尝试找出一种在目标图像上实际进行人脸识别时收集置信度的方法。我搜索了一些示例,但没有找到我可以看到的实现方法。感谢所有帮助,谢谢大家。
public static void facecompare() {
String trainingDir = "C:/TrainingDirectory"; //training directory
IplImage testImage = cvLoadImage("C:/TargetImages/boland_straight_happy_open_4.pgm"); //the target image
File root = new File(trainingDir);
FilenameFilter pngFilter = new FilenameFilter() {
public boolean accept(File dir, String name) {
return name.toLowerCase().endsWith(".pgm");
}
};
File[] imageFiles = root.listFiles(pngFilter);
MatVector images = new MatVector(imageFiles.length);
int[] labels = new int[imageFiles.length];
int counter = 0;
int label;
IplImage img;
IplImage grayImg;
for (File image : imageFiles) {
img = cvLoadImage(image.getAbsolutePath());
label = Integer.parseInt(image.getName().split("\\-")[0]);
grayImg = IplImage.create(img.width(), img.height(), IPL_DEPTH_8U, 1);
cvCvtColor(img, grayImg, CV_BGR2GRAY);
images.put(counter, grayImg);
labels[counter] = label;
counter++;
}
IplImage greyTestImage = IplImage.create(testImage.width(), testImage.height(), IPL_DEPTH_8U, 1);
// FaceRecognizer faceRecognizer = createFisherFaceRecognizer();
// FaceRecognizer faceRecognizer = createEigenFaceRecognizer();
FaceRecognizer faceRecognizer = createLBPHFaceRecognizer();
faceRecognizer.train(images, labels);
cvCvtColor(testImage, greyTestImage, CV_BGR2GRAY);
int predictedLabel = faceRecognizer.predict(greyTestImage);
System.out.println("Predicted label: " + predictedLabel);
}
最佳答案
还有另一种预测方法可以返回置信度:
// pointer-like output parameters
// only the first element of these arrays will be changed
int[] plabel = new int[1];
double[] pconfidence = new double[1];
faceRecognizer.predict(greyTestImage, plabel, pconfidence);
int predictedLabel = plabel[0];
double confidence = pconfidence[0];
关于opencv - 借助JAVACV计划树立信心,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/15599475/