在智能设备普及和AI技术进步的推动下，用户对线上互动的质量、个性化以及沉浸式体验的追求日益增强。例如，对于热衷于图片编辑或视频制作的用户来说，他们需要一种快速而简便的方法来将特定主体从背景中分离出来。
HarmonyOS SDK 基础视觉服务（Core Vision Kit）提供主体分割能力，可以检测出图片中区别于背景的前景物体或区域（即"显著主体"），并将其从背景中分离出来，适用于需要识别和提取图像主要信息的场景，广泛使用于前景目标检测和前景主体分离的场景。
适用场景
主体贴纸：从图片中提取显著性的主体，去掉背景。
背景替换：替换并提取出主体对象的背景。
显著性检测：快速定位图片中显著性区域。
辅助图片编辑：例如单独对主体进行美化处理。
开发步骤
1.引用相关类添加至工程。
import { subjectSegmentation } from '@kit.CoreVisionKit'; 2.准备预处理的图片资源，将图片转换为PixelMap，并添加初始化和释放方法。
async aboutToAppear(): Promise<void> { const initResult = await subjectSegmentation.init(); hilog.info(0x0000, 'subjectSegmentationSample', `Subject segmentation initialization result:${initResult}`); } async aboutToDisappear(): Promise<void> { await subjectSegmentation.release(); hilog.info(0x0000, 'subjectSegmentationSample', 'Subject segmentation released successfully'); } private async selectImage() { let uri = await this.openPhoto() if (uri === undefined) { hilog.error(0x0000, TAG, "uri is undefined"); } this.loadImage(uri); } private openPhoto(): Promise<Array<string>> { return new Promise<Array<string>>((resolve, reject) => { let PhotoSelectOptions = new photoAccessHelper.PhotoSelectOptions(); PhotoSelectOptions.MIMEType = photoAccessHelper.PhotoViewMIMETypes.IMAGE_TYPE; PhotoSelectOptions.maxSelectNumber = 1; let photoPicker: photoAccessHelper.PhotoViewPicker = new photoAccessHelper.PhotoViewPicker(); hilog.info(0x0000, TAG, 'PhotoViewPicker.select successfully, PhotoSelectResult uri: '); photoPicker.select(PhotoSelectOptions).then((PhotoSelectResult) => { hilog.info(0x0000, TAG, `PhotoViewPicker.select successfully, PhotoSelectResult uri: ${PhotoSelectResult.photoUris}`); resolve(PhotoSelectResult.photoUris) }).catch((err: BusinessError) => { hilog.error(0x0000, TAG, `PhotoViewPicker.select failed with errCode: ${err.code}, errMessage: ${err.message}`); reject(); }); }) } private loadImage(names: string[]) { setTimeout(async () => { let imageSource: image.ImageSource | undefined = undefined let fileSource = await fileIo.open(names[0], fileIo.OpenMode.READ_ONLY) imageSource = image.createImageSource(fileSource.fd) this.chooseImage = await imageSource.createPixelMap() hilog.info(0x0000, TAG, `this.chooseImage===${this.chooseImage}`); }, 100 ) } 3.实例化待分割的入参项VisionInfo，并传入待检测图片的PixelMap。
let visionInfo: subjectSegmentation.VisionInfo = { pixelMap: this.chooseImage, }; 4.配置通用文本识别的配置项SegmentationConfig，包括最大分割主体个数、是否输出每个主体的分割信息，以及是否输出分割后的前景图。
let config: subjectSegmentation.SegmentationConfig = { maxCount: parseInt(this.maxNum), enableSubjectDetails: true, enableSubjectForegroundImage: true, }; 5.调用imageSegmentation的ai.vision.doSegmentation接口，实现主体分割。
let data: subjectSegmentation.SegmentationResult = await subjectSegmentation.doSegmentation(visionInfo, config); let outputString = `Subject count: ${data.subjectCount}n`; outputString += `Max subject count: ${config.maxCount}n`; outputString += `Enable subject details: ${config.enableSubjectDetails ? 'Yes' : 'No'}nn`; let segBox : subjectSegmentation.Rectangle = data.fullSubject.subjectRectangle; let segBoxString = `Full subject box:nLeft: ${segBox.left}, Top: ${segBox.top}, Width: ${segBox.width}, Height: ${segBox.height}nn`; outputString += segBoxString; if (config.enableSubjectDetails) { outputString += 'Individual subject boxes:n'; if (data.subjectDetails) { for (let i = 0; i < data.subjectDetails.length; i++) { let detailSegBox: subjectSegmentation.Rectangle = data.subjectDetails[i].subjectRectangle; outputString += `Subject ${i + 1}:nLeft: ${detailSegBox.left}, Top: ${detailSegBox.top}, Width: ${detailSegBox.width}, Height: ${detailSegBox.height}nn`; } } } 了解更多详情>>
