/** See how well it processes an image which is not an GrayS32 */
@Test
public void checkOtherType() {
GrayS32 orig = new GrayS32(width, height);
GImageMiscOps.fillUniform(orig, rand, 0, 20);
GrayU8 orig8 = ConvertImage.convert(orig, (GrayU8) null);
int N = 3;
ImageDimension dimen = UtilWavelet.transformDimension(orig, N);
GrayS32 found = new GrayS32(dimen.width, dimen.height);
GrayS32 expected = new GrayS32(dimen.width, dimen.height);
WaveletDescription<WlCoef_I32> desc =
FactoryWaveletDaub.biorthogonal_I32(5, BorderType.REFLECT);
GrayS32 storage = new GrayS32(dimen.width, dimen.height);
WaveletTransformOps.transformN(desc, orig.clone(), expected, storage, N);
WaveletTransformInt<GrayU8> alg = new WaveletTransformInt<>(desc, N, 0, 255, GrayU8.class);
alg.transform(orig8, found);
// see if the two techniques produced the same results
BoofTesting.assertEquals(expected, found, 0);
// see if it can convert it back
GrayU8 reconstructed = new GrayU8(width, height);
alg.invert(found, reconstructed);
BoofTesting.assertEquals(orig8, reconstructed, 0);
// make sure the input has not been modified
BoofTesting.assertEquals(expected, found, 0);
}
@Test
public void compareToWaveletTransformOps() {
GrayS32 orig = new GrayS32(width, height);
GImageMiscOps.fillUniform(orig, rand, 0, 20);
GrayS32 origCopy = orig.clone();
int N = 3;
ImageDimension dimen = UtilWavelet.transformDimension(orig, N);
GrayS32 found = new GrayS32(dimen.width, dimen.height);
GrayS32 expected = new GrayS32(dimen.width, dimen.height);
WaveletDescription<WlCoef_I32> desc =
FactoryWaveletDaub.biorthogonal_I32(5, BorderType.REFLECT);
GrayS32 storage = new GrayS32(dimen.width, dimen.height);
WaveletTransformOps.transformN(desc, orig.clone(), expected, storage, N);
WaveletTransformInt<GrayS32> alg = new WaveletTransformInt<>(desc, N, 0, 255, GrayS32.class);
alg.transform(orig, found);
// make sure the original input was not modified like it is in WaveletTransformOps
BoofTesting.assertEquals(origCopy, orig, 0);
// see if the two techniques produced the same results
BoofTesting.assertEquals(expected, found, 0);
// test inverse transform
GrayS32 reconstructed = new GrayS32(width, height);
alg.invert(found, reconstructed);
BoofTesting.assertEquals(orig, reconstructed, 0);
// make sure the input has not been modified
BoofTesting.assertEquals(expected, found, 0);
}
public static <T extends ImageSingleBand> T createSingleBand(
Class<T> type, int width, int height) {
type = BoofTesting.convertGenericToSpecificType(type);
if (type == ImageUInt8.class) {
return (T) new ImageUInt8(width, height);
} else if (type == ImageSInt8.class) {
return (T) new ImageSInt8(width, height);
} else if (type == ImageSInt16.class) {
return (T) new ImageSInt16(width, height);
} else if (type == ImageUInt16.class) {
return (T) new ImageUInt16(width, height);
} else if (type == ImageSInt32.class) {
return (T) new ImageSInt32(width, height);
} else if (type == ImageSInt64.class) {
return (T) new ImageSInt64(width, height);
} else if (type == ImageFloat32.class) {
return (T) new ImageFloat32(width, height);
} else if (type == ImageFloat64.class) {
return (T) new ImageFloat64(width, height);
} else if (type == ImageInteger.class) {
// ImageInteger is a generic type, so just create something
return (T) new ImageSInt32(width, height);
}
throw new RuntimeException("Unknown type: " + type.getSimpleName());
}
/** See if accessing the image edge causes it to blow up. */
@Test
public void get_edges() {
T img = createImage(width, height);
GImageMiscOps.fillUniform(img, rand, 0, 100);
BoofTesting.checkSubImage(this, "get_edges", false, img);
}
/** The XY and YX second derivatives should be indential */
private void testSecondDerivative(Method m1, Method m2) {
Class params[] = m1.getParameterTypes();
ImageGray input = GeneralizedImageOps.createSingleBand(params[0], width, height);
ImageGray derivX = GeneralizedImageOps.createSingleBand(params[1], width, height);
ImageGray derivY = GeneralizedImageOps.createSingleBand(params[2], width, height);
ImageGray derivXX = GeneralizedImageOps.createSingleBand(params[1], width, height);
ImageGray derivYY = GeneralizedImageOps.createSingleBand(params[2], width, height);
ImageGray derivXY = GeneralizedImageOps.createSingleBand(params[1], width, height);
ImageGray derivYX = GeneralizedImageOps.createSingleBand(params[1], width, height);
GImageMiscOps.fillUniform(input, rand, 0, 40);
Object border;
if (params[3] == ImageBorder_F32.class) {
border = new ImageBorder1D_F32(BorderIndex1D_Wrap.class);
} else {
border = new ImageBorder1D_S32(BorderIndex1D_Wrap.class);
}
try {
m1.invoke(null, input, derivX, derivY, border);
m2.invoke(null, derivX, derivXX, derivXY, border);
m2.invoke(null, derivY, derivYX, derivYY, border);
} catch (IllegalAccessException | InvocationTargetException e) {
throw new RuntimeException(e);
}
// BoofTesting.printDiff(derivXY,derivYX);
BoofTesting.assertEquals(derivXY, derivYX, 1e-3f);
}
/**
* Creates a random image and looks for corners in it. Sees if the naive and fast algorithm
* produce exactly the same results.
*/
@Test
public void compareToNaive() {
GrayU8 img = new GrayU8(width, height);
ImageMiscOps.fillUniform(img, new Random(0xfeed), 0, 100);
GrayS16 derivX = new GrayS16(img.getWidth(), img.getHeight());
GrayS16 derivY = new GrayS16(img.getWidth(), img.getHeight());
GradientSobel.process(img, derivX, derivY, new ImageBorder1D_S32(BorderIndex1D_Extend.class));
BoofTesting.checkSubImage(this, "compareToNaive", true, derivX, derivY);
}
public static void applyInnerMethod(
String functionName,
WaveletDescription<?> desc,
ImageSingleBand input,
ImageSingleBand output) {
Method m;
Object args[];
if (functionName.contains("Inverse")) {
WlCoef coef = desc.getInverse().getInnerCoefficients();
m =
BoofTesting.findMethod(
ImplWaveletTransformInner.class,
functionName,
coef.getClass(),
input.getClass(),
output.getClass());
args = new Object[] {coef, input, output};
} else {
WlCoef coef = desc.getForward();
m =
BoofTesting.findMethod(
ImplWaveletTransformInner.class,
functionName,
coef.getClass(),
input.getClass(),
output.getClass());
args = new Object[] {coef, input, output};
}
try {
m.invoke(null, args);
} catch (InvocationTargetException e) {
throw new RuntimeException(e);
} catch (IllegalAccessException e) {
throw new RuntimeException(e);
}
}
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);
}
/**
* Converts an image from one type to another type.
*
* @param src Input image. Not modified.
* @param dst Converted output image. Modified.
* @return Converted image.
*/
@SuppressWarnings({"unchecked"})
public static void convert(ImageSingleBand<?> src, ImageSingleBand<?> dst) {
if (src.getClass() == dst.getClass()) {
((ImageSingleBand) dst).setTo(src);
return;
}
Method m =
BoofTesting.findMethod(ImplConvertImage.class, "convert", src.getClass(), dst.getClass());
try {
m.invoke(null, src, dst);
} catch (IllegalAccessException e) {
throw new RuntimeException(e);
} catch (InvocationTargetException e) {
throw new RuntimeException(e);
}
}
private void compareToNaive(
Image left, Image right, int minDisparity, int maxDisparity, int radiusX, int radiusY) {
int w = left.width;
int h = left.height;
DisparityScoreSadRect<Image, Disparity> alg =
createAlg(minDisparity, maxDisparity, radiusX, radiusY, compDisp);
StereoDisparityWtoNaive<Image> naive =
new StereoDisparityWtoNaive<Image>(minDisparity, maxDisparity, radiusX, radiusY);
Disparity found = GeneralizedImageOps.createSingleBand(disparityType, w, h);
ImageFloat32 expected = new ImageFloat32(w, h);
alg.process(left, right, found);
naive.process(left, right, expected);
BoofTesting.assertEquals(found, expected, 1);
}
/** Process two images, one is a sub-image of the first. See if it produces the same results */
@Test
public void checkSubImage() {
SiftImageScaleSpace ss1 = new SiftImageScaleSpace(1.6f, 5, 4, false);
SiftImageScaleSpace ss2 = new SiftImageScaleSpace(1.6f, 5, 4, false);
ImageFloat32 input = new ImageFloat32(60, 70);
GImageMiscOps.fillUniform(input, rand, 0, 100);
ImageFloat32 sub = BoofTesting.createSubImageOf(input);
ss1.constructPyramid(input);
ss2.constructPyramid(sub);
for (int index = 0; index < ss1.scale.length; index++) {
ImageFloat32 s1 = ss1.scale[index];
ImageFloat32 s2 = ss2.scale[index];
float sum1 = ImageStatistics.sum(s1);
float sum2 = ImageStatistics.sum(s2);
assertTrue(sum1 != 0);
assertEquals(sum1, sum2, 1e-6);
}
}
@Test
public void border() {
BoofTesting.checkSubImage(this, "checkBorder", false, img, 0, 0, 5, 7);
BoofTesting.checkSubImage(this, "checkBorder", false, img, img.width - 1, img.height - 1, 5, 7);
BoofTesting.checkSubImage(this, "checkBorder", false, img, 100, 200, 5, 7);
}
@Test
public void inner() {
BoofTesting.checkSubImage(this, "checkInner", false, img, 4, 6, 7, 5);
BoofTesting.checkSubImage(this, "checkInner", false, img, 7, 3, 4, 5);
BoofTesting.checkSubImage(this, "checkInner", false, img, 4, 6, 2, 4);
}
