适用场景
主体分割，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。例如：
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主体贴纸，从图片中提取显著性的主体，去掉背景。
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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。
效果如下图所示：
开发步骤
-
引用相关类添加至工程。
import { subjectSegmentation } from '@kit.CoreVisionKit'; import { image } from '@kit.ImageKit'; import { hilog } from '@kit.PerformanceAnalysisKit'; import { BusinessError } from '@kit.BasicServicesKit'; import { fileIo } from '@kit.CoreFileKit'; import { photoAccessHelper } from '@kit.MediaLibraryKit'; -
初始化和释放：在aboutToAppear中调用subjectSegmentation.init()初始化主体分割服务（加载模型），在aboutToDisappear中调用subjectSegmentation.release()释放资源。
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'); } -
通过photoAccessHelper.PhotoViewPicker拉起图库选择图片，使用fileIo与image模块将URI转换为PixelMap，为后续分割接口准备输入数据。
private async selectImage() { let uri = await this.openPhoto(); if (uri === undefined) { hilog.error(0x0000, TAG, 'uri is undefined'); return; } this.loadImage(uri); } private async 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(); 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(err); }); }); } 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(); await fileIo.close(fileSource); }, 100); } -
实例化VisionInfo并传入待检测图片的PixelMap，同时配置SegmentationConfig，设置最大主体个数、是否输出详细信息与前景图。
let visionInfo: subjectSegmentation.VisionInfo = { pixelMap: this.chooseImage }; let config: subjectSegmentation.SegmentationConfig = { maxCount: parseInt(this.maxNum), enableSubjectDetails: true, enableSubjectForegroundImage: true }; -
调用subjectSegmentation的subjectSegmentation.doSegmentation接口实现主体分割，并将结果展示在界面上。
Button('Image Segmentation') .type(ButtonType.Capsule) .fontColor(Color.White) .alignSelf(ItemAlign.Center) .width('80%') .margin(10) .onClick(() => { if (!this.chooseImage) { hilog.error(0x0000, TAG, 'imageSegmentation not have chooseImage'); return; } let visionInfo: subjectSegmentation.VisionInfo = { pixelMap: this.chooseImage }; let config: subjectSegmentation.SegmentationConfig = { maxCount: parseInt(this.maxNum), enableSubjectDetails: true, enableSubjectForegroundImage: true }; subjectSegmentation.doSegmentation(visionInfo, config) .then((data: subjectSegmentation.SegmentationResult) => { // 拼装分割结果信息 let outputString = `Subject count: ${data.subjectCount}\n`; outputString += `Max subject count: ${config.maxCount}\n`; outputString += `Enable subject details: ${config.enableSubjectDetails ? 'Yes' : 'No'}\n\n`; let segBox: subjectSegmentation.Rectangle = data.fullSubject.subjectRectangle; outputString += `Full subject box:\nLeft: ${segBox.left}, Top: ${segBox.top}, Width: ${segBox.width}, Height: ${segBox.height}\n\n`; // 拼装每个主体的详细分割信息 if (config.enableSubjectDetails && data.subjectDetails) { outputString += 'Individual subject boxes:\n'; 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}\n\n`; } } hilog.info(0x0000, TAG, 'Segmentation result: ' + outputString); this.dataValues = outputString; if (data.fullSubject && data.fullSubject.foregroundImage) { this.segmentedImage = data.fullSubject.foregroundImage; } else { hilog.error(0x0000, TAG, 'No foreground image in segmentation result'); } }) .catch((error: BusinessError) => { hilog.error(0x0000, TAG, `Image segmentation failed errCode: ${error.code}, errMessage: ${error.message}`); this.dataValues = `Error: ${error.message}`; this.segmentedImage = undefined; }); })
[h2]Index.ets
import { subjectSegmentation } from '@kit.CoreVisionKit';
import { image } from '@kit.ImageKit';
import { hilog } from '@kit.PerformanceAnalysisKit';
import { BusinessError } from '@kit.BasicServicesKit';
import { fileIo } from '@kit.CoreFileKit';
import { photoAccessHelper } from '@kit.MediaLibraryKit';
const TAG: string = 'ImageSegmentationSample';
@Entry
@Component
struct Index {
@State chooseImage: PixelMap | undefined = undefined;
@State dataValues: string = '';
@State segmentedImage: PixelMap | undefined = undefined;
// 设置识别主体数量的上限
@State maxNum: string = '20';
async aboutToAppear(): Promise<void> {
const initResult = await subjectSegmentation.init();
hilog.info(0x0000, 'subjectSegmentationSample', `Subject segmentation initialization result:${initResult}`);
}
async aboutToDisappear(): Promise<void> {
await subjectSegmentation.release();
hilog.info(0x0000, 'subjectSegmentationSample', 'Subject segmentation released successfully');
}
build() {
Column() {
Image(this.chooseImage)
.objectFit(ImageFit.Fill)
.height('30%')
.accessibilityDescription('Image to be segmented')
Scroll() {
Text(this.dataValues)
.copyOption(CopyOptions.LocalDevice)
.margin(10)
.width('100%')
}
.height('20%')
Image(this.segmentedImage)
.objectFit(ImageFit.Fill)
.height('30%')
.accessibilityDescription('Segmented subject image')
Row() {
Text('Max subject count:')
.fontSize(16)
TextInput({ placeholder: 'Enter max subject count', text: this.maxNum })
.type(InputType.Number)
.placeholderColor(Color.Gray)
.fontSize(16)
.backgroundColor(Color.White)
.onChange((value: string) => {
this.maxNum = value;
})
}
.width('80%')
.margin(10)
Button('Select Image')
.type(ButtonType.Capsule)
.fontColor(Color.White)
.alignSelf(ItemAlign.Center)
.width('80%')
.margin(10)
.onClick(() => {
void this.selectImage();
})
Button('Image Segmentation')
.type(ButtonType.Capsule)
.fontColor(Color.White)
.alignSelf(ItemAlign.Center)
.width('80%')
.margin(10)
.onClick(() => {
if (!this.chooseImage) {
hilog.error(0x0000, TAG, 'imageSegmentation not have chooseImage');
return;
}
let visionInfo: subjectSegmentation.VisionInfo = {
pixelMap: this.chooseImage
};
let config: subjectSegmentation.SegmentationConfig = {
maxCount: parseInt(this.maxNum),
enableSubjectDetails: true,
enableSubjectForegroundImage: true
};
subjectSegmentation.doSegmentation(visionInfo, config)
.then((data: subjectSegmentation.SegmentationResult) => {
// 拼装分割结果信息
let outputString = `Subject count: ${data.subjectCount}\n`;
outputString += `Max subject count: ${config.maxCount}\n`;
outputString += `Enable subject details: ${config.enableSubjectDetails ? 'Yes' : 'No'}\n\n`;
let segBox: subjectSegmentation.Rectangle = data.fullSubject.subjectRectangle;
outputString += `Full subject box:\nLeft: ${segBox.left}, Top: ${segBox.top}, Width: ${segBox.width}, Height: ${segBox.height}\n\n`;
// 拼装每个主体的详细分割信息
if (config.enableSubjectDetails && data.subjectDetails) {
outputString += 'Individual subject boxes:\n';
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}\n\n`;
}
}
hilog.info(0x0000, TAG, 'Segmentation result: ' + outputString);
this.dataValues = outputString;
if (data.fullSubject && data.fullSubject.foregroundImage) {
this.segmentedImage = data.fullSubject.foregroundImage;
} else {
hilog.error(0x0000, TAG, 'No foreground image in segmentation result');
}
})
.catch((error: BusinessError) => {
hilog.error(0x0000, TAG, `Image segmentation failed errCode: ${error.code}, errMessage: ${error.message}`);
this.dataValues = `Error: ${error.message}`;
this.segmentedImage = undefined;
});
})
}
.width('100%')
.height('80%')
.justifyContent(FlexAlign.Center)
}
private async selectImage() {
let uri = await this.openPhoto();
if (uri === undefined) {
hilog.error(0x0000, TAG, 'uri is undefined');
return;
}
this.loadImage(uri);
}
private async 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();
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(err);
});
});
}
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();
await fileIo.close(fileSource);
}, 100);
}
}