/**
* The number of octaves is too large for input image and should stop processing before it gets
* too small
*/
@Test
public void smallImages() {
SiftImageScaleSpace ss = new SiftImageScaleSpace(1.6f, 5, 4, false);
ImageFloat32 input = new ImageFloat32(10, 15);
GImageMiscOps.fillUniform(input, rand, 0, 100);
ss.constructPyramid(input);
ss.computeFeatureIntensity();
ss.computeDerivatives();
assertEquals(2, ss.actualOctaves);
// images in rest of the octaves should be zero
int index = 3 * 5;
for (; index < ss.scale.length; index++) {
ImageFloat32 s = ss.scale[index];
ImageFloat32 gx = ss.derivX[index];
ImageFloat32 gy = ss.derivY[index];
assertTrue(ImageStatistics.sum(s) == 0);
assertTrue(ImageStatistics.sum(gx) == 0);
assertTrue(ImageStatistics.sum(gy) == 0);
}
index = 3 * 4;
for (; index < ss.dog.length; index++) {
ImageFloat32 dog = ss.dog[index];
assertTrue(ImageStatistics.sum(dog) == 0);
}
}
public static BufferedImage standard(ImageSingleBand<?> src, BufferedImage dst) {
if (src.getDataType().isInteger()) {
ImageInteger srcInt = (ImageInteger) src;
if (src.getDataType().isSigned()) {
double max = GImageStatistics.maxAbs(srcInt);
return colorizeSign(srcInt, dst, (int) max);
} else {
if (src.getDataType().getNumBits() == 8) {
dst = ConvertBufferedImage.convertTo((ImageUInt8) src, dst);
} else {
double max = GImageStatistics.maxAbs(srcInt);
dst = grayUnsigned(srcInt, dst, (int) max);
}
}
} else if (ImageFloat32.class.isAssignableFrom(src.getClass())) {
ImageFloat32 img = (ImageFloat32) src;
float max = ImageStatistics.maxAbs(img);
boolean hasNegative = false;
for (int i = 0; i < img.getHeight(); i++) {
for (int j = 0; j < img.getWidth(); j++) {
if (img.get(j, i) < 0) {
hasNegative = true;
break;
}
}
}
if (hasNegative) return colorizeSign(img, dst, (int) max);
else return grayMagnitude((ImageFloat32) src, dst, max);
}
return dst;
}
@Test
public void performLearning() {
float interp_factor = 0.075f;
ImageFloat32 a = new ImageFloat32(20, 25);
ImageFloat32 b = new ImageFloat32(20, 25);
ImageMiscOps.fill(a, 100);
ImageMiscOps.fill(b, 200);
CirculantTracker<ImageFloat32> alg =
new CirculantTracker<ImageFloat32>(1f / 16, 0.2, 1e-2, 0.075, 1.0, 64, 255, interp);
alg.initialize(a, 0, 0, 20, 25);
// copy its internal value
ImageFloat64 templateC = new ImageFloat64(alg.template.width, alg.template.height);
templateC.setTo(alg.template);
// give it two images
alg.performLearning(b);
// make sure the images aren't full of zero
assertTrue(Math.abs(ImageStatistics.sum(templateC)) > 0.1);
assertTrue(Math.abs(ImageStatistics.sum(alg.template)) > 0.1);
int numNotSame = 0;
// the result should be an average of the two
for (int i = 0; i < a.data.length; i++) {
if (Math.abs(a.data[i] - alg.templateNew.data[i]) > 1e-4) numNotSame++;
// should be more like the original one than the new one
double expected =
templateC.data[i] * (1 - interp_factor) + interp_factor * alg.templateNew.data[i];
double found = alg.template.data[i];
assertEquals(expected, found, 1e-4);
}
// make sure it is actually different
assertTrue(numNotSame > 100);
}
/** 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);
}
}
public static BufferedImage graySign(ImageFloat32 src, BufferedImage dst, float maxAbsValue) {
dst = checkInputs(src, dst);
if (maxAbsValue < 0) maxAbsValue = ImageStatistics.maxAbs(src);
for (int y = 0; y < src.height; y++) {
for (int x = 0; x < src.width; x++) {
float v = src.get(x, y);
int rgb = 127 + (int) (127 * v / maxAbsValue);
dst.setRGB(x, y, rgb << 16 | rgb << 8 | rgb);
}
}
return dst;
}
/** Fits polygons to found contours around binary blobs. */
public static void fitBinaryImage(ImageFloat32 input) {
ImageUInt8 binary = new ImageUInt8(input.width, input.height);
BufferedImage polygon =
new BufferedImage(input.width, input.height, BufferedImage.TYPE_INT_RGB);
// the mean pixel value is often a reasonable threshold when creating a binary image
double mean = ImageStatistics.mean(input);
// create a binary image by thresholding
ThresholdImageOps.threshold(input, binary, (float) mean, true);
// reduce noise with some filtering
ImageUInt8 filtered = BinaryImageOps.erode8(binary, null);
filtered = BinaryImageOps.dilate8(filtered, null);
// Find the contour around the shapes
List<Contour> contours = BinaryImageOps.contour(filtered, 8, null);
// Fit a polygon to each shape and draw the results
Graphics2D g2 = polygon.createGraphics();
g2.setStroke(new BasicStroke(2));
for (Contour c : contours) {
// Fit the polygon to the found external contour. Note loop = true
List<PointIndex_I32> vertexes =
ShapeFittingOps.fitPolygon(c.external, true, toleranceDist, toleranceAngle, 100);
g2.setColor(Color.RED);
VisualizeShapes.drawPolygon(vertexes, true, g2);
// handle internal contours now
g2.setColor(Color.BLUE);
for (List<Point2D_I32> internal : c.internal) {
vertexes = ShapeFittingOps.fitPolygon(internal, true, toleranceDist, toleranceAngle, 100);
VisualizeShapes.drawPolygon(vertexes, true, g2);
}
}
ShowImages.showWindow(polygon, "Binary Blob Contours");
}
