Internal

PiperOrigin-RevId: 529890599

mediapipe/tasks/web/vision/core/BUILD

@@ -87,6 +87,7 @@ mediapipe_ts_library(
     deps = [
         ":image",
         ":image_processing_options",
+        ":mask",
         ":vision_task_options",
         "//mediapipe/framework/formats:rect_jspb_proto",
         "//mediapipe/tasks/web/core",

mediapipe/tasks/web/vision/core/render_utils.ts

@@ -16,8 +16,6 @@
  * limitations under the License.
  */
 
-import {MPImageChannelConverter} from '../../../../tasks/web/vision/core/image';
-
 // Pre-baked color table for a maximum of 12 classes.
 const CM_ALPHA = 128;
 const COLOR_MAP: Array<[number, number, number, number]> = [
@@ -35,8 +33,37 @@ const COLOR_MAP: Array<[number, number, number, number]> = [
   [255, 255, 255, CM_ALPHA]   // class 11 is white; could do black instead?
 ];
 
-/** The color converter we use in our demos. */
+
-export const RENDER_UTIL_CONVERTER: MPImageChannelConverter = {
+/** Helper function to draw a confidence mask */
-  floatToRGBAConverter: v => [128, 0, 0, v * 255],
+export function drawConfidenceMask(
-  uint8ToRGBAConverter: v => COLOR_MAP[v % COLOR_MAP.length],
+    ctx: CanvasRenderingContext2D, image: Float32Array, width: number,
-};
+    height: number): void {
+  const uint8Array = new Uint8ClampedArray(width * height * 4);
+  for (let i = 0; i < image.length; i++) {
+    uint8Array[4 * i] = 128;
+    uint8Array[4 * i + 1] = 0;
+    uint8Array[4 * i + 2] = 0;
+    uint8Array[4 * i + 3] = image[i] * 255;
+  }
+  ctx.putImageData(new ImageData(uint8Array, width, height), 0, 0);
+}
+
+/**
+ * Helper function to draw a category mask. For GPU, we only have F32Arrays
+ * for now.
+ */
+export function drawCategoryMask(
+    ctx: CanvasRenderingContext2D, image: Uint8Array|Float32Array,
+    width: number, height: number): void {
+  const rgbaArray = new Uint8ClampedArray(width * height * 4);
+  const isFloatArray = image instanceof Float32Array;
+  for (let i = 0; i < image.length; i++) {
+    const colorIndex = isFloatArray ? Math.round(image[i] * 255) : image[i];
+    const color = COLOR_MAP[colorIndex % COLOR_MAP.length];
+    rgbaArray[4 * i] = color[0];
+    rgbaArray[4 * i + 1] = color[1];
+    rgbaArray[4 * i + 2] = color[2];
+    rgbaArray[4 * i + 3] = color[3];
+  }
+  ctx.putImageData(new ImageData(rgbaArray, width, height), 0, 0);
+}

mediapipe/tasks/web/vision/core/vision_task_runner.ts

@@ -20,6 +20,7 @@ import {WasmFileset} from '../../../../tasks/web/core/wasm_fileset';
 import {MPImage} from '../../../../tasks/web/vision/core/image';
 import {ImageProcessingOptions} from '../../../../tasks/web/vision/core/image_processing_options';
 import {MPImageShaderContext} from '../../../../tasks/web/vision/core/image_shader_context';
+import {MPMask} from '../../../../tasks/web/vision/core/mask';
 import {GraphRunner, ImageSource, WasmMediaPipeConstructor} from '../../../../web/graph_runner/graph_runner';
 import {SupportImage, WasmImage} from '../../../../web/graph_runner/graph_runner_image_lib';
 import {isWebKit} from '../../../../web/graph_runner/platform_utils';
@@ -226,7 +227,7 @@ export abstract class VisionTaskRunner extends TaskRunner {
   /**
    * Converts a WasmImage to an MPImage.
    *
-   * Converts the underlying Uint8ClampedArray-backed images to ImageData
+   * Converts the underlying Uint8Array-backed images to ImageData
    * (adding an alpha channel if necessary), passes through WebGLTextures and
    * throws for Float32Array-backed images.
    */
@@ -235,11 +236,9 @@ export abstract class VisionTaskRunner extends TaskRunner {
     const {data, width, height} = wasmImage;
     const pixels = width * height;
 
-    let container: ImageData|WebGLTexture|Uint8ClampedArray;
+    let container: ImageData|WebGLTexture;
-    if (data instanceof Uint8ClampedArray) {
+    if (data instanceof Uint8Array) {
-      if (data.length === pixels) {
+      if (data.length === pixels * 3) {
-        container = data;  // Mask
-      } else if (data.length === pixels * 3) {
         // TODO: Convert in C++
         const rgba = new Uint8ClampedArray(pixels * 4);
         for (let i = 0; i < pixels; ++i) {
@@ -249,19 +248,17 @@ export abstract class VisionTaskRunner extends TaskRunner {
           rgba[4 * i + 3] = 255;
         }
         container = new ImageData(rgba, width, height);
-      } else if (data.length ===pixels * 4) {
+      } else if (data.length === pixels * 4) {
-        container = new ImageData(data, width, height);
+        container = new ImageData(
+            new Uint8ClampedArray(data.buffer, data.byteOffset, data.length),
+            width, height);
       } else {
         throw new Error(`Unsupported channel count: ${data.length/pixels}`);
       }
-    } else if (data instanceof Float32Array) {
+    } else if (data instanceof WebGLTexture) {
-      if (data.length === pixels) {
-        container = data;  // Mask
-      } else {
-        throw new Error(`Unsupported channel count: ${data.length/pixels}`);
-      }
-    } else {  // WebGLTexture
       container = data;
+    } else {
+      throw new Error(`Unsupported format: ${data.constructor.name}`);
     }
 
     const image = new MPImage(
@@ -271,6 +268,30 @@ export abstract class VisionTaskRunner extends TaskRunner {
     return shouldCopyData ? image.clone() : image;
   }
 
+  /** Converts a WasmImage to an MPMask.  */
+  protected convertToMPMask(wasmImage: WasmImage, shouldCopyData: boolean):
+      MPMask {
+    const {data, width, height} = wasmImage;
+    const pixels = width * height;
+
+    let container: WebGLTexture|Uint8Array|Float32Array;
+    if (data instanceof Uint8Array || data instanceof Float32Array) {
+      if (data.length === pixels) {
+        container = data;
+      } else {
+        throw new Error(`Unsupported channel count: ${data.length / pixels}`);
+      }
+    } else {
+      container = data;
+    }
+
+    const mask = new MPMask(
+        [container],
+        /* ownsWebGLTexture= */ false, this.graphRunner.wasmModule.canvas!,
+        this.shaderContext, width, height);
+    return shouldCopyData ? mask.clone() : mask;
+  }
+
   /** Closes and cleans up the resources held by this task. */
   override close(): void {
     this.shaderContext.close();

mediapipe/tasks/web/vision/face_stylizer/face_stylizer_test.ts

@@ -109,7 +109,7 @@ describe('FaceStylizer', () => {
     faceStylizer.fakeWasmModule._waitUntilIdle.and.callFake(() => {
       verifyListenersRegistered(faceStylizer);
       faceStylizer.imageListener!
-          ({data: new Uint8ClampedArray([1, 1, 1, 1]), width: 1, height: 1},
+          ({data: new Uint8Array([1, 1, 1, 1]), width: 1, height: 1},
            /* timestamp= */ 1337);
     });
 
@@ -134,7 +134,7 @@ describe('FaceStylizer', () => {
     faceStylizer.fakeWasmModule._waitUntilIdle.and.callFake(() => {
       verifyListenersRegistered(faceStylizer);
       faceStylizer.imageListener!
-          ({data: new Uint8ClampedArray([1, 1, 1, 1]), width: 1, height: 1},
+          ({data: new Uint8Array([1, 1, 1, 1]), width: 1, height: 1},
            /* timestamp= */ 1337);
     });
 

mediapipe/tasks/web/vision/image_segmenter/BUILD

@@ -35,7 +35,7 @@ mediapipe_ts_declaration(
     deps = [
         "//mediapipe/tasks/web/core",
         "//mediapipe/tasks/web/core:classifier_options",
-        "//mediapipe/tasks/web/vision/core:image",
+        "//mediapipe/tasks/web/vision/core:mask",
         "//mediapipe/tasks/web/vision/core:vision_task_options",
     ],
 )
@@ -52,7 +52,7 @@ mediapipe_ts_library(
         "//mediapipe/framework:calculator_jspb_proto",
         "//mediapipe/tasks/web/core",
         "//mediapipe/tasks/web/core:task_runner_test_utils",
-        "//mediapipe/tasks/web/vision/core:image",
+        "//mediapipe/tasks/web/vision/core:mask",
         "//mediapipe/web/graph_runner:graph_runner_image_lib_ts",
     ],
 )

mediapipe/tasks/web/vision/image_segmenter/image_segmenter.ts

@@ -412,7 +412,7 @@ export class ImageSegmenter extends VisionTaskRunner {
       this.graphRunner.attachImageVectorListener(
           CONFIDENCE_MASKS_STREAM, (masks, timestamp) => {
             this.result.confidenceMasks = masks.map(
-                wasmImage => this.convertToMPImage(
+                wasmImage => this.convertToMPMask(
                     wasmImage, /* shouldCopyData= */ !this.userCallback));
             this.setLatestOutputTimestamp(timestamp);
             this.maybeInvokeCallback();
@@ -431,7 +431,7 @@ export class ImageSegmenter extends VisionTaskRunner {
 
       this.graphRunner.attachImageListener(
           CATEGORY_MASK_STREAM, (mask, timestamp) => {
-            this.result.categoryMask = this.convertToMPImage(
+            this.result.categoryMask = this.convertToMPMask(
                 mask, /* shouldCopyData= */ !this.userCallback);
             this.setLatestOutputTimestamp(timestamp);
             this.maybeInvokeCallback();

mediapipe/tasks/web/vision/image_segmenter/image_segmenter_result.d.ts

@@ -14,7 +14,7 @@
  * limitations under the License.
  */
 
-import {MPImage} from '../../../../tasks/web/vision/core/image';
+import {MPMask} from '../../../../tasks/web/vision/core/mask';
 
 /** The output result of ImageSegmenter. */
 export declare interface ImageSegmenterResult {
@@ -23,12 +23,12 @@ export declare interface ImageSegmenterResult {
    * `MPImage`s where, for each mask, each pixel represents the prediction
    * confidence, usually in the [0, 1] range.
    */
-  confidenceMasks?: MPImage[];
+  confidenceMasks?: MPMask[];
 
   /**
    * A category mask represented as a `Uint8ClampedArray` or
    * `WebGLTexture`-backed `MPImage` where each pixel represents the class which
    * the pixel in the original image was predicted to belong to.
    */
-  categoryMask?: MPImage;
+  categoryMask?: MPMask;
 }

mediapipe/tasks/web/vision/image_segmenter/image_segmenter_test.ts

@@ -19,8 +19,8 @@ import 'jasmine';
 // Placeholder for internal dependency on encodeByteArray
 import {CalculatorGraphConfig} from '../../../../framework/calculator_pb';
 import {addJasmineCustomFloatEqualityTester, createSpyWasmModule, MediapipeTasksFake, SpyWasmModule, verifyGraph} from '../../../../tasks/web/core/task_runner_test_utils';
+import {MPMask} from '../../../../tasks/web/vision/core/mask';
 import {WasmImage} from '../../../../web/graph_runner/graph_runner_image_lib';
-import {MPImage} from '../../../../tasks/web/vision/core/image';
 
 import {ImageSegmenter} from './image_segmenter';
 import {ImageSegmenterOptions} from './image_segmenter_options';
@@ -165,7 +165,7 @@ describe('ImageSegmenter', () => {
   });
 
   it('supports category mask', async () => {
-    const mask = new Uint8ClampedArray([1, 2, 3, 4]);
+    const mask = new Uint8Array([1, 2, 3, 4]);
 
     await imageSegmenter.setOptions(
         {outputCategoryMask: true, outputConfidenceMasks: false});
@@ -183,7 +183,7 @@ describe('ImageSegmenter', () => {
     return new Promise<void>(resolve => {
       imageSegmenter.segment({} as HTMLImageElement, result => {
         expect(imageSegmenter.fakeWasmModule._waitUntilIdle).toHaveBeenCalled();
-        expect(result.categoryMask).toBeInstanceOf(MPImage);
+        expect(result.categoryMask).toBeInstanceOf(MPMask);
         expect(result.confidenceMasks).not.toBeDefined();
         expect(result.categoryMask!.width).toEqual(2);
         expect(result.categoryMask!.height).toEqual(2);
@@ -216,18 +216,18 @@ describe('ImageSegmenter', () => {
         expect(imageSegmenter.fakeWasmModule._waitUntilIdle).toHaveBeenCalled();
         expect(result.categoryMask).not.toBeDefined();
 
-        expect(result.confidenceMasks![0]).toBeInstanceOf(MPImage);
+        expect(result.confidenceMasks![0]).toBeInstanceOf(MPMask);
         expect(result.confidenceMasks![0].width).toEqual(2);
         expect(result.confidenceMasks![0].height).toEqual(2);
 
-        expect(result.confidenceMasks![1]).toBeInstanceOf(MPImage);
+        expect(result.confidenceMasks![1]).toBeInstanceOf(MPMask);
         resolve();
       });
     });
   });
 
   it('supports combined category and confidence masks', async () => {
-    const categoryMask = new Uint8ClampedArray([1]);
+    const categoryMask = new Uint8Array([1]);
     const confidenceMask1 = new Float32Array([0.0]);
     const confidenceMask2 = new Float32Array([1.0]);
 
@@ -252,19 +252,19 @@ describe('ImageSegmenter', () => {
       // Invoke the image segmenter
       imageSegmenter.segment({} as HTMLImageElement, result => {
         expect(imageSegmenter.fakeWasmModule._waitUntilIdle).toHaveBeenCalled();
-        expect(result.categoryMask).toBeInstanceOf(MPImage);
+        expect(result.categoryMask).toBeInstanceOf(MPMask);
         expect(result.categoryMask!.width).toEqual(1);
         expect(result.categoryMask!.height).toEqual(1);
 
-        expect(result.confidenceMasks![0]).toBeInstanceOf(MPImage);
+        expect(result.confidenceMasks![0]).toBeInstanceOf(MPMask);
-        expect(result.confidenceMasks![1]).toBeInstanceOf(MPImage);
+        expect(result.confidenceMasks![1]).toBeInstanceOf(MPMask);
         resolve();
       });
     });
   });
 
   it('invokes listener once masks are available', async () => {
-    const categoryMask = new Uint8ClampedArray([1]);
+    const categoryMask = new Uint8Array([1]);
     const confidenceMask = new Float32Array([0.0]);
     let listenerCalled = false;
 
@@ -306,7 +306,7 @@ describe('ImageSegmenter', () => {
     });
 
     const result = imageSegmenter.segment({} as HTMLImageElement);
-    expect(result.confidenceMasks![0]).toBeInstanceOf(MPImage);
+    expect(result.confidenceMasks![0]).toBeInstanceOf(MPMask);
     result.confidenceMasks![0].close();
   });
 });

mediapipe/tasks/web/vision/interactive_segmenter/BUILD

@@ -37,7 +37,7 @@ mediapipe_ts_declaration(
     deps = [
         "//mediapipe/tasks/web/core",
         "//mediapipe/tasks/web/core:classifier_options",
-        "//mediapipe/tasks/web/vision/core:image",
+        "//mediapipe/tasks/web/vision/core:mask",
         "//mediapipe/tasks/web/vision/core:vision_task_options",
     ],
 )
@@ -54,7 +54,7 @@ mediapipe_ts_library(
         "//mediapipe/framework:calculator_jspb_proto",
         "//mediapipe/tasks/web/core",
         "//mediapipe/tasks/web/core:task_runner_test_utils",
-        "//mediapipe/tasks/web/vision/core:image",
+        "//mediapipe/tasks/web/vision/core:mask",
         "//mediapipe/util:render_data_jspb_proto",
         "//mediapipe/web/graph_runner:graph_runner_image_lib_ts",
     ],

mediapipe/tasks/web/vision/interactive_segmenter/interactive_segmenter.ts

@@ -328,7 +328,7 @@ export class InteractiveSegmenter extends VisionTaskRunner {
       this.graphRunner.attachImageVectorListener(
           CONFIDENCE_MASKS_STREAM, (masks, timestamp) => {
             this.result.confidenceMasks = masks.map(
-                wasmImage => this.convertToMPImage(
+                wasmImage => this.convertToMPMask(
                     wasmImage, /* shouldCopyData= */ !this.userCallback));
             this.setLatestOutputTimestamp(timestamp);
             this.maybeInvokeCallback();
@@ -347,7 +347,7 @@ export class InteractiveSegmenter extends VisionTaskRunner {
 
       this.graphRunner.attachImageListener(
           CATEGORY_MASK_STREAM, (mask, timestamp) => {
-            this.result.categoryMask = this.convertToMPImage(
+            this.result.categoryMask = this.convertToMPMask(
                 mask, /* shouldCopyData= */ !this.userCallback);
             this.setLatestOutputTimestamp(timestamp);
             this.maybeInvokeCallback();

mediapipe/tasks/web/vision/interactive_segmenter/interactive_segmenter_result.d.ts

@@ -14,7 +14,7 @@
  * limitations under the License.
  */
 
-import {MPImage} from '../../../../tasks/web/vision/core/image';
+import {MPMask} from '../../../../tasks/web/vision/core/mask';
 
 /** The output result of InteractiveSegmenter. */
 export declare interface InteractiveSegmenterResult {
@@ -23,12 +23,12 @@ export declare interface InteractiveSegmenterResult {
    * `MPImage`s where, for each mask, each pixel represents the prediction
    * confidence, usually in the [0, 1] range.
    */
-  confidenceMasks?: MPImage[];
+  confidenceMasks?: MPMask[];
 
   /**
    * A category mask represented as a `Uint8ClampedArray` or
    * `WebGLTexture`-backed `MPImage` where each pixel represents the class which
    * the pixel in the original image was predicted to belong to.
    */
-  categoryMask?: MPImage;
+  categoryMask?: MPMask;
 }

mediapipe/tasks/web/vision/interactive_segmenter/interactive_segmenter_test.ts

@@ -19,7 +19,7 @@ import 'jasmine';
 // Placeholder for internal dependency on encodeByteArray
 import {CalculatorGraphConfig} from '../../../../framework/calculator_pb';
 import {addJasmineCustomFloatEqualityTester, createSpyWasmModule, MediapipeTasksFake, SpyWasmModule, verifyGraph} from '../../../../tasks/web/core/task_runner_test_utils';
-import {MPImage} from '../../../../tasks/web/vision/core/image';
+import {MPMask} from '../../../../tasks/web/vision/core/mask';
 import {RenderData as RenderDataProto} from '../../../../util/render_data_pb';
 import {WasmImage} from '../../../../web/graph_runner/graph_runner_image_lib';
 
@@ -177,7 +177,7 @@ describe('InteractiveSegmenter', () => {
   });
 
   it('supports category mask', async () => {
-    const mask = new Uint8ClampedArray([1, 2, 3, 4]);
+    const mask = new Uint8Array([1, 2, 3, 4]);
 
     await interactiveSegmenter.setOptions(
         {outputCategoryMask: true, outputConfidenceMasks: false});
@@ -195,7 +195,7 @@ describe('InteractiveSegmenter', () => {
       interactiveSegmenter.segment({} as HTMLImageElement, KEYPOINT, result => {
         expect(interactiveSegmenter.fakeWasmModule._waitUntilIdle)
             .toHaveBeenCalled();
-        expect(result.categoryMask).toBeInstanceOf(MPImage);
+        expect(result.categoryMask).toBeInstanceOf(MPMask);
         expect(result.categoryMask!.width).toEqual(2);
         expect(result.categoryMask!.height).toEqual(2);
         expect(result.confidenceMasks).not.toBeDefined();
@@ -228,18 +228,18 @@ describe('InteractiveSegmenter', () => {
             .toHaveBeenCalled();
         expect(result.categoryMask).not.toBeDefined();
 
-        expect(result.confidenceMasks![0]).toBeInstanceOf(MPImage);
+        expect(result.confidenceMasks![0]).toBeInstanceOf(MPMask);
         expect(result.confidenceMasks![0].width).toEqual(2);
         expect(result.confidenceMasks![0].height).toEqual(2);
 
-        expect(result.confidenceMasks![1]).toBeInstanceOf(MPImage);
+        expect(result.confidenceMasks![1]).toBeInstanceOf(MPMask);
         resolve();
       });
     });
   });
 
   it('supports combined category and confidence masks', async () => {
-    const categoryMask = new Uint8ClampedArray([1]);
+    const categoryMask = new Uint8Array([1]);
     const confidenceMask1 = new Float32Array([0.0]);
     const confidenceMask2 = new Float32Array([1.0]);
 
@@ -266,19 +266,19 @@ describe('InteractiveSegmenter', () => {
           {} as HTMLImageElement, KEYPOINT, result => {
             expect(interactiveSegmenter.fakeWasmModule._waitUntilIdle)
                 .toHaveBeenCalled();
-            expect(result.categoryMask).toBeInstanceOf(MPImage);
+            expect(result.categoryMask).toBeInstanceOf(MPMask);
             expect(result.categoryMask!.width).toEqual(1);
             expect(result.categoryMask!.height).toEqual(1);
 
-            expect(result.confidenceMasks![0]).toBeInstanceOf(MPImage);
+            expect(result.confidenceMasks![0]).toBeInstanceOf(MPMask);
-            expect(result.confidenceMasks![1]).toBeInstanceOf(MPImage);
+            expect(result.confidenceMasks![1]).toBeInstanceOf(MPMask);
             resolve();
           });
     });
   });
 
   it('invokes listener once masks are avaiblae', async () => {
-    const categoryMask = new Uint8ClampedArray([1]);
+    const categoryMask = new Uint8Array([1]);
     const confidenceMask = new Float32Array([0.0]);
     let listenerCalled = false;
 
@@ -321,7 +321,7 @@ describe('InteractiveSegmenter', () => {
 
     const result =
         interactiveSegmenter.segment({} as HTMLImageElement, KEYPOINT);
-    expect(result.confidenceMasks![0]).toBeInstanceOf(MPImage);
+    expect(result.confidenceMasks![0]).toBeInstanceOf(MPMask);
     result.confidenceMasks![0].close();
   });
 });

mediapipe/tasks/web/vision/pose_landmarker/BUILD

@@ -45,7 +45,7 @@ mediapipe_ts_declaration(
         "//mediapipe/tasks/web/components/containers:category",
         "//mediapipe/tasks/web/components/containers:landmark",
         "//mediapipe/tasks/web/core",
-        "//mediapipe/tasks/web/vision/core:image",
+        "//mediapipe/tasks/web/vision/core:mask",
         "//mediapipe/tasks/web/vision/core:vision_task_options",
     ],
 )
@@ -63,7 +63,7 @@ mediapipe_ts_library(
         "//mediapipe/tasks/web/components/processors:landmark_result",
         "//mediapipe/tasks/web/core",
         "//mediapipe/tasks/web/core:task_runner_test_utils",
-        "//mediapipe/tasks/web/vision/core:image",
+        "//mediapipe/tasks/web/vision/core:mask",
         "//mediapipe/tasks/web/vision/core:vision_task_runner",
     ],
 )

mediapipe/tasks/web/vision/pose_landmarker/pose_landmarker.ts

@@ -504,7 +504,7 @@ export class PoseLandmarker extends VisionTaskRunner {
       this.graphRunner.attachImageVectorListener(
           SEGMENTATION_MASK_STREAM, (masks, timestamp) => {
             this.result.segmentationMasks = masks.map(
-                wasmImage => this.convertToMPImage(
+                wasmImage => this.convertToMPMask(
                     wasmImage, /* shouldCopyData= */ !this.userCallback));
             this.setLatestOutputTimestamp(timestamp);
             this.maybeInvokeCallback();

mediapipe/tasks/web/vision/pose_landmarker/pose_landmarker_result.d.ts

@@ -16,7 +16,7 @@
 
 import {Category} from '../../../../tasks/web/components/containers/category';
 import {Landmark, NormalizedLandmark} from '../../../../tasks/web/components/containers/landmark';
-import {MPImage} from '../../../../tasks/web/vision/core/image';
+import {MPMask} from '../../../../tasks/web/vision/core/mask';
 
 export {Category, Landmark, NormalizedLandmark};
 
@@ -35,5 +35,5 @@ export declare interface PoseLandmarkerResult {
   auxilaryLandmarks: NormalizedLandmark[][];
 
   /** Segmentation mask for the detected pose. */
-  segmentationMasks?: MPImage[];
+  segmentationMasks?: MPMask[];
 }

mediapipe/tasks/web/vision/pose_landmarker/pose_landmarker_test.ts

@@ -18,7 +18,7 @@ import 'jasmine';
 import {CalculatorGraphConfig} from '../../../../framework/calculator_pb';
 import {createLandmarks, createWorldLandmarks} from '../../../../tasks/web/components/processors/landmark_result_test_lib';
 import {addJasmineCustomFloatEqualityTester, createSpyWasmModule, MediapipeTasksFake, SpyWasmModule, verifyGraph} from '../../../../tasks/web/core/task_runner_test_utils';
-import {MPImage} from '../../../../tasks/web/vision/core/image';
+import {MPMask} from '../../../../tasks/web/vision/core/mask';
 import {VisionGraphRunner} from '../../../../tasks/web/vision/core/vision_task_runner';
 
 import {PoseLandmarker} from './pose_landmarker';
@@ -225,7 +225,7 @@ describe('PoseLandmarker', () => {
       expect(result.landmarks).toEqual([[{'x': 0, 'y': 0, 'z': 0}]]);
       expect(result.worldLandmarks).toEqual([[{'x': 0, 'y': 0, 'z': 0}]]);
       expect(result.auxilaryLandmarks).toEqual([[{'x': 0, 'y': 0, 'z': 0}]]);
-      expect(result.segmentationMasks![0]).toBeInstanceOf(MPImage);
+      expect(result.segmentationMasks![0]).toBeInstanceOf(MPMask);
       done();
     });
   });

mediapipe/web/graph_runner/graph_runner_image_lib.ts

@@ -10,7 +10,7 @@ type LibConstructor = new (...args: any[]) => GraphRunner;
 
 /** An image returned from a MediaPipe graph. */
 export interface WasmImage {
-  data: Uint8ClampedArray|Float32Array|WebGLTexture;
+  data: Uint8Array|Float32Array|WebGLTexture;
   width: number;
   height: number;
 }