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可同时检测出给定图片中的各种物体,包括风景、动物、植物、建筑、人脸、表格、文本等位置,并框选出物体。
效果如下图所示:

在使用多目标识别时,将实现多目标识别相关的类添加至工程。
import { image } from '@kit.ImageKit';
import { hilog } from '@kit.PerformanceAnalysisKit';
import { BusinessError } from '@kit.BasicServicesKit';
import { fileIo } from '@kit.CoreFileKit';
import { objectDetection, visionBase } from '@kit.CoreVisionKit';
import { photoAccessHelper } from '@kit.MediaLibraryKit';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,为后续检测接口准备输入数据。
Button('选择图片')
.type(ButtonType.Capsule)
.fontColor(Color.White)
.alignSelf(ItemAlign.Center)
.width('80%')
.margin(10)
.onClick(() => {
// 拉起图库,获取图片资源
void this.selectImage();
}) 选择图片与解码图片的方法实现如下:
private async selectImage() {
let uri = await this.openPhoto();
if (!uri) {
hilog.error(0x0000, 'objectDetectSample', 'Failed to define uri.');
return;
}
this.loadImage(uri);
}
private async openPhoto(): Promise<string> {
return new Promise<string>((resolve, reject) => {
let photoPicker: photoAccessHelper.PhotoViewPicker = new photoAccessHelper.PhotoViewPicker();
photoPicker.select({
MIMEType: photoAccessHelper.PhotoViewMIMETypes.IMAGE_TYPE,
maxSelectNumber: 1
}).then(res => {
resolve(res.photoUris[0]);
}).catch((err: BusinessError) => {
hilog.error(0x0000, 'objectDetectSample', `Failed to get photo image uri. code: ${err.code}, message: ${err.message}`);
reject(err);
});
});
}
private loadImage(name: string) {
setTimeout(async () => {
let fileSource = await fileIo.open(name, fileIo.OpenMode.READ_ONLY);
this.imageSource = image.createImageSource(fileSource.fd);
this.chooseImage = await this.imageSource.createPixelMap();
await fileIo.close(fileSource);
}, 100);
}实例化visionBase.Request对象,将PixelMap封装为输入参数;调用ObjectDetector.create()创建检测器实例,再调用其process方法,获取图片中各物体的位置与类别信息,并将结果展示在界面上。
Button('开始多目标识别')
.type(ButtonType.Capsule)
.fontColor(Color.White)
.alignSelf(ItemAlign.Center)
.width('80%')
.margin(10)
.onClick(() => {
// 调用封装的异步识别函数
void this.handleMultiObjectDetection();
}) 多目标识别的方法实现如下:
private async handleMultiObjectDetection() {
try {
if (!this.chooseImage) {
hilog.error(0x0000, 'objectDetectSample', 'Failed to choose image.');
return;
}
// 调用多目标检测接口
let request: visionBase.Request = {
inputData: { pixelMap: this.chooseImage }
};
let detector = await objectDetection.ObjectDetector.create();
let data: objectDetection.ObjectDetectionResponse = await detector.process(request);
await detector.destroy();
if (!data) {
hilog.error(0x0000, 'objectDetectSample', 'Invalid object detection result');
return;
}
let objectJson = JSON.stringify(data);
hilog.info(0x0000, 'objectDetectSample', `Succeeded in object detection: ${objectJson}`);
this.dataValues = objectJson;
} catch (err) {
const error = err as BusinessError;
hilog.error(0x0000, 'objectDetectSample', `Object detection error. Code: ${error.code}, message: ${error.message}`);
}
}import { image } from '@kit.ImageKit';
import { hilog } from '@kit.PerformanceAnalysisKit';
import { BusinessError } from '@kit.BasicServicesKit';
import { fileIo } from '@kit.CoreFileKit';
import { objectDetection, visionBase } from '@kit.CoreVisionKit';
import { photoAccessHelper } from '@kit.MediaLibraryKit';
@Entry
@Component
struct Index {
private imageSource: image.ImageSource | undefined = undefined;
@State chooseImage: PixelMap | undefined = undefined;
@State dataValues: string = '';
build() {
Column() {
Image(this.chooseImage)
.objectFit(ImageFit.Fill)
.height('60%')
Text(this.dataValues)
.copyOption(CopyOptions.LocalDevice)
.height('15%')
.margin(10)
.width('60%')
Button('选择图片')
.type(ButtonType.Capsule)
.fontColor(Color.White)
.alignSelf(ItemAlign.Center)
.width('80%')
.margin(10)
.onClick(() => {
// 拉起图库
void this.selectImage();
})
Button('开始多目标识别')
.type(ButtonType.Capsule)
.fontColor(Color.White)
.alignSelf(ItemAlign.Center)
.width('80%')
.margin(10)
.onClick(() => {
// 调用封装的异步识别函数
void this.handleMultiObjectDetection();
})
}
.width('100%')
.height('100%')
.justifyContent(FlexAlign.Center)
}
// 封装多目标识别的异步逻辑
private async handleMultiObjectDetection() {
try {
if (!this.chooseImage) {
hilog.error(0x0000, 'objectDetectSample', 'Failed to choose image.');
return;
}
// 调用多目标检测接口
let request: visionBase.Request = {
inputData: { pixelMap: this.chooseImage }
};
let detector = await objectDetection.ObjectDetector.create();
let data: objectDetection.ObjectDetectionResponse = await detector.process(request);
await detector.destroy();
if (!data) {
hilog.error(0x0000, 'objectDetectSample', 'Invalid object detection result');
return;
}
let objectJson = JSON.stringify(data);
hilog.info(0x0000, 'objectDetectSample', `Succeeded in object detection: ${objectJson}`);
this.dataValues = objectJson;
} catch (err) {
hilog.error(0x0000, 'objectDetectSample', `Object detection error: ${err}`);
}
}
private async selectImage() {
let uri = await this.openPhoto();
if (!uri) {
hilog.error(0x0000, 'objectDetectSample', 'Failed to define uri.');
return;
}
this.loadImage(uri);
}
private async openPhoto(): Promise<string> {
return new Promise<string>((resolve, reject) => {
let photoPicker: photoAccessHelper.PhotoViewPicker = new photoAccessHelper.PhotoViewPicker();
photoPicker.select({
MIMEType: photoAccessHelper.PhotoViewMIMETypes.IMAGE_TYPE,
maxSelectNumber: 1
}).then(res => {
resolve(res.photoUris[0]);
}).catch((err: BusinessError) => {
hilog.error(0x0000, 'objectDetectSample', `Failed to get photo image uri. code: ${err.code}, message: ${err.message}`);
reject(err);
});
});
}
private loadImage(name: string) {
setTimeout(async () => {
let fileSource = await fileIo.open(name, fileIo.OpenMode.READ_ONLY);
this.imageSource = image.createImageSource(fileSource.fd);
this.chooseImage = await this.imageSource.createPixelMap();
await fileIo.close(fileSource);
}, 100);
}
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