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import java.io.File;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import javax.imageio.ImageIO;
import org.codehaus.jackson.map.introspect.Annotated;
import org.openimaj.data.dataset.GroupedDataset;
import org.openimaj.data.dataset.ListDataset;
import org.openimaj.data.dataset.VFSGroupDataset;
import org.openimaj.experiment.dataset.split.GroupedRandomSplitter;
import org.openimaj.experiment.dataset.util.DatasetAdaptors;
import org.openimaj.feature.DoubleFV;
import org.openimaj.feature.DoubleFVComparison;
import org.openimaj.image.DisplayUtilities;
import org.openimaj.image.FImage;
import org.openimaj.image.ImageUtilities;
import org.openimaj.image.model.EigenImages;
import org.openimaj.image.processing.face.alignment.RotateScaleAligner;
import org.openimaj.image.processing.face.detection.HaarCascadeDetector;
import org.openimaj.image.processing.face.detection.keypoints.FKEFaceDetector;
import org.openimaj.image.processing.face.detection.keypoints.KEDetectedFace;
import org.openimaj.image.processing.face.recognition.EigenFaceRecogniser;
import org.openimaj.image.processing.face.recognition.FaceRecognitionEngine;
import org.openimaj.ml.annotation.AnnotatedObject;
import org.openimaj.ml.annotation.ScoredAnnotation;
import org.openimaj.util.pair.IndependentPair;

public class Demo {

  public static void main(String ... s) throws IOException {

    FKEFaceDetector faceDetector = new FKEFaceDetector(new HaarCascadeDetector());

    EigenFaceRecogniser<KEDetectedFace, Integer> faceRecognizer = EigenFaceRecogniser.create(20, new RotateScaleAligner(), 1, DoubleFVComparison.CORRELATION, 0.9f);

    FaceRecognitionEngine<KEDetectedFace, Integer> faceEngine = FaceRecognitionEngine.create(faceDetector, faceRecognizer);


    for(int i = 1; i < 15; i ++){
      System.out.println(i);
      FImage pamu = ImageUtilities.createFImage(ImageIO.read(new File("/home/nagarjuna/Pictures/Webcam/"+i+".jpg")));
      List<KEDetectedFace> faces = faceEngine.getDetector().detectFaces(pamu);
      if(faces.size() > 0)
      faceEngine.train(faces.get(0), i);
    }

    FImage pamu = ImageUtilities.createFImage(ImageIO.read(new File("/home/nagarjuna/Pictures/Webcam/"+12+".jpg")));

    List<KEDetectedFace> faces = faceEngine.getDetector().detectFaces(pamu);

    List<IndependentPair<KEDetectedFace, ScoredAnnotation<Integer>>> rfaces = faceEngine.recogniseBest(faces.get(0).getFacePatch());
    ScoredAnnotation<Integer> score = rfaces.get(0).getSecondObject();
    DisplayUtilities.display(rfaces.get(0).getFirstObject().getFacePatch());
    if(score != null) {
      System.out.println("confidence: "+score.confidence);
      System.out.println("annotation: "+score.annotation);
    }else {
      System.out.println("score is null");
    }
  }
}

输出：

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score is null
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1 回答 1

1

不幸的是，OpenIMAJ 在课堂上处理相似性度量（而不是距离度量）的方式似乎出现了一个错误KNNAnnotator。已提交修复（修订 #2560），并且包含它的新快照（版本 1.3-SNAPSHOT）应该在几个小时内可用。目前，您应该能够更改DoubleFVComparison.CORRELATION为DoubleFVComparison.EUCLIDEAN，然后它应该可以工作。

我注意到您的代码中可能应该修复的其他一些内容：

  • 而不是ImageUtilities.createFImage(ImageIO.read(new File("...")));，您应该使用ImageUtilities.readF(new File("..."));它来解决 ImageIO 中的许多记录错误，尤其是在 jpeg 读取方面，并且您还可以获得对许多其他图像文件格式的支持。
  • 您无需自己手动对查询图像进行人脸检测；该faceEngine.recogniseBest(FImage)方法在内部为您执行此操作（连同对齐）
于 2014-07-16T13:51:07.023 回答