public void recognizeFileList(final String szFileTest) {
System.out.println("===========================================");
System.out.println("recognizing faces indexed from " + szFileTest);
int i = 0;
int nTestFaces = 0; // the number of test images
CvMat trainPersonNumMat; // the person numbers during training
float[] projectedTestFace;
String answer;
int nCorrect = 0;
int nWrong = 0;
double timeFaceRecognizeStart;
double tallyFaceRecognizeTime;
float confidence = 0.0f;
// load test images and ground truth for person number
testFaceImgArr = loadFaceImgArray(szFileTest);
nTestFaces = testFaceImgArr.length;
System.out.println(nTestFaces + " test faces loaded");
// load the saved training data
trainPersonNumMat = loadTrainingData();
if (trainPersonNumMat == null) {
return;
}
// project the test images onto the PCA subspace
projectedTestFace = new float[nEigens];
timeFaceRecognizeStart = (double) cvGetTickCount(); // Record the timing.
for (i = 0; i < nTestFaces; i++) {
int iNearest;
int nearest;
int truth;
// project the test image onto the PCA subspace
cvEigenDecomposite(
testFaceImgArr[i], // obj
nEigens, // nEigObjs
eigenVectArr, // eigInput (Pointer)
0, // ioFlags
null, // userData
pAvgTrainImg, // avg
projectedTestFace); // coeffs
// LOGGER.info("projectedTestFace\n" + floatArrayToString(projectedTestFace));
final FloatPointer pConfidence = new FloatPointer(confidence);
iNearest = findNearestNeighbor(projectedTestFace, new FloatPointer(pConfidence));
confidence = pConfidence.get();
truth = personNumTruthMat.data_i().get(i);
nearest = trainPersonNumMat.data_i().get(iNearest);
if (nearest == truth) {
answer = "Correct";
nCorrect++;
} else {
answer = "WRONG!";
nWrong++;
}
System.out.println(
"nearest = "
+ nearest
+ ", Truth = "
+ truth
+ " ("
+ answer
+ "). Confidence = "
+ confidence);
}
tallyFaceRecognizeTime = (double) cvGetTickCount() - timeFaceRecognizeStart;
if (nCorrect + nWrong > 0) {
System.out.println(
"TOTAL ACCURACY: "
+ (nCorrect * 100 / (nCorrect + nWrong))
+ "% out of "
+ (nCorrect + nWrong)
+ " tests.");
System.out.println(
"TOTAL TIME: "
+ (tallyFaceRecognizeTime / (cvGetTickFrequency() * 1000.0 * (nCorrect + nWrong)))
+ " ms average.");
}
}
/* From a normalized image file to recognized if match current trained data.
*/
public void recognize(String tmpDetectImageOutput, String trainedOutput, String personName) {
File folder = new File(tmpDetectImageOutput);
File[] listOfFiles = folder.listFiles();
ArrayList<String> testFaceFileNames = new ArrayList<String>();
String answer = "";
// load image to testFaces array list
for (int i = 0; i < listOfFiles.length; i++) {
if (listOfFiles[i].isFile()) {
String file = listOfFiles[i].getName();
String filepath = tmpDetectImageOutput + "/" + file;
IplImage tmpImage = cvLoadImage(filepath, CV_LOAD_IMAGE_GRAYSCALE);
if (tmpImage != null) {
testFaces.add(tmpImage);
testFaceFileNames.add(filepath);
}
}
}
CvMat trainPersonNumMat = loadTrainingData(trainedOutput, personName);
// int ntestfaces = testFaces.size() ;
int nTestFaces = testFaces.size();
LOGGER.info(trainedOutput + "/" + personName + ".xml");
System.out.println("total: " + nTestFaces + " to be tested latter...");
personNumTruthMat = cvCreateMat(1, nTestFaces, CV_32SC1); // type, 32-
float[] projectedTestFace = new float[nEigens];
float confidence = 0.0f;
int nCorrect = 0;
int nWrong = 0;
double timeFaceRecognizeStart = (double) cvGetTickCount(); // supposedly to record the timing??
for (int i = 0; i < nTestFaces; i++) {
int iNearest;
int nearest;
int truth;
// project the test image onto the PCA subspace
LOGGER.info("before find decomposite..");
cvEigenDecomposite(
testFaces.get(i),
nEigens, // nEigObjs
eigenVectArr, // eigInput (Pointer)
0, // ioFlags
null, // userData
pAvgTrainImg, // avg
projectedTestFace); // coeffs
// LOGGER.info("projectedTestFace\n" + floatArrayToString(projectedTestFace));
final FloatPointer pConfidence = new FloatPointer(confidence);
LOGGER.info("before find nearest...");
iNearest = findNearestNeighbor(projectedTestFace, new FloatPointer(pConfidence));
confidence = pConfidence.get();
truth = personNumTruthMat.data_i().get(i);
nearest = trainPersonNumMat.data_i().get(iNearest);
if (nearest == truth) {
answer = "Correct";
nCorrect++;
} else {
answer = "WRONG!";
nWrong++;
}
LOGGER.info(testFaceFileNames.get(i));
LOGGER.info(
"nearest = "
+ nearest
+ ", Truth = "
+ truth
+ " ("
+ answer
+ "). Confidence = "
+ confidence);
}
}