public static void testTargetFeaturesAgainstImages(
Vector<HaarFeature> features, Vector<IntegralImage> images) {
int numberOfTrue = 0;
int numberOfFalse = 0;
for (IntegralImage ii : images) {
float weightSum = 0.0f;
float sum = 0.0f;
for (HaarFeature hf : features) {
// HaarFeature hf = allFeatures.get(slimFeature.featureNumber);
// hf.threshold = slimFeature.threshold;
float v = hf.weight * ii.evaluateAsClassifier(hf);
sum += v;
weightSum += hf.weight;
}
boolean success = (sum >= weightSum * 0.5f);
// System.out.println("image " + ii.name + " is a " + success + " : " + sum + " > " +
// weightSum*0.5f);
if (success) {
numberOfTrue++;
} else {
numberOfFalse++;
}
}
System.out.println("*************");
System.out.println("true: " + numberOfTrue);
System.out.println("false: " + numberOfFalse);
int min = Math.min(numberOfFalse, numberOfTrue);
int max = Math.max(numberOfFalse, numberOfTrue);
float percentError = min * 100.0f / max;
System.out.println("percentError = " + percentError);
}
