Update java image segmenter to always output confidence masks and optionally output category mask.

PiperOrigin-RevId: 521852718

mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imagesegmenter/ImageSegmenter.java

@@ -79,10 +79,15 @@ public final class ImageSegmenter extends BaseVisionTaskApi {
   private static final List<String> INPUT_STREAMS =
       Collections.unmodifiableList(
           Arrays.asList("IMAGE:" + IMAGE_IN_STREAM_NAME, "NORM_RECT:" + NORM_RECT_IN_STREAM_NAME));
-  private static final int CONFIDENCE_MASKS_OUT_STREAM_INDEX = 0;
+  private static final List<String> OUTPUT_STREAMS =
+      Collections.unmodifiableList(
+          Arrays.asList(
+              "GROUPED_SEGMENTATION:segmented_mask_out",
+              "IMAGE:image_out",
+              "SEGMENTATION:0:segmentation"));
+  private static final int GROUPED_SEGMENTATION_OUT_STREAM_INDEX = 0;
   private static final int IMAGE_OUT_STREAM_INDEX = 1;
-  private static final int CONFIDENCE_MASK_OUT_STREAM_INDEX = 2;
+  private static final int SEGMENTATION_OUT_STREAM_INDEX = 2;
-  private static final int CATEGORY_MASK_OUT_STREAM_INDEX = 3;
   private static final String TASK_GRAPH_NAME =
       "mediapipe.tasks.vision.image_segmenter.ImageSegmenterGraph";
   private static final String TENSORS_TO_SEGMENTATION_CALCULATOR_NAME =
@@ -99,13 +104,6 @@ public final class ImageSegmenter extends BaseVisionTaskApi {
    */
   public static ImageSegmenter createFromOptions(
       Context context, ImageSegmenterOptions segmenterOptions) {
-    List<String> outputStreams = new ArrayList<>();
-    outputStreams.add("CONFIDENCE_MASKS:confidence_masks");
-    outputStreams.add("IMAGE:image_out");
-    outputStreams.add("CONFIDENCE_MASK:0:confidence_mask");
-    if (segmenterOptions.outputCategoryMask()) {
-      outputStreams.add("CATEGORY_MASK:category_mask");
-    }
     // TODO: Consolidate OutputHandler and TaskRunner.
     OutputHandler<ImageSegmenterResult, MPImage> handler = new OutputHandler<>();
     handler.setOutputPacketConverter(
@@ -113,62 +111,50 @@ public final class ImageSegmenter extends BaseVisionTaskApi {
           @Override
           public ImageSegmenterResult convertToTaskResult(List<Packet> packets)
               throws MediaPipeException {
-            if (packets.get(CONFIDENCE_MASKS_OUT_STREAM_INDEX).isEmpty()) {
+            if (packets.get(GROUPED_SEGMENTATION_OUT_STREAM_INDEX).isEmpty()) {
               return ImageSegmenterResult.create(
                   new ArrayList<>(),
-                  Optional.empty(),
+                  packets.get(GROUPED_SEGMENTATION_OUT_STREAM_INDEX).getTimestamp());
-                  packets.get(CONFIDENCE_MASKS_OUT_STREAM_INDEX).getTimestamp());
             }
-            List<MPImage> confidenceMasks = new ArrayList<>();
+            List<MPImage> segmentedMasks = new ArrayList<>();
-            int width = PacketGetter.getImageWidth(packets.get(CONFIDENCE_MASK_OUT_STREAM_INDEX));
+            int width = PacketGetter.getImageWidth(packets.get(SEGMENTATION_OUT_STREAM_INDEX));
-            int height = PacketGetter.getImageHeight(packets.get(CONFIDENCE_MASK_OUT_STREAM_INDEX));
+            int height = PacketGetter.getImageHeight(packets.get(SEGMENTATION_OUT_STREAM_INDEX));
-            int confidenceMasksListSize =
+            int imageFormat =
-                PacketGetter.getImageListSize(packets.get(CONFIDENCE_MASKS_OUT_STREAM_INDEX));
+                segmenterOptions.outputType() == ImageSegmenterOptions.OutputType.CONFIDENCE_MASK
-            ByteBuffer[] buffersArray = new ByteBuffer[confidenceMasksListSize];
+                    ? MPImage.IMAGE_FORMAT_VEC32F1
+                    : MPImage.IMAGE_FORMAT_ALPHA;
+            int imageListSize =
+                PacketGetter.getImageListSize(packets.get(GROUPED_SEGMENTATION_OUT_STREAM_INDEX));
+            ByteBuffer[] buffersArray = new ByteBuffer[imageListSize];
             // If resultListener is not provided, the resulted MPImage is deep copied from mediapipe
             // graph. If provided, the result MPImage is wrapping the mediapipe packet memory.
-            boolean copyImage = !segmenterOptions.resultListener().isPresent();
+            if (!segmenterOptions.resultListener().isPresent()) {
-            if (copyImage) {
+              for (int i = 0; i < imageListSize; i++) {
-              for (int i = 0; i < confidenceMasksListSize; i++) {
+                buffersArray[i] =
-                buffersArray[i] = ByteBuffer.allocateDirect(width * height * 4);
+                    ByteBuffer.allocateDirect(
+                        width * height * (imageFormat == MPImage.IMAGE_FORMAT_VEC32F1 ? 4 : 1));
               }
             }
             if (!PacketGetter.getImageList(
-                packets.get(CONFIDENCE_MASKS_OUT_STREAM_INDEX), buffersArray, copyImage)) {
+                packets.get(GROUPED_SEGMENTATION_OUT_STREAM_INDEX),
+                buffersArray,
+                !segmenterOptions.resultListener().isPresent())) {
               throw new MediaPipeException(
                   MediaPipeException.StatusCode.INTERNAL.ordinal(),
-                  "There is an error getting segmented masks.");
+                  "There is an error getting segmented masks. It usually results from incorrect"
+                      + " options of unsupported OutputType of given model.");
             }
             for (ByteBuffer buffer : buffersArray) {
               ByteBufferImageBuilder builder =
-                  new ByteBufferImageBuilder(buffer, width, height, MPImage.IMAGE_FORMAT_VEC32F1);
+                  new ByteBufferImageBuilder(buffer, width, height, imageFormat);
-              confidenceMasks.add(builder.build());
+              segmentedMasks.add(builder.build());
-            }
-            Optional<MPImage> categoryMask = Optional.empty();
-            if (segmenterOptions.outputCategoryMask()) {
-              ByteBuffer buffer;
-              if (copyImage) {
-                buffer = ByteBuffer.allocateDirect(width * height);
-                if (!PacketGetter.getImageData(
-                    packets.get(CATEGORY_MASK_OUT_STREAM_INDEX), buffer)) {
-                  throw new MediaPipeException(
-                      MediaPipeException.StatusCode.INTERNAL.ordinal(),
-                      "There is an error getting category mask.");
-                }
-              } else {
-                buffer =
-                    PacketGetter.getImageDataDirectly(packets.get(CATEGORY_MASK_OUT_STREAM_INDEX));
-              }
-              ByteBufferImageBuilder builder =
-                  new ByteBufferImageBuilder(buffer, width, height, MPImage.IMAGE_FORMAT_ALPHA);
-              categoryMask = Optional.of(builder.build());
             }
+
             return ImageSegmenterResult.create(
-                confidenceMasks,
+                segmentedMasks,
-                categoryMask,
                 BaseVisionTaskApi.generateResultTimestampMs(
                     segmenterOptions.runningMode(),
-                    packets.get(CONFIDENCE_MASKS_OUT_STREAM_INDEX)));
+                    packets.get(GROUPED_SEGMENTATION_OUT_STREAM_INDEX)));
           }
 
           @Override
@@ -188,7 +174,7 @@ public final class ImageSegmenter extends BaseVisionTaskApi {
                 .setTaskRunningModeName(segmenterOptions.runningMode().name())
                 .setTaskGraphName(TASK_GRAPH_NAME)
                 .setInputStreams(INPUT_STREAMS)
-                .setOutputStreams(outputStreams)
+                .setOutputStreams(OUTPUT_STREAMS)
                 .setTaskOptions(segmenterOptions)
                 .setEnableFlowLimiting(segmenterOptions.runningMode() == RunningMode.LIVE_STREAM)
                 .build(),
@@ -567,8 +553,8 @@ public final class ImageSegmenter extends BaseVisionTaskApi {
        */
       public abstract Builder setDisplayNamesLocale(String value);
 
-      /** Whether to output category mask. */
+      /** The output type from image segmenter. */
-      public abstract Builder setOutputCategoryMask(boolean value);
+      public abstract Builder setOutputType(OutputType value);
 
       /**
        * Sets an optional {@link ResultListener} to receive the segmentation results when the graph
@@ -608,17 +594,27 @@ public final class ImageSegmenter extends BaseVisionTaskApi {
 
     abstract String displayNamesLocale();
 
-    abstract boolean outputCategoryMask();
+    abstract OutputType outputType();
 
     abstract Optional<ResultListener<ImageSegmenterResult, MPImage>> resultListener();
 
     abstract Optional<ErrorListener> errorListener();
 
+    /** The output type of segmentation results. */
+    public enum OutputType {
+      // Gives a single output mask where each pixel represents the class which
+      // the pixel in the original image was predicted to belong to.
+      CATEGORY_MASK,
+      // Gives a list of output masks where, for each mask, each pixel represents
+      // the prediction confidence, usually in the [0, 1] range.
+      CONFIDENCE_MASK
+    }
+
     public static Builder builder() {
       return new AutoValue_ImageSegmenter_ImageSegmenterOptions.Builder()
           .setRunningMode(RunningMode.IMAGE)
           .setDisplayNamesLocale("en")
-          .setOutputCategoryMask(false);
+          .setOutputType(OutputType.CATEGORY_MASK);
     }
 
     /**
@@ -637,6 +633,14 @@ public final class ImageSegmenter extends BaseVisionTaskApi {
 
       SegmenterOptionsProto.SegmenterOptions.Builder segmenterOptionsBuilder =
           SegmenterOptionsProto.SegmenterOptions.newBuilder();
+      if (outputType() == OutputType.CONFIDENCE_MASK) {
+        segmenterOptionsBuilder.setOutputType(
+            SegmenterOptionsProto.SegmenterOptions.OutputType.CONFIDENCE_MASK);
+      } else if (outputType() == OutputType.CATEGORY_MASK) {
+        segmenterOptionsBuilder.setOutputType(
+            SegmenterOptionsProto.SegmenterOptions.OutputType.CATEGORY_MASK);
+      }
+
       taskOptionsBuilder.setSegmenterOptions(segmenterOptionsBuilder);
       return CalculatorOptions.newBuilder()
           .setExtension(

mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imagesegmenter/ImageSegmenterResult.java

@@ -19,7 +19,6 @@ import com.google.mediapipe.framework.image.MPImage;
 import com.google.mediapipe.tasks.core.TaskResult;
 import java.util.Collections;
 import java.util.List;
-import java.util.Optional;
 
 /** Represents the segmentation results generated by {@link ImageSegmenter}. */
 @AutoValue
@@ -28,24 +27,18 @@ public abstract class ImageSegmenterResult implements TaskResult {
   /**
    * Creates an {@link ImageSegmenterResult} instance from a list of segmentation MPImage.
    *
-   * @param confidenceMasks a {@link List} of MPImage in IMAGE_FORMAT_VEC32F1 format representing
+   * @param segmentations a {@link List} of MPImage representing the segmented masks. If OutputType
-   *     the confidence masks, where, for each mask, each pixel represents the prediction
+   *     is CATEGORY_MASK, the masks will be in IMAGE_FORMAT_ALPHA format. If OutputType is
-   *     confidence, usually in the [0, 1] range.
+   *     CONFIDENCE_MASK, the masks will be in IMAGE_FORMAT_VEC32F1 format.
-   * @param categoryMask an {@link Optional} MPImage in IMAGE_FORMAT_ALPHA format representing a
-   *     category mask, where each pixel represents the class which the pixel in the original image
-   *     was predicted to belong to.
    * @param timestampMs a timestamp for this result.
    */
   // TODO: consolidate output formats across platforms.
-  public static ImageSegmenterResult create(
+  public static ImageSegmenterResult create(List<MPImage> segmentations, long timestampMs) {
-      List<MPImage> confidenceMasks, Optional<MPImage> categoryMask, long timestampMs) {
     return new AutoValue_ImageSegmenterResult(
-        Collections.unmodifiableList(confidenceMasks), categoryMask, timestampMs);
+        Collections.unmodifiableList(segmentations), timestampMs);
   }
 
-  public abstract List<MPImage> confidenceMasks();
+  public abstract List<MPImage> segmentations();
-
-  public abstract Optional<MPImage> categoryMask();
 
   @Override
   public abstract long timestampMs();

mediapipe/tasks/java/com/google/mediapipe/tasks/vision/interactivesegmenter/InteractiveSegmenter.java

@@ -133,7 +133,6 @@ public final class InteractiveSegmenter extends BaseVisionTaskApi {
             if (packets.get(GROUPED_SEGMENTATION_OUT_STREAM_INDEX).isEmpty()) {
               return ImageSegmenterResult.create(
                   new ArrayList<>(),
-                  Optional.empty(),
                   packets.get(GROUPED_SEGMENTATION_OUT_STREAM_INDEX).getTimestamp());
             }
             List<MPImage> segmentedMasks = new ArrayList<>();
@@ -173,7 +172,6 @@ public final class InteractiveSegmenter extends BaseVisionTaskApi {
 
             return ImageSegmenterResult.create(
                 segmentedMasks,
-                Optional.empty(),
                 BaseVisionTaskApi.generateResultTimestampMs(
                     RunningMode.IMAGE, packets.get(GROUPED_SEGMENTATION_OUT_STREAM_INDEX)));
           }

mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/imagesegmenter/ImageSegmenterTest.java

@@ -61,13 +61,14 @@ public class ImageSegmenterTest {
       ImageSegmenterOptions options =
           ImageSegmenterOptions.builder()
               .setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
-              .setOutputCategoryMask(true)
+              .setOutputType(ImageSegmenterOptions.OutputType.CATEGORY_MASK)
               .build();
       ImageSegmenter imageSegmenter =
           ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
       ImageSegmenterResult actualResult = imageSegmenter.segment(getImageFromAsset(inputImageName));
-      assertThat(actualResult.categoryMask().isPresent()).isTrue();
+      List<MPImage> segmentations = actualResult.segmentations();
-      MPImage actualMaskBuffer = actualResult.categoryMask().get();
+      assertThat(segmentations.size()).isEqualTo(1);
+      MPImage actualMaskBuffer = actualResult.segmentations().get(0);
       MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
       verifyCategoryMask(
           actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY, MAGNIFICATION_FACTOR);
@@ -80,14 +81,15 @@ public class ImageSegmenterTest {
       ImageSegmenterOptions options =
           ImageSegmenterOptions.builder()
               .setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
+              .setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
               .build();
       ImageSegmenter imageSegmenter =
           ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
       ImageSegmenterResult actualResult = imageSegmenter.segment(getImageFromAsset(inputImageName));
-      List<MPImage> segmentations = actualResult.confidenceMasks();
+      List<MPImage> segmentations = actualResult.segmentations();
       assertThat(segmentations.size()).isEqualTo(21);
       // Cat category index 8.
-      MPImage actualMaskBuffer = segmentations.get(8);
+      MPImage actualMaskBuffer = actualResult.segmentations().get(8);
       MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
       verifyConfidenceMask(actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY);
     }
@@ -100,36 +102,40 @@ public class ImageSegmenterTest {
           ImageSegmenterOptions.builder()
               .setBaseOptions(
                   BaseOptions.builder().setModelAssetPath(SELFIE_128x128_MODEL_FILE).build())
+              .setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
               .build();
       ImageSegmenter imageSegmenter =
           ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
       ImageSegmenterResult actualResult = imageSegmenter.segment(getImageFromAsset(inputImageName));
-      List<MPImage> segmentations = actualResult.confidenceMasks();
+      List<MPImage> segmentations = actualResult.segmentations();
       assertThat(segmentations.size()).isEqualTo(2);
       // Selfie category index 1.
-      MPImage actualMaskBuffer = segmentations.get(1);
+      MPImage actualMaskBuffer = actualResult.segmentations().get(1);
       MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
       verifyConfidenceMask(actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY);
     }
 
-    @Test
+    // TODO: enable this unit test once activation option is supported in metadata.
-    public void segment_successWith144x256Segmentation() throws Exception {
+    // @Test
-      final String inputImageName = "mozart_square.jpg";
+    // public void segment_successWith144x256Segmentation() throws Exception {
-      final String goldenImageName = "selfie_segm_144_256_3_expected_mask.jpg";
+    //   final String inputImageName = "mozart_square.jpg";
-      ImageSegmenterOptions options =
+    //   final String goldenImageName = "selfie_segm_144_256_3_expected_mask.jpg";
-          ImageSegmenterOptions.builder()
+    //   ImageSegmenterOptions options =
-              .setBaseOptions(
+    //       ImageSegmenterOptions.builder()
-                  BaseOptions.builder().setModelAssetPath(SELFIE_144x256_MODEL_FILE).build())
+    //           .setBaseOptions(
-              .build();
+    //               BaseOptions.builder().setModelAssetPath(SELFIE_144x256_MODEL_FILE).build())
-      ImageSegmenter imageSegmenter =
+    //           .setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
-          ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
+    //           .build();
-      ImageSegmenterResult actualResult = imageSegmenter.segment(getImageFromAsset(inputImageName));
+    //   ImageSegmenter imageSegmenter =
-      List<MPImage> segmentations = actualResult.confidenceMasks();
+    //       ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
-      assertThat(segmentations.size()).isEqualTo(1);
+    //   ImageSegmenterResult actualResult =
-      MPImage actualMaskBuffer = segmentations.get(0);
+    // imageSegmenter.segment(getImageFromAsset(inputImageName));
-      MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
+    //   List<MPImage> segmentations = actualResult.segmentations();
-      verifyConfidenceMask(actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY);
+    //   assertThat(segmentations.size()).isEqualTo(1);
-    }
+    //   MPImage actualMaskBuffer = actualResult.segmentations().get(0);
+    //   MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
+    //   verifyConfidenceMask(actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY);
+    // }
 
     @Test
     public void getLabels_success() throws Exception {
@@ -159,6 +165,7 @@ public class ImageSegmenterTest {
       ImageSegmenterOptions options =
           ImageSegmenterOptions.builder()
               .setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
+              .setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
               .build();
       ImageSegmenter imageSegmenter =
           ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
@@ -280,15 +287,16 @@ public class ImageSegmenterTest {
       ImageSegmenterOptions options =
           ImageSegmenterOptions.builder()
               .setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
+              .setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
               .setRunningMode(RunningMode.IMAGE)
               .build();
       ImageSegmenter imageSegmenter =
           ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
       ImageSegmenterResult actualResult = imageSegmenter.segment(getImageFromAsset(inputImageName));
-      List<MPImage> segmentations = actualResult.confidenceMasks();
+      List<MPImage> segmentations = actualResult.segmentations();
       assertThat(segmentations.size()).isEqualTo(21);
       // Cat category index 8.
-      MPImage actualMaskBuffer = segmentations.get(8);
+      MPImage actualMaskBuffer = actualResult.segmentations().get(8);
       MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
       verifyConfidenceMask(actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY);
     }
@@ -301,11 +309,12 @@ public class ImageSegmenterTest {
       ImageSegmenterOptions options =
           ImageSegmenterOptions.builder()
               .setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
+              .setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
               .setRunningMode(RunningMode.IMAGE)
               .setResultListener(
                   (segmenterResult, inputImage) -> {
                     verifyConfidenceMask(
-                        segmenterResult.confidenceMasks().get(8),
+                        segmenterResult.segmentations().get(8),
                         expectedResult,
                         GOLDEN_MASK_SIMILARITY);
                   })
@@ -322,6 +331,7 @@ public class ImageSegmenterTest {
       ImageSegmenterOptions options =
           ImageSegmenterOptions.builder()
               .setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
+              .setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
               .setRunningMode(RunningMode.VIDEO)
               .build();
       ImageSegmenter imageSegmenter =
@@ -331,10 +341,10 @@ public class ImageSegmenterTest {
         ImageSegmenterResult actualResult =
             imageSegmenter.segmentForVideo(
                 getImageFromAsset(inputImageName), /* timestampsMs= */ i);
-        List<MPImage> segmentations = actualResult.confidenceMasks();
+        List<MPImage> segmentations = actualResult.segmentations();
         assertThat(segmentations.size()).isEqualTo(21);
         // Cat category index 8.
-        MPImage actualMaskBuffer = segmentations.get(8);
+        MPImage actualMaskBuffer = actualResult.segmentations().get(8);
         verifyConfidenceMask(actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY);
       }
     }
@@ -347,11 +357,12 @@ public class ImageSegmenterTest {
       ImageSegmenterOptions options =
           ImageSegmenterOptions.builder()
               .setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
+              .setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
               .setRunningMode(RunningMode.VIDEO)
               .setResultListener(
                   (segmenterResult, inputImage) -> {
                     verifyConfidenceMask(
-                        segmenterResult.confidenceMasks().get(8),
+                        segmenterResult.segmentations().get(8),
                         expectedResult,
                         GOLDEN_MASK_SIMILARITY);
                   })
@@ -373,11 +384,12 @@ public class ImageSegmenterTest {
       ImageSegmenterOptions options =
           ImageSegmenterOptions.builder()
               .setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
+              .setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
               .setRunningMode(RunningMode.LIVE_STREAM)
               .setResultListener(
                   (segmenterResult, inputImage) -> {
                     verifyConfidenceMask(
-                        segmenterResult.confidenceMasks().get(8),
+                        segmenterResult.segmentations().get(8),
                         expectedResult,
                         GOLDEN_MASK_SIMILARITY);
                   })
@@ -399,11 +411,12 @@ public class ImageSegmenterTest {
       ImageSegmenterOptions options =
           ImageSegmenterOptions.builder()
               .setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
+              .setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
               .setRunningMode(RunningMode.LIVE_STREAM)
               .setResultListener(
                   (segmenterResult, inputImage) -> {
                     verifyConfidenceMask(
-                        segmenterResult.confidenceMasks().get(8),
+                        segmenterResult.segmentations().get(8),
                         expectedResult,
                         GOLDEN_MASK_SIMILARITY);
                   })

mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/interactivesegmenter/InteractiveSegmenterTest.java

@@ -60,10 +60,7 @@ public class InteractiveSegmenterTest {
               ApplicationProvider.getApplicationContext(), options);
       MPImage image = getImageFromAsset(inputImageName);
       ImageSegmenterResult actualResult = imageSegmenter.segment(image, roi);
-      // TODO update to correct category mask output.
+      List<MPImage> segmentations = actualResult.segmentations();
-      // After InteractiveSegmenter updated according to (b/276519300), update this to use
-      // categoryMask field instead of confidenceMasks.
-      List<MPImage> segmentations = actualResult.confidenceMasks();
       assertThat(segmentations.size()).isEqualTo(1);
     }
 
@@ -82,7 +79,7 @@ public class InteractiveSegmenterTest {
               ApplicationProvider.getApplicationContext(), options);
       ImageSegmenterResult actualResult =
           imageSegmenter.segment(getImageFromAsset(inputImageName), roi);
-      List<MPImage> segmentations = actualResult.confidenceMasks();
+      List<MPImage> segmentations = actualResult.segmentations();
       assertThat(segmentations.size()).isEqualTo(2);
     }
   }