Add .close() method to ImageSegmenterResult/InteractiveSegmenterResult/PoseLandmarkerResult
PiperOrigin-RevId: 530973944
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@ -22,6 +22,7 @@ import {ImageSegmenterGraphOptions as ImageSegmenterGraphOptionsProto} from '../
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import {SegmenterOptions as SegmenterOptionsProto} from '../../../../tasks/cc/vision/image_segmenter/proto/segmenter_options_pb';
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import {WasmFileset} from '../../../../tasks/web/core/wasm_fileset';
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import {ImageProcessingOptions} from '../../../../tasks/web/vision/core/image_processing_options';
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import {MPMask} from '../../../../tasks/web/vision/core/mask';
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import {VisionGraphRunner, VisionTaskRunner} from '../../../../tasks/web/vision/core/vision_task_runner';
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import {LabelMapItem} from '../../../../util/label_map_pb';
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import {ImageSource, WasmModule} from '../../../../web/graph_runner/graph_runner';
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@ -58,7 +59,8 @@ export type ImageSegmenterCallback = (result: ImageSegmenterResult) => void;
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/** Performs image segmentation on images. */
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export class ImageSegmenter extends VisionTaskRunner {
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private result: ImageSegmenterResult = {};
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private categoryMask?: MPMask;
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private confidenceMasks?: MPMask[];
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private labels: string[] = [];
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private userCallback?: ImageSegmenterCallback;
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private outputCategoryMask = DEFAULT_OUTPUT_CATEGORY_MASK;
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@ -265,10 +267,7 @@ export class ImageSegmenter extends VisionTaskRunner {
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this.reset();
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this.processImageData(image, imageProcessingOptions);
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if (!this.userCallback) {
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return this.result;
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}
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return this.processResults();
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}
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/**
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@ -347,10 +346,7 @@ export class ImageSegmenter extends VisionTaskRunner {
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this.reset();
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this.processVideoData(videoFrame, imageProcessingOptions, timestamp);
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if (!this.userCallback) {
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return this.result;
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}
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return this.processResults();
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}
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/**
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@ -369,21 +365,20 @@ export class ImageSegmenter extends VisionTaskRunner {
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}
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private reset(): void {
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this.result = {};
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}
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/** Invokes the user callback once all data has been received. */
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private maybeInvokeCallback(): void {
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if (this.outputConfidenceMasks && !('confidenceMasks' in this.result)) {
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return;
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}
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if (this.outputCategoryMask && !('categoryMask' in this.result)) {
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return;
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this.categoryMask = undefined;
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this.confidenceMasks = undefined;
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}
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private processResults(): ImageSegmenterResult|void {
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try {
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const result =
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new ImageSegmenterResult(this.confidenceMasks, this.categoryMask);
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if (this.userCallback) {
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this.userCallback(this.result);
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this.userCallback(result);
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} else {
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return result;
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}
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} finally {
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// Free the image memory, now that we've kept all streams alive long
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// enough to be returned in our callbacks.
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this.freeKeepaliveStreams();
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@ -417,17 +412,15 @@ export class ImageSegmenter extends VisionTaskRunner {
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this.graphRunner.attachImageVectorListener(
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CONFIDENCE_MASKS_STREAM, (masks, timestamp) => {
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this.result.confidenceMasks = masks.map(
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this.confidenceMasks = masks.map(
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wasmImage => this.convertToMPMask(
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wasmImage, /* shouldCopyData= */ !this.userCallback));
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this.setLatestOutputTimestamp(timestamp);
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this.maybeInvokeCallback();
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});
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this.graphRunner.attachEmptyPacketListener(
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CONFIDENCE_MASKS_STREAM, timestamp => {
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this.result.confidenceMasks = undefined;
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this.confidenceMasks = [];
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this.setLatestOutputTimestamp(timestamp);
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this.maybeInvokeCallback();
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});
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}
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@ -438,16 +431,14 @@ export class ImageSegmenter extends VisionTaskRunner {
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this.graphRunner.attachImageListener(
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CATEGORY_MASK_STREAM, (mask, timestamp) => {
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this.result.categoryMask = this.convertToMPMask(
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this.categoryMask = this.convertToMPMask(
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mask, /* shouldCopyData= */ !this.userCallback);
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this.setLatestOutputTimestamp(timestamp);
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this.maybeInvokeCallback();
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});
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this.graphRunner.attachEmptyPacketListener(
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CATEGORY_MASK_STREAM, timestamp => {
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this.result.categoryMask = undefined;
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this.categoryMask = undefined;
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this.setLatestOutputTimestamp(timestamp);
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this.maybeInvokeCallback();
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});
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}
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@ -17,18 +17,26 @@
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import {MPMask} from '../../../../tasks/web/vision/core/mask';
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/** The output result of ImageSegmenter. */
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export declare interface ImageSegmenterResult {
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export class ImageSegmenterResult {
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constructor(
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/**
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* Multiple masks represented as `Float32Array` or `WebGLTexture`-backed
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* `MPImage`s where, for each mask, each pixel represents the prediction
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* confidence, usually in the [0, 1] range.
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*/
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confidenceMasks?: MPMask[];
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readonly confidenceMasks?: MPMask[],
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/**
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* A category mask represented as a `Uint8ClampedArray` or
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* `WebGLTexture`-backed `MPImage` where each pixel represents the class which
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* the pixel in the original image was predicted to belong to.
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* `WebGLTexture`-backed `MPImage` where each pixel represents the class
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* which the pixel in the original image was predicted to belong to.
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*/
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categoryMask?: MPMask;
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readonly categoryMask?: MPMask) {}
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/** Frees the resources held by the category and confidence masks. */
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close(): void {
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this.confidenceMasks?.forEach(m => {
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m.close();
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});
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this.categoryMask?.close();
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}
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}
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@ -263,7 +263,7 @@ describe('ImageSegmenter', () => {
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});
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});
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it('invokes listener once masks are available', async () => {
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it('invokes listener after masks are available', async () => {
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const categoryMask = new Uint8Array([1]);
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const confidenceMask = new Float32Array([0.0]);
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let listenerCalled = false;
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@ -282,7 +282,7 @@ describe('ImageSegmenter', () => {
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{data: confidenceMask, width: 1, height: 1},
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],
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1337);
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expect(listenerCalled).toBeTrue();
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expect(listenerCalled).toBeFalse();
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});
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return new Promise<void>(resolve => {
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@ -307,6 +307,6 @@ describe('ImageSegmenter', () => {
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const result = imageSegmenter.segment({} as HTMLImageElement);
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expect(result.confidenceMasks![0]).toBeInstanceOf(MPMask);
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result.confidenceMasks![0].close();
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result.close();
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});
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});
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@ -21,6 +21,7 @@ import {ImageSegmenterGraphOptions as ImageSegmenterGraphOptionsProto} from '../
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import {SegmenterOptions as SegmenterOptionsProto} from '../../../../tasks/cc/vision/image_segmenter/proto/segmenter_options_pb';
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import {WasmFileset} from '../../../../tasks/web/core/wasm_fileset';
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import {ImageProcessingOptions} from '../../../../tasks/web/vision/core/image_processing_options';
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import {MPMask} from '../../../../tasks/web/vision/core/mask';
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import {RegionOfInterest} from '../../../../tasks/web/vision/core/types';
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import {VisionGraphRunner, VisionTaskRunner} from '../../../../tasks/web/vision/core/vision_task_runner';
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import {Color as ColorProto} from '../../../../util/color_pb';
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@ -83,7 +84,8 @@ export type InteractiveSegmenterCallback =
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* - batch is always 1
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*/
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export class InteractiveSegmenter extends VisionTaskRunner {
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private result: InteractiveSegmenterResult = {};
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private categoryMask?: MPMask;
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private confidenceMasks?: MPMask[];
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private outputCategoryMask = DEFAULT_OUTPUT_CATEGORY_MASK;
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private outputConfidenceMasks = DEFAULT_OUTPUT_CONFIDENCE_MASKS;
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private userCallback?: InteractiveSegmenterCallback;
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@ -276,28 +278,24 @@ export class InteractiveSegmenter extends VisionTaskRunner {
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this.reset();
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this.processRenderData(roi, this.getSynctheticTimestamp());
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this.processImageData(image, imageProcessingOptions);
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if (!this.userCallback) {
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return this.result;
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}
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return this.processResults();
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}
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private reset(): void {
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this.result = {};
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}
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/** Invokes the user callback once all data has been received. */
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private maybeInvokeCallback(): void {
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if (this.outputConfidenceMasks && !('confidenceMasks' in this.result)) {
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return;
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}
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if (this.outputCategoryMask && !('categoryMask' in this.result)) {
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return;
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this.confidenceMasks = undefined;
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this.categoryMask = undefined;
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}
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private processResults(): InteractiveSegmenterResult|void {
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try {
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const result = new InteractiveSegmenterResult(
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this.confidenceMasks, this.categoryMask);
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if (this.userCallback) {
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this.userCallback(this.result);
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this.userCallback(result);
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} else {
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return result;
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}
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} finally {
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// Free the image memory, now that we've kept all streams alive long
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// enough to be returned in our callbacks.
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this.freeKeepaliveStreams();
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@ -333,17 +331,15 @@ export class InteractiveSegmenter extends VisionTaskRunner {
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this.graphRunner.attachImageVectorListener(
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CONFIDENCE_MASKS_STREAM, (masks, timestamp) => {
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this.result.confidenceMasks = masks.map(
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this.confidenceMasks = masks.map(
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wasmImage => this.convertToMPMask(
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wasmImage, /* shouldCopyData= */ !this.userCallback));
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this.setLatestOutputTimestamp(timestamp);
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this.maybeInvokeCallback();
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});
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this.graphRunner.attachEmptyPacketListener(
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CONFIDENCE_MASKS_STREAM, timestamp => {
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this.result.confidenceMasks = undefined;
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this.confidenceMasks = [];
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this.setLatestOutputTimestamp(timestamp);
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this.maybeInvokeCallback();
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});
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}
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@ -354,16 +350,14 @@ export class InteractiveSegmenter extends VisionTaskRunner {
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this.graphRunner.attachImageListener(
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CATEGORY_MASK_STREAM, (mask, timestamp) => {
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this.result.categoryMask = this.convertToMPMask(
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this.categoryMask = this.convertToMPMask(
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mask, /* shouldCopyData= */ !this.userCallback);
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this.setLatestOutputTimestamp(timestamp);
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this.maybeInvokeCallback();
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});
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this.graphRunner.attachEmptyPacketListener(
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CATEGORY_MASK_STREAM, timestamp => {
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this.result.categoryMask = undefined;
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this.categoryMask = undefined;
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this.setLatestOutputTimestamp(timestamp);
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this.maybeInvokeCallback();
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});
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}
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@ -17,18 +17,26 @@
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import {MPMask} from '../../../../tasks/web/vision/core/mask';
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/** The output result of InteractiveSegmenter. */
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export declare interface InteractiveSegmenterResult {
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export class InteractiveSegmenterResult {
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constructor(
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/**
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* Multiple masks represented as `Float32Array` or `WebGLTexture`-backed
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* `MPImage`s where, for each mask, each pixel represents the prediction
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* confidence, usually in the [0, 1] range.
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*/
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confidenceMasks?: MPMask[];
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readonly confidenceMasks?: MPMask[],
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/**
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* A category mask represented as a `Uint8ClampedArray` or
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* `WebGLTexture`-backed `MPImage` where each pixel represents the class which
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* the pixel in the original image was predicted to belong to.
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* `WebGLTexture`-backed `MPImage` where each pixel represents the class
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* which the pixel in the original image was predicted to belong to.
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*/
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categoryMask?: MPMask;
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readonly categoryMask?: MPMask) {}
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/** Frees the resources held by the category and confidence masks. */
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close(): void {
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this.confidenceMasks?.forEach(m => {
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m.close();
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});
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this.categoryMask?.close();
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}
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}
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@ -277,7 +277,7 @@ describe('InteractiveSegmenter', () => {
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});
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});
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it('invokes listener once masks are avaiblae', async () => {
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it('invokes listener after masks are avaiblae', async () => {
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const categoryMask = new Uint8Array([1]);
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const confidenceMask = new Float32Array([0.0]);
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let listenerCalled = false;
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@ -296,7 +296,7 @@ describe('InteractiveSegmenter', () => {
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{data: confidenceMask, width: 1, height: 1},
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],
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1337);
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expect(listenerCalled).toBeTrue();
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expect(listenerCalled).toBeFalse();
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});
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return new Promise<void>(resolve => {
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@ -322,6 +322,6 @@ describe('InteractiveSegmenter', () => {
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const result =
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interactiveSegmenter.segment({} as HTMLImageElement, KEYPOINT);
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expect(result.confidenceMasks![0]).toBeInstanceOf(MPMask);
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result.confidenceMasks![0].close();
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result.close();
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});
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});
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@ -21,9 +21,11 @@ import {BaseOptions as BaseOptionsProto} from '../../../../tasks/cc/core/proto/b
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import {PoseDetectorGraphOptions} from '../../../../tasks/cc/vision/pose_detector/proto/pose_detector_graph_options_pb';
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import {PoseLandmarkerGraphOptions} from '../../../../tasks/cc/vision/pose_landmarker/proto/pose_landmarker_graph_options_pb';
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import {PoseLandmarksDetectorGraphOptions} from '../../../../tasks/cc/vision/pose_landmarker/proto/pose_landmarks_detector_graph_options_pb';
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import {Landmark, NormalizedLandmark} from '../../../../tasks/web/components/containers/landmark';
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import {convertToLandmarks, convertToWorldLandmarks} from '../../../../tasks/web/components/processors/landmark_result';
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import {WasmFileset} from '../../../../tasks/web/core/wasm_fileset';
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import {ImageProcessingOptions} from '../../../../tasks/web/vision/core/image_processing_options';
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import {MPMask} from '../../../../tasks/web/vision/core/mask';
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import {Connection} from '../../../../tasks/web/vision/core/types';
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import {VisionGraphRunner, VisionTaskRunner} from '../../../../tasks/web/vision/core/vision_task_runner';
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import {ImageSource, WasmModule} from '../../../../web/graph_runner/graph_runner';
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@ -61,7 +63,9 @@ export type PoseLandmarkerCallback = (result: PoseLandmarkerResult) => void;
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/** Performs pose landmarks detection on images. */
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export class PoseLandmarker extends VisionTaskRunner {
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private result: Partial<PoseLandmarkerResult> = {};
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private landmarks: NormalizedLandmark[][] = [];
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private worldLandmarks: Landmark[][] = [];
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private segmentationMasks?: MPMask[];
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private outputSegmentationMasks = false;
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private userCallback?: PoseLandmarkerCallback;
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private readonly options: PoseLandmarkerGraphOptions;
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@ -268,10 +272,7 @@ export class PoseLandmarker extends VisionTaskRunner {
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this.resetResults();
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this.processImageData(image, imageProcessingOptions);
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if (!this.userCallback) {
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return this.result as PoseLandmarkerResult;
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}
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return this.processResults();
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}
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/**
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@ -352,31 +353,25 @@ export class PoseLandmarker extends VisionTaskRunner {
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this.resetResults();
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this.processVideoData(videoFrame, imageProcessingOptions, timestamp);
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if (!this.userCallback) {
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return this.result as PoseLandmarkerResult;
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}
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return this.processResults();
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}
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private resetResults(): void {
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this.result = {};
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}
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/** Invokes the user callback once all data has been received. */
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private maybeInvokeCallback(): void {
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if (!('landmarks' in this.result)) {
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return;
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}
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if (!('worldLandmarks' in this.result)) {
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return;
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}
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if (this.outputSegmentationMasks && !('segmentationMasks' in this.result)) {
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return;
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this.landmarks = [];
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this.worldLandmarks = [];
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this.segmentationMasks = undefined;
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}
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private processResults(): PoseLandmarkerResult|void {
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try {
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const result = new PoseLandmarkerResult(
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this.landmarks, this.worldLandmarks, this.segmentationMasks);
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if (this.userCallback) {
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this.userCallback(this.result as Required<PoseLandmarkerResult>);
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this.userCallback(result);
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} else {
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return result;
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}
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} finally {
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// Free the image memory, now that we've finished our callback.
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this.freeKeepaliveStreams();
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}
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@ -396,11 +391,11 @@ export class PoseLandmarker extends VisionTaskRunner {
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* Converts raw data into a landmark, and adds it to our landmarks list.
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*/
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private addJsLandmarks(data: Uint8Array[]): void {
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this.result.landmarks = [];
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this.landmarks = [];
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for (const binaryProto of data) {
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const poseLandmarksProto =
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NormalizedLandmarkList.deserializeBinary(binaryProto);
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this.result.landmarks.push(convertToLandmarks(poseLandmarksProto));
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this.landmarks.push(convertToLandmarks(poseLandmarksProto));
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}
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}
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@ -409,11 +404,11 @@ export class PoseLandmarker extends VisionTaskRunner {
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* worldLandmarks list.
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*/
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private adddJsWorldLandmarks(data: Uint8Array[]): void {
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this.result.worldLandmarks = [];
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this.worldLandmarks = [];
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for (const binaryProto of data) {
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const poseWorldLandmarksProto =
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LandmarkList.deserializeBinary(binaryProto);
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this.result.worldLandmarks.push(
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this.worldLandmarks.push(
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convertToWorldLandmarks(poseWorldLandmarksProto));
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}
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}
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@ -448,26 +443,22 @@ export class PoseLandmarker extends VisionTaskRunner {
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NORM_LANDMARKS_STREAM, (binaryProto, timestamp) => {
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this.addJsLandmarks(binaryProto);
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this.setLatestOutputTimestamp(timestamp);
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this.maybeInvokeCallback();
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});
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this.graphRunner.attachEmptyPacketListener(
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NORM_LANDMARKS_STREAM, timestamp => {
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this.result.landmarks = [];
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this.landmarks = [];
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this.setLatestOutputTimestamp(timestamp);
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this.maybeInvokeCallback();
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});
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||||
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||||
this.graphRunner.attachProtoVectorListener(
|
||||
WORLD_LANDMARKS_STREAM, (binaryProto, timestamp) => {
|
||||
this.adddJsWorldLandmarks(binaryProto);
|
||||
this.setLatestOutputTimestamp(timestamp);
|
||||
this.maybeInvokeCallback();
|
||||
});
|
||||
this.graphRunner.attachEmptyPacketListener(
|
||||
WORLD_LANDMARKS_STREAM, timestamp => {
|
||||
this.result.worldLandmarks = [];
|
||||
this.worldLandmarks = [];
|
||||
this.setLatestOutputTimestamp(timestamp);
|
||||
this.maybeInvokeCallback();
|
||||
});
|
||||
|
||||
if (this.outputSegmentationMasks) {
|
||||
|
@ -477,17 +468,15 @@ export class PoseLandmarker extends VisionTaskRunner {
|
|||
|
||||
this.graphRunner.attachImageVectorListener(
|
||||
SEGMENTATION_MASK_STREAM, (masks, timestamp) => {
|
||||
this.result.segmentationMasks = masks.map(
|
||||
this.segmentationMasks = masks.map(
|
||||
wasmImage => this.convertToMPMask(
|
||||
wasmImage, /* shouldCopyData= */ !this.userCallback));
|
||||
this.setLatestOutputTimestamp(timestamp);
|
||||
this.maybeInvokeCallback();
|
||||
});
|
||||
this.graphRunner.attachEmptyPacketListener(
|
||||
SEGMENTATION_MASK_STREAM, timestamp => {
|
||||
this.result.segmentationMasks = [];
|
||||
this.segmentationMasks = [];
|
||||
this.setLatestOutputTimestamp(timestamp);
|
||||
this.maybeInvokeCallback();
|
||||
});
|
||||
}
|
||||
|
||||
|
|
|
@ -24,13 +24,18 @@ export {Category, Landmark, NormalizedLandmark};
|
|||
* Represents the pose landmarks deection results generated by `PoseLandmarker`.
|
||||
* Each vector element represents a single pose detected in the image.
|
||||
*/
|
||||
export declare interface PoseLandmarkerResult {
|
||||
/** Pose landmarks of detected poses. */
|
||||
landmarks: NormalizedLandmark[][];
|
||||
|
||||
export class PoseLandmarkerResult {
|
||||
constructor(/** Pose landmarks of detected poses. */
|
||||
readonly landmarks: NormalizedLandmark[][],
|
||||
/** Pose landmarks in world coordinates of detected poses. */
|
||||
worldLandmarks: Landmark[][];
|
||||
|
||||
readonly worldLandmarks: Landmark[][],
|
||||
/** Segmentation mask for the detected pose. */
|
||||
segmentationMasks?: MPMask[];
|
||||
readonly segmentationMasks?: MPMask[]) {}
|
||||
|
||||
/** Frees the resources held by the segmentation masks. */
|
||||
close(): void {
|
||||
this.segmentationMasks?.forEach(m => {
|
||||
m.close();
|
||||
});
|
||||
}
|
||||
}
|
||||
|
|
|
@ -287,7 +287,7 @@ describe('PoseLandmarker', () => {
|
|||
});
|
||||
});
|
||||
|
||||
it('invokes listener once masks are available', (done) => {
|
||||
it('invokes listener after masks are available', (done) => {
|
||||
const landmarksProto = [createLandmarks().serializeBinary()];
|
||||
const worldLandmarksProto = [createWorldLandmarks().serializeBinary()];
|
||||
const masks = [
|
||||
|
@ -309,13 +309,12 @@ describe('PoseLandmarker', () => {
|
|||
expect(listenerCalled).toBeFalse();
|
||||
expect(listenerCalled).toBeFalse();
|
||||
poseLandmarker.listeners.get('segmentation_masks')!(masks, 1337);
|
||||
expect(listenerCalled).toBeTrue();
|
||||
done();
|
||||
});
|
||||
|
||||
// Invoke the pose landmarker
|
||||
poseLandmarker.detect({} as HTMLImageElement, () => {
|
||||
listenerCalled = true;
|
||||
done();
|
||||
});
|
||||
});
|
||||
|
||||
|
@ -336,5 +335,6 @@ describe('PoseLandmarker', () => {
|
|||
expect(poseLandmarker.fakeWasmModule._waitUntilIdle).toHaveBeenCalled();
|
||||
expect(result.landmarks).toEqual([[{'x': 0, 'y': 0, 'z': 0}]]);
|
||||
expect(result.worldLandmarks).toEqual([[{'x': 0, 'y': 0, 'z': 0}]]);
|
||||
result.close();
|
||||
});
|
||||
});
|
||||
|
|
Loading…
Reference in New Issue
Block a user