotationResultsList()) {
-        int faceCount = 0;
-        // Display the results for each face
-        for (FaceDetectionAnnotation faceAnnotation : results.getFaceDetectionAnnotationsList()) {
-          faceFound = true;
-          System.out.println("\nFace: " + ++faceCount);
-          // Each FaceDetectionAnnotation has only one segment.
-          for (FaceSegment segment : faceAnnotation.getSegmentsList()) {
-            double startTime = segment.getSegment().getStartTimeOffset().getSeconds()
-                + segment.getSegment().getStartTimeOffset().getNanos() / 1e9;
-            double endTime = segment.getSegment().getEndTimeOffset().getSeconds()
-                + segment.getSegment().getEndTimeOffset().getNanos() / 1e9;
-            System.out.printf("Segment location: %.3fs to %.3f\n", startTime, endTime);
-          }
-          // There are typically many frames for each face,
-          try {
-            // Here we process only the first frame.
-            if (faceAnnotation.getFramesCount() > 0) {
-              FaceDetectionFrame frame = faceAnnotation.getFrames(0); // get the first frame
-              double timeOffset = frame.getTimeOffset().getSeconds()
-                  + frame.getTimeOffset().getNanos() / 1e9;
-              System.out.printf("First frame time offset: %.3fs\n", timeOffset);
-              // print info on the first normalized bounding box
-              NormalizedBoundingBox box = frame.getAttributes(0).getNormalizedBoundingBox();
-              System.out.printf("\tLeft: %.3f\n", box.getLeft());
-              System.out.printf("\tTop: %.3f\n", box.getTop());
-              System.out.printf("\tBottom: %.3f\n", box.getBottom());
-              System.out.printf("\tRight: %.3f\n", box.getRight());
-            } else {
-              System.out.println("No frames found in annotation");
-            }
-          } catch (IndexOutOfBoundsException ioe) {
-            System.out.println("Could not retrieve frame: " + ioe.getMessage());
-          }
-        }
-      }
-
-      if (!faceFound) {
-        System.out.println("No faces detected in " + gcsUri);
-      }
-    }
-  }
-  // [END video_face_bounding_boxes]
-
-  // [START video_face_emotions]
-  /**
-   * Analyze faces' emotions over frames on the video at the provided Cloud Storage path.
-   *
-   * @param gcsUri the path to the video file to analyze.
-   */
-  public static void analyzeFaceEmotions(String gcsUri) throws Exception {
-    // Instantiate a com.google.cloud.videointelligence.v1p1beta1.VideoIntelligenceServiceClient
-    try (VideoIntelligenceServiceClient client = VideoIntelligenceServiceClient.create()) {
-      // Set the configuration to include bounding boxes
-      FaceConfig config = FaceConfig.newBuilder()
-          .setIncludeEmotions(true)
-          .build();
-
-      // Set the video context with the above configuration
-      VideoContext context = VideoContext.newBuilder()
-          .setFaceDetectionConfig(config)
-          .build();
-
-      // Create the request
-      AnnotateVideoRequest request = AnnotateVideoRequest.newBuilder()
-          .setInputUri(gcsUri)
-          .addFeatures(Feature.FACE_DETECTION)
-          .setVideoContext(context)
-          .build();
-
-      // asynchronously perform facial analysis on videos
-      OperationFuture<AnnotateVideoResponse, AnnotateVideoProgress> response =
-          client.annotateVideoAsync(request);
-
-      System.out.println("Waiting for operation to complete...");
-      boolean faceFound = false;
-      // Display the results
-      for (VideoAnnotationResults results : response.get(600, TimeUnit.SECONDS)
-          .getAnnotationResultsList()) {
-        int faceCount = 0;
-        // Display the results for each face
-        for (FaceDetectionAnnotation faceAnnotation : results.getFaceDetectionAnnotationsList()) {
-          faceFound = true;
-          System.out.println("\nFace: " + ++faceCount);
-          // Each FaceDetectionAnnotation has only one segment.
-          for (FaceSegment segment : faceAnnotation.getSegmentsList()) {
-            double startTime = segment.getSegment().getStartTimeOffset().getSeconds()
-                + segment.getSegment().getStartTimeOffset().getNanos() / 1e9;
-            double endTime = segment.getSegment().getEndTimeOffset().getSeconds()
-                + segment.getSegment().getEndTimeOffset().getNanos() / 1e9;
-            System.out.printf("Segment location: %.3fs to %.3f\n", startTime, endTime);
-          }
-
-          try {
-            // Print each frame's highest emotion
-            for (FaceDetectionFrame frame : faceAnnotation.getFramesList()) {
-              double timeOffset = frame.getTimeOffset().getSeconds()
-                  + frame.getTimeOffset().getNanos() / 1e9;
-              float highestScore = 0.0f;
-              String emotion = "";
-              // Get the highest scoring emotion for the current frame
-              for (EmotionAttribute emotionAttribute : frame.getAttributes(0).getEmotionsList()) {
-                if (emotionAttribute.getScore() > highestScore) {
-                  highestScore = emotionAttribute.getScore();
-                  emotion = emotionAttribute.getEmotion().name();
-                }
-              }
-              System.out.printf("\t%4.2fs: %14s %4.3f\n", timeOffset, emotion, highestScore);
-            }
-
-          } catch (IndexOutOfBoundsException ioe) {
-            System.out.println("Could not retrieve frame: " + ioe.getMessage());
-          }
-        }
-      }
-
-      if (!faceFound) {
-        System.out.println("No faces detected in " + gcsUri);
-      }
-    }
-  }
-  // [END video_face_emotions]
-
   // [START video_speech_transcription]
   /**
    * Transcribe speech from a video stored on GCS.
@@ -268,7 +98,7 @@ public static void speechTranscription(String gcsUri) throws Exception {
           .setVideoContext(context)
           .build();
 
-      // asynchronously perform facial analysis on videos
+      // asynchronously perform speech transcription on videos
       OperationFuture<AnnotateVideoResponse, AnnotateVideoProgress> response =
           client.annotateVideoAsync(request);
 

video/beta/src/test/java/com/example/video/DetectIT.java

@@ -34,7 +34,7 @@ public class DetectIT {
   private ByteArrayOutputStream bout;
   private PrintStream out;
 
-  static final String FACES_FILE_LOCATION =
+  static final String FILE_LOCATION =
       "gs://java-docs-samples-testing/video/googlework_short.mp4";
 
   @Before
@@ -49,27 +49,9 @@ public void tearDown() {
     System.setOut(null);
   }
 
-  @Test
-  public void testFacesBoundingBoxes() throws Exception {
-    String[] args = {"faces-bounding-boxes", FACES_FILE_LOCATION};
-    Detect.argsHelper(args);
-    String got = bout.toString();
-
-    assertThat(got).contains("Top:");
-  }
-
-  @Test
-  public void testFacesEmotions() throws Exception {
-    String[] args = {"faces-emotions", FACES_FILE_LOCATION};
-    Detect.argsHelper(args);
-    String got = bout.toString();
-
-    assertThat(got).contains("CONCENTRATION");
-  }
-
   @Test
   public void testSpeechTranscription() throws Exception {
-    String[] args = {"speech-transcription", FACES_FILE_LOCATION};
+    String[] args = {"speech-transcription", FILE_LOCATION};
     Detect.argsHelper(args);
     String got = bout.toString();