AI能力：objectDetection（多目标识别）

多目标识别服务提供了从图像中识别多个目标的能力。通过拍照、录像等光学输入方式，把各种场景下的图像转化为数字图像信息，再利用AI底层能力对图像进行分析，从中定位并识别出多个感兴趣的目标对象，如人脸、动物、植物等，便于用户提取目标的类别、边框位置、置信度等信息。

目前本服务支持识别的目标类型包括：风景，动物，植物，建筑，人脸，表格，文本，人头，猫头，狗头，食物，汽车，人体，文档，卡证。

示例：

import { objectDetection, visionBase } 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';
let imageSource: image.ImageSource | undefined = undefined;
let chooseImage: image.PixelMap | undefined = undefined;
// 创建对象检测器
let detector: objectDetection.ObjectDetector | undefined = undefined;
async function createDetector() {
  detector = await objectDetection.ObjectDetector.create();
  hilog.info(0x0000, 'objectDetectionSample', 'Object detector created successfully');
}
@Entry
@Component
struct Page {
  build() {
    Column(){
      Button('Start').onClick(() => {
        // 将图片转换为PixelMap，可以通过图库获取
        let photoPicker: photoAccessHelper.PhotoViewPicker = new photoAccessHelper.PhotoViewPicker();
        photoPicker.select({
          MIMEType: photoAccessHelper.PhotoViewMIMETypes.IMAGE_TYPE,
          maxSelectNumber: 1
        }).then((res: photoAccessHelper.PhotoSelectResult) => {
          let uri = res.photoUris[0];
          if (uri === undefined) {
            hilog.info(0x0000, 'objectDetectionSample', 'uri is undefined');
            return
          }
          setTimeout(async () => {
            let file = await fileIo.open(uri, fileIo.OpenMode.READ_ONLY);
            imageSource = image.createImageSource(file.fd);
            chooseImage = await imageSource.createPixelMap();
            hilog.info(0x0000, 'objectDetectionSample', 'chooseImage:', chooseImage);
            if (!chooseImage) {
              return
            }
            // 创建检测器
            await createDetector();
            if (!detector) {
              hilog.error(0x0000, 'objectDetectionSample', 'Detector is not initialized');
              return;
            }
            // 调用对象检测接口
            let request: visionBase.Request = {
              inputData: { pixelMap: chooseImage },
              scene: visionBase.SceneMode.FOREGROUND
            };
            let response: objectDetection.ObjectDetectionResponse = await detector.process(request);
            if (response.objects.length === 0) {
              hilog.info(0x0000, 'objectDetectionSample', 'No objects detected in the image.');
            } else {
              let objectString = JSON.stringify(response.objects);
              hilog.info(0x0000, 'objectDetectionSample', 'Detected objects: ' + objectString);
            }
            // 清理资源
            if (chooseImage && imageSource) {
              chooseImage.release();
              imageSource.release();
            }
            if (file) {
              try {
                await fileIo.close(file);
              } catch (err) {
                hilog.error(0x0000, 'objectDetectionSample', `Failed to close fileSource. Code: ${err.code}，message: ${err.message}`);
              }
            }
            if (detector) {
              await detector.destroy();
              hilog.info(0x0000, 'objectDetectionSample', 'Object detector destroyed successfully');
            }
          }, 100);
        }).catch((err: BusinessError) => {
          hilog.error(0x0000, 'objectDetectionSample', `Failed to get photo image uri. code: ${err.code}，message: ${err.message}`);
        });
      })
    }
  }
}

但是无法实现你所说的计算卡路里功能。