public void compareToNaive(GrayS16 derivX, GrayS16 derivY) {
GrayF32 expected = new GrayF32(derivX.width, derivX.height);
GrayF32 found = new GrayF32(derivX.width, derivX.height);
ImplSsdCornerNaive naive = new ImplSsdCornerNaive(width, height, 3, true);
naive.process(derivX, derivY, expected);
ImplShiTomasiCornerWeighted_S16 fast = new ImplShiTomasiCornerWeighted_S16(3);
fast.process(derivX, derivY, found);
// how the weighted is applied is different between these two verisons, which is why the error
// tolerance is so high
BoofTesting.assertEqualsInner(expected, found, 0.5, 3, 3, true);
}
public static void assertEqualsInner(
ImageBase imgA, ImageBase imgB, double tol, int borderX, int borderY, boolean relative) {
// if no specialized check exists, use a slower generalized approach
if (imgA instanceof ImageSingleBand) {
GImageSingleBand a = FactoryGImageSingleBand.wrap((ImageSingleBand) imgA);
GImageSingleBand b = FactoryGImageSingleBand.wrap((ImageSingleBand) imgB);
for (int y = borderY; y < imgA.height - borderY; y++) {
for (int x = borderX; x < imgA.width - borderX; x++) {
double valA = a.get(x, y).doubleValue();
double valB = b.get(x, y).doubleValue();
double error = Math.abs(valA - valB);
if (relative) {
double denominator = Math.abs(valA) + Math.abs(valB);
if (denominator == 0) denominator = 1;
error /= denominator;
}
if (error > tol)
throw new RuntimeException(
"Values not equal at (" + x + "," + y + ") " + valA + " " + valB);
}
}
} else if (imgA instanceof MultiSpectral) {
MultiSpectral a = (MultiSpectral) imgA;
MultiSpectral b = (MultiSpectral) imgB;
if (a.getNumBands() != b.getNumBands())
throw new RuntimeException("Number of bands not equal");
for (int band = 0; band < a.getNumBands(); band++) {
assertEqualsInner(a.getBand(band), b.getBand(band), tol, borderX, borderY, relative);
}
} else {
throw new RuntimeException("Unknown image type");
}
}
