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mediapipe/mediapipe/tasks/web/vision/image_segmenter/image_segmenter.ts
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2023-01-26 12:31:54 -08:00

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TypeScript

/**
* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
import {CalculatorGraphConfig} from '../../../../framework/calculator_pb';
import {CalculatorOptions} from '../../../../framework/calculator_options_pb';
import {BaseOptions as BaseOptionsProto} from '../../../../tasks/cc/core/proto/base_options_pb';
import {ImageSegmenterGraphOptions as ImageSegmenterGraphOptionsProto} from '../../../../tasks/cc/vision/image_segmenter/proto/image_segmenter_graph_options_pb';
import {SegmenterOptions as SegmenterOptionsProto} from '../../../../tasks/cc/vision/image_segmenter/proto/segmenter_options_pb';
import {WasmFileset} from '../../../../tasks/web/core/wasm_fileset';
import {ImageProcessingOptions} from '../../../../tasks/web/vision/core/image_processing_options';
import {VisionGraphRunner, VisionTaskRunner} from '../../../../tasks/web/vision/core/vision_task_runner';
import {ImageSource, WasmModule} from '../../../../web/graph_runner/graph_runner';
// Placeholder for internal dependency on trusted resource url
import {ImageSegmenterOptions} from './image_segmenter_options';
export * from './image_segmenter_options';
export {ImageSource}; // Used in the public API
/**
* The ImageSegmenter returns the segmentation result as a Uint8Array (when
* the default mode of `CATEGORY_MASK` is used) or as a Float32Array (for
* output type `CONFIDENCE_MASK`). The `WebGLTexture` output type is reserved
* for future usage.
*/
export type SegmentationMask = Uint8Array|Float32Array|WebGLTexture;
/**
* A callback that receives the computed masks from the image segmenter. The
* callback either receives a single element array with a category mask (as a
* `[Uint8Array]`) or multiple confidence masks (as a `Float32Array[]`).
* The returned data is only valid for the duration of the callback. If
* asynchronous processing is needed, all data needs to be copied before the
* callback returns.
*/
export type SegmentationMaskCallback =
(masks: SegmentationMask[], width: number, height: number) => void;
const IMAGE_STREAM = 'image_in';
const NORM_RECT_STREAM = 'norm_rect';
const GROUPED_SEGMENTATIONS_STREAM = 'segmented_masks';
const IMAGEA_SEGMENTER_GRAPH =
'mediapipe.tasks.vision.image_segmenter.ImageSegmenterGraph';
// The OSS JS API does not support the builder pattern.
// tslint:disable:jspb-use-builder-pattern
/** Performs image segmentation on images. */
export class ImageSegmenter extends VisionTaskRunner {
private userCallback: SegmentationMaskCallback = () => {};
private readonly options: ImageSegmenterGraphOptionsProto;
private readonly segmenterOptions: SegmenterOptionsProto;
/**
* Initializes the Wasm runtime and creates a new image segmenter from the
* provided options.
* @param wasmFileset A configuration object that provides the location of
* the Wasm binary and its loader.
* @param imageSegmenterOptions The options for the Image Segmenter. Note
* that either a path to the model asset or a model buffer needs to be
* provided (via `baseOptions`).
*/
static createFromOptions(
wasmFileset: WasmFileset,
imageSegmenterOptions: ImageSegmenterOptions): Promise<ImageSegmenter> {
return VisionTaskRunner.createInstance(
ImageSegmenter, /* initializeCanvas= */ true, wasmFileset,
imageSegmenterOptions);
}
/**
* Initializes the Wasm runtime and creates a new image segmenter based on
* the provided model asset buffer.
* @param wasmFileset A configuration object that provides the location of
* the Wasm binary and its loader.
* @param modelAssetBuffer A binary representation of the model.
*/
static createFromModelBuffer(
wasmFileset: WasmFileset,
modelAssetBuffer: Uint8Array): Promise<ImageSegmenter> {
return VisionTaskRunner.createInstance(
ImageSegmenter, /* initializeCanvas= */ true, wasmFileset,
{baseOptions: {modelAssetBuffer}});
}
/**
* Initializes the Wasm runtime and creates a new image segmenter based on
* the path to the model asset.
* @param wasmFileset A configuration object that provides the location of
* the Wasm binary and its loader.
* @param modelAssetPath The path to the model asset.
*/
static createFromModelPath(
wasmFileset: WasmFileset,
modelAssetPath: string): Promise<ImageSegmenter> {
return VisionTaskRunner.createInstance(
ImageSegmenter, /* initializeCanvas= */ true, wasmFileset,
{baseOptions: {modelAssetPath}});
}
/** @hideconstructor */
constructor(
wasmModule: WasmModule,
glCanvas?: HTMLCanvasElement|OffscreenCanvas|null) {
super(
new VisionGraphRunner(wasmModule, glCanvas), IMAGE_STREAM,
NORM_RECT_STREAM, /* roiAllowed= */ false);
this.options = new ImageSegmenterGraphOptionsProto();
this.segmenterOptions = new SegmenterOptionsProto();
this.options.setSegmenterOptions(this.segmenterOptions);
this.options.setBaseOptions(new BaseOptionsProto());
}
protected override get baseOptions(): BaseOptionsProto {
return this.options.getBaseOptions()!;
}
protected override set baseOptions(proto: BaseOptionsProto) {
this.options.setBaseOptions(proto);
}
/**
* Sets new options for the image segmenter.
*
* Calling `setOptions()` with a subset of options only affects those
* options. You can reset an option back to its default value by
* explicitly setting it to `undefined`.
*
* @param options The options for the image segmenter.
*/
override setOptions(options: ImageSegmenterOptions): Promise<void> {
// Note that we have to support both JSPB and ProtobufJS, hence we
// have to expliclity clear the values instead of setting them to
// `undefined`.
if (options.displayNamesLocale !== undefined) {
this.options.setDisplayNamesLocale(options.displayNamesLocale);
} else if ('displayNamesLocale' in options) { // Check for undefined
this.options.clearDisplayNamesLocale();
}
if (options.outputType === 'CONFIDENCE_MASK') {
this.segmenterOptions.setOutputType(
SegmenterOptionsProto.OutputType.CONFIDENCE_MASK);
} else {
this.segmenterOptions.setOutputType(
SegmenterOptionsProto.OutputType.CATEGORY_MASK);
}
return super.applyOptions(options);
}
/**
* Performs image segmentation on the provided single image and invokes the
* callback with the response. The method returns synchronously once the
* callback returns. Only use this method when the ImageSegmenter is
* created with running mode `image`.
*
* @param image An image to process.
* @param callback The callback that is invoked with the segmented masks. The
* lifetime of the returned data is only guaranteed for the duration of the
* callback.
*/
segment(image: ImageSource, callback: SegmentationMaskCallback): void;
/**
* Performs image segmentation on the provided single image and invokes the
* callback with the response. The method returns synchronously once the
* callback returns. Only use this method when the ImageSegmenter is
* created with running mode `image`.
*
* @param image An image to process.
* @param imageProcessingOptions the `ImageProcessingOptions` specifying how
* to process the input image before running inference.
* @param callback The callback that is invoked with the segmented masks. The
* lifetime of the returned data is only guaranteed for the duration of the
* callback.
*/
segment(
image: ImageSource, imageProcessingOptions: ImageProcessingOptions,
callback: SegmentationMaskCallback): void;
segment(
image: ImageSource,
imageProcessingOptionsOrCallback: ImageProcessingOptions|
SegmentationMaskCallback,
callback?: SegmentationMaskCallback): void {
const imageProcessingOptions =
typeof imageProcessingOptionsOrCallback !== 'function' ?
imageProcessingOptionsOrCallback :
{};
this.userCallback = typeof imageProcessingOptionsOrCallback === 'function' ?
imageProcessingOptionsOrCallback :
callback!;
this.processImageData(image, imageProcessingOptions);
this.userCallback = () => {};
}
/**
* Performs image segmentation on the provided video frame and invokes the
* callback with the response. The method returns synchronously once the
* callback returns. Only use this method when the ImageSegmenter is
* created with running mode `video`.
*
* @param videoFrame A video frame to process.
* @param timestamp The timestamp of the current frame, in ms.
* @param callback The callback that is invoked with the segmented masks. The
* lifetime of the returned data is only guaranteed for the duration of the
* callback.
*/
segmentForVideo(
videoFrame: ImageSource, timestamp: number,
callback: SegmentationMaskCallback): void;
/**
* Performs image segmentation on the provided video frame and invokes the
* callback with the response. The method returns synchronously once the
* callback returns. Only use this method when the ImageSegmenter is
* created with running mode `video`.
*
* @param videoFrame A video frame to process.
* @param imageProcessingOptions the `ImageProcessingOptions` specifying how
* to process the input image before running inference.
* @param timestamp The timestamp of the current frame, in ms.
* @param callback The callback that is invoked with the segmented masks. The
* lifetime of the returned data is only guaranteed for the duration of the
* callback.
*/
segmentForVideo(
videoFrame: ImageSource, imageProcessingOptions: ImageProcessingOptions,
timestamp: number, callback: SegmentationMaskCallback): void;
segmentForVideo(
videoFrame: ImageSource,
timestampOrImageProcessingOptions: number|ImageProcessingOptions,
timestampOrCallback: number|SegmentationMaskCallback,
callback?: SegmentationMaskCallback): void {
const imageProcessingOptions =
typeof timestampOrImageProcessingOptions !== 'number' ?
timestampOrImageProcessingOptions :
{};
const timestamp = typeof timestampOrImageProcessingOptions === 'number' ?
timestampOrImageProcessingOptions :
timestampOrCallback as number;
this.userCallback = typeof timestampOrCallback === 'function' ?
timestampOrCallback :
callback!;
this.processVideoData(videoFrame, imageProcessingOptions, timestamp);
this.userCallback = () => {};
}
/** Updates the MediaPipe graph configuration. */
protected override refreshGraph(): void {
const graphConfig = new CalculatorGraphConfig();
graphConfig.addInputStream(IMAGE_STREAM);
graphConfig.addInputStream(NORM_RECT_STREAM);
graphConfig.addOutputStream(GROUPED_SEGMENTATIONS_STREAM);
const calculatorOptions = new CalculatorOptions();
calculatorOptions.setExtension(
ImageSegmenterGraphOptionsProto.ext, this.options);
const segmenterNode = new CalculatorGraphConfig.Node();
segmenterNode.setCalculator(IMAGEA_SEGMENTER_GRAPH);
segmenterNode.addInputStream('IMAGE:' + IMAGE_STREAM);
segmenterNode.addInputStream('NORM_RECT:' + NORM_RECT_STREAM);
segmenterNode.addOutputStream(
'GROUPED_SEGMENTATION:' + GROUPED_SEGMENTATIONS_STREAM);
segmenterNode.setOptions(calculatorOptions);
graphConfig.addNode(segmenterNode);
this.graphRunner.attachImageVectorListener(
GROUPED_SEGMENTATIONS_STREAM, (masks, timestamp) => {
if (masks.length === 0) {
this.userCallback([], 0, 0);
} else {
this.userCallback(
masks.map(m => m.data), masks[0].width, masks[0].height);
}
this.setLatestOutputTimestamp(timestamp);
});
const binaryGraph = graphConfig.serializeBinary();
this.setGraph(new Uint8Array(binaryGraph), /* isBinary= */ true);
}
}