/** Checks to see if the two ways of specifying interpolation work */
@Test
public void scale_InterpTypeStyle() {
ImageFloat32 input = new ImageFloat32(width, height);
ImageFloat32 output = new ImageFloat32(width, height);
GImageMiscOps.fillUniform(input, rand, 0, 100);
DistortImageOps.scale(input, output, TypeInterpolate.BILINEAR);
InterpolatePixel<ImageFloat32> interp = FactoryInterpolation.bilinearPixel(input);
interp.setImage(input);
float scaleX = (float) input.width / (float) output.width;
float scaleY = (float) input.height / (float) output.height;
if (input.getTypeInfo().isInteger()) {
for (int i = 0; i < output.height; i++) {
for (int j = 0; j < output.width; j++) {
float val = interp.get(j * scaleX, i * scaleY);
assertEquals((int) val, output.get(j, i), 1e-4);
}
}
} else {
for (int i = 0; i < output.height; i++) {
for (int j = 0; j < output.width; j++) {
float val = interp.get(j * scaleX, i * scaleY);
assertEquals(val, output.get(j, i), 1e-4);
}
}
}
}
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;
}
private void constructHistograms(double c_x, double c_y, double scale, double orientation) {
double c = Math.cos(orientation);
double s = Math.sin(orientation);
int gridRadius = gridWidth / 2;
// This is the distance between samples
// The size is computed by finding the width of one block in the grid, then dividing by the
// number of samples along that side
double sampleUnit = (2.0 * scale * sigmaToRadius) / numSamples;
// how wide a grid cell is in pixels
double gridCellLength = numSamples * sampleUnit;
int gridCellLengthI = (int) (gridCellLength + 0.5); // round to int
// System.out.println("-----------------------------------------");
// System.out.println(" cell length "+gridCellLength);
// System.out.println(" sampleUnit "+sampleUnit);
int allSampleIndex = 0;
for (int gy = 0; gy < gridWidth; gy++) {
double gridY = (gy - gridRadius) * gridCellLength;
for (int gx = 0; gx < gridWidth; gx++) {
// top left coordinate of grid in pixels
double gridX = (gx - gridRadius) * gridCellLength;
// TODO Sample all pixels here
for (int sy = 0; sy < numSamples; sy++) {
double y = sy * sampleUnit + gridY;
for (int sx = 0; sx < numSamples; sx++, allSampleIndex++) {
// Sample point in pixels in grid coordinate system
double x = sx * sampleUnit + gridX;
// Rotate and translate into image pixel coordinates, then round
int px = (int) (x * c - y * s + c_x + 0.5);
int py = (int) (x * s + y * c + c_y + 0.5);
if (image.isInBounds(px, py)) {
double dx = derivX.unsafe_get(px, py);
double dy = derivY.unsafe_get(px, py);
// Gaussian weighting applied to whole sample area
double w = gridWeights[allSampleIndex];
// rotate derivative into grid coordinate system
double adjX = (dx * c + dy * s) * w;
double adjY = (-dx * s + dy * c) * w;
addToHistograms(
gx - gridRadius,
gy - gridRadius,
x / gridCellLength,
y / gridCellLength,
adjX,
adjY);
}
}
}
}
}
}
public void checkInner(ImageFloat32 image, int c_x, int c_y, int w, int h) {
ImplDescribePointPixelRegionNCC_F32 alg = new ImplDescribePointPixelRegionNCC_F32(w, h);
NccFeature desc = new NccFeature(alg.getDescriptorLength());
alg.setImage(image);
assertTrue(alg.isInBounds(c_x, c_y));
alg.process(c_x, c_y, desc);
int y0 = c_y - h / 2;
int x0 = c_x - w / 2;
double mean = 0;
for (int y = y0; y < y0 + h; y++) {
for (int x = x0; x < x0 + w; x++) {
mean += image.get(x, y);
}
}
mean /= w * h;
double variance = 0;
for (int y = y0; y < y0 + h; y++) {
for (int x = x0; x < x0 + w; x++) {
double a = image.get(x, y) - mean;
variance += a * a;
}
}
variance /= w * h;
assertEquals(desc.mean, mean, 1e-8);
assertEquals(desc.sigma, Math.sqrt(variance), 1e-8);
int index = 0;
for (int y = y0; y < y0 + h; y++) {
for (int x = x0; x < x0 + w; x++, index++) {
assertEquals(image.get(x, y) - mean, desc.value[index], 1e-4);
}
}
}
/**
* Runs a canny edge detector on the input image given the provided thresholds. If configured to
* save a list of trace points then the output image is optional.
*
* <p>NOTE: Input and output can be the same instance, if the image type allows it.
*
* @param input Input image. Not modified.
* @param threshLow Lower threshold. >= 0.
* @param threshHigh Upper threshold. >= 0.
* @param output (Might be option) Output binary image. Edge pixels are marked with 1 and
* everything else 0.
*/
public void process(T input, float threshLow, float threshHigh, ImageUInt8 output) {
if (threshLow < 0 || threshHigh < 0)
throw new IllegalArgumentException("Threshold must be >= zero!");
if (hysteresisMark != null) {
if (output == null)
throw new IllegalArgumentException(
"An output image must be specified when configured to mark edge points");
}
// setup internal data structures
blurred.reshape(input.width, input.height);
derivX.reshape(input.width, input.height);
derivY.reshape(input.width, input.height);
intensity.reshape(input.width, input.height);
suppressed.reshape(input.width, input.height);
angle.reshape(input.width, input.height);
direction.reshape(input.width, input.height);
work.reshape(input.width, input.height);
// run canny edge detector
blur.process(input, blurred);
gradient.process(blurred, derivX, derivY);
GGradientToEdgeFeatures.intensityAbs(derivX, derivY, intensity);
GGradientToEdgeFeatures.direction(derivX, derivY, angle);
GradientToEdgeFeatures.discretizeDirection4(angle, direction);
GradientToEdgeFeatures.nonMaxSuppression4(intensity, direction, suppressed);
performThresholding(threshLow, threshHigh, output);
}
/** Sets a rectangle inside the image with the specified value. */
public static void fillRectangle(
ImageFloat32 img, float value, int x0, int y0, int width, int height) {
int x1 = x0 + width;
int y1 = y0 + height;
for (int y = y0; y < y1; y++) {
for (int x = x0; x < x1; x++) {
if (img.isInBounds(x, y)) img.set(x, y, value);
}
}
}
private void shiftCopy(int offX, int offY, ImageFloat32 src, ImageFloat32 dst) {
for (int y = 0; y < src.height; y++) {
for (int x = 0; x < src.width; x++) {
int xx = x + offX;
int yy = y + offY;
if (xx >= 0 && xx < src.width && yy >= 0 && yy < src.height) {
dst.set(xx, yy, src.get(x, y));
}
}
}
}
@Test
public void checkIntensity() {
ImageUInt8 input = new ImageUInt8(40, 50);
ImageFloat32 intensity = new ImageFloat32(input.width, input.height);
int[] offsets = DiscretizedCircle.imageOffsets(3, input.stride);
createCircle(4, 5, offsets, minContinuous, detectDifference + 1, input);
createCircle(12, 20, offsets, minContinuous, detectDifference + 10, input);
alg.process(input, intensity);
assertTrue(intensity.get(4, 5) < intensity.get(12, 20));
}
/**
* Fills the whole image with the specified pixel value
*
* @param img An image.
* @param value The value that the image is being filled with.
*/
public static void fill(ImageFloat32 img, float value) {
final int h = img.getHeight();
final int w = img.getWidth();
float[] data = img.data;
for (int y = 0; y < h; y++) {
int index = img.getStartIndex() + y * img.getStride();
for (int x = 0; x < w; x++) {
data[index++] = value;
}
}
}
private void checUpSample(int w, int h) {
ImageFloat32 input = new ImageFloat32(w, h);
ImageFloat32 output = new ImageFloat32(w * 2, h * 2);
GImageMiscOps.fillUniform(input, rand, 0, 100);
SiftImageScaleSpace.upSample(input, output);
for (int i = 0; i < output.height; i++) {
for (int j = 0; j < output.width; j++) {
assertTrue(input.get(j / 2, i / 2) == output.get(j, i));
}
}
}
/**
* Sets each value in the image to a value drawn from an uniform distribution that has a range of
* min <= X < max.
*/
public static void randomize(ImageFloat32 img, Random rand, float min, float max) {
final int h = img.getHeight();
final int w = img.getWidth();
float range = max - min;
float[] data = img.data;
for (int y = 0; y < h; y++) {
int index = img.getStartIndex() + y * img.getStride();
for (int x = 0; x < w; x++) {
data[index++] = rand.nextFloat() * range + min;
}
}
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double computeMeanSquaredError(ImageFloat32 imgA, ImageFloat32 imgB) {
final int h = imgA.getHeight();
final int w = imgA.getWidth();
double total = 0;
for (int y = 0; y < h; y++) {
for (int x = 0; x < w; x++) {
double difference = imgA.get(x, y) - imgB.get(x, y);
total += difference * difference;
}
}
return total / (w * h);
}
private static BufferedImage disparity(
ImageFloat32 src, BufferedImage dst, int minValue, int maxValue, int invalidColor) {
float range = maxValue - minValue;
for (int y = 0; y < src.height; y++) {
for (int x = 0; x < src.width; x++) {
float v = src.unsafe_get(x, y);
if (v > range) {
dst.setRGB(x, y, invalidColor);
} else {
int r, b;
if (v == 0) {
r = b = 0;
} else {
r = (int) (255 * v / maxValue);
b = (int) (255 * (maxValue - v) / maxValue);
}
dst.setRGB(x, y, r << 16 | b);
}
}
}
return dst;
}
/** Flips the image from top to bottom */
public static void flipVertical(ImageFloat32 img) {
int h2 = img.height / 2;
for (int y = 0; y < h2; y++) {
int index1 = img.getStartIndex() + y * img.getStride();
int index2 = img.getStartIndex() + (img.height - y - 1) * img.getStride();
int end = index1 + img.width;
while (index1 < end) {
float tmp = img.data[index1];
img.data[index1++] = img.data[index2];
img.data[index2++] = (float) tmp;
}
}
}
public void checkBorder(ImageFloat32 image, int c_x, int c_y, int w, int h) {
ImplDescribePointPixelRegion_F32 alg = new ImplDescribePointPixelRegion_F32(w, h);
TupleDesc_F32 desc = new TupleDesc_F32(alg.getDescriptorLength());
alg.setImage(image);
alg.process(c_x, c_y, desc);
int index = 0;
int y0 = c_y - h / 2;
int x0 = c_x - w / 2;
for (int y = y0; y < y0 + h; y++) {
for (int x = x0; x < x0 + w; x++, index++) {
if (image.isInBounds(x, y)) assertEquals(image.get(x, y), desc.value[index], 1e-4);
else assertEquals(0, desc.value[index], 1e-4);
}
}
}
/** Adds Gaussian/normal i.i.d noise to each pixel in the image. */
public static void addGaussian(
ImageFloat32 img, Random rand, double sigma, float min, float max) {
final int h = img.getHeight();
final int w = img.getWidth();
float[] data = img.data;
for (int y = 0; y < h; y++) {
int index = img.getStartIndex() + y * img.getStride();
for (int x = 0; x < w; x++) {
float value = (data[index]) + (float) (rand.nextGaussian() * sigma);
if (value < min) value = min;
if (value > max) value = max;
data[index++] = value;
}
}
}
@Test
public void scaleSanityCheck() {
ImageFloat32 input = new ImageFloat32(width, height);
ImageFloat32 output = new ImageFloat32(width / 2, height / 2);
GImageMiscOps.fillUniform(input, rand, 0, 100);
DistortImageOps.scale(input, output, TypeInterpolate.BILINEAR);
double error = 0;
for (int y = 0; y < output.height; y++) {
for (int x = 0; x < output.width; x++) {
double e = input.get(x * 2, y * 2) - output.get(x, y);
error += Math.abs(e);
}
}
assertTrue(error / (output.width * output.height) < 0.1);
}
public static void set(ImageSingleBand img, int x, int y, double value) {
if (ImageInteger.class.isAssignableFrom(img.getClass())) {
((ImageInteger) img).set(x, y, (int) value);
} else if (img instanceof ImageFloat32) {
((ImageFloat32) img).set(x, y, (float) value);
} else if (img instanceof ImageFloat64) {
((ImageFloat64) img).set(x, y, value);
} else {
throw new IllegalArgumentException(
"Unknown or incompatible image type: " + img.getClass().getSimpleName());
}
}
/** Very simple test for rotation accuracy. */
@Test
public void rotate_SanityCheck() {
ImageFloat32 input = new ImageFloat32(width, height);
ImageFloat32 output = new ImageFloat32(height, width);
GImageMiscOps.fillUniform(input, rand, 0, 100);
DistortImageOps.rotate(input, output, TypeInterpolate.BILINEAR, (float) Math.PI / 2f);
double error = 0;
// the outside pixels are ignored because numerical round off can cause those to be skipped
for (int y = 1; y < input.height - 1; y++) {
for (int x = 1; x < input.width - 1; x++) {
int xx = output.width - y;
int yy = x;
double e = input.get(x, y) - output.get(xx, yy);
error += Math.abs(e);
}
}
assertTrue(error / (width * height) < 0.1);
}
/**
* Checks to see if the BufferedImage has the same intensity values as the ImageUInt8
*
* @param imgA BufferedImage
* @param imgB ImageUInt8
*/
public static void checkEquals(BufferedImage imgA, ImageFloat32 imgB, float tol) {
if (imgA.getRaster() instanceof ByteInterleavedRaster
&& imgA.getType() != BufferedImage.TYPE_BYTE_INDEXED) {
ByteInterleavedRaster raster = (ByteInterleavedRaster) imgA.getRaster();
if (raster.getNumBands() == 1) {
int strideA = raster.getScanlineStride();
int offsetA = raster.getDataOffset(0) - raster.getNumBands() + 1;
// handle a special case where the RGB conversion is screwed
for (int i = 0; i < imgA.getHeight(); i++) {
for (int j = 0; j < imgA.getWidth(); j++) {
float valB = imgB.get(j, i);
int valA = raster.getDataStorage()[offsetA + i * strideA + j];
valA &= 0xFF;
if (Math.abs(valA - valB) > tol)
throw new RuntimeException("Images are not equal: A = " + valA + " B = " + valB);
}
}
return;
}
}
for (int y = 0; y < imgA.getHeight(); y++) {
for (int x = 0; x < imgA.getWidth(); x++) {
int rgb = imgA.getRGB(x, y);
float gray = (((rgb >>> 16) & 0xFF) + ((rgb >>> 8) & 0xFF) + (rgb & 0xFF)) / 3.0f;
float grayB = imgB.get(x, y);
if (Math.abs(gray - grayB) > tol) {
throw new RuntimeException("images are not equal: A = " + gray + " B = " + grayB);
}
}
}
}
private static BufferedImage grayMagnitude(
ImageFloat32 src, BufferedImage dst, float maxAbsValue) {
for (int y = 0; y < src.height; y++) {
for (int x = 0; x < src.width; x++) {
float v = Math.abs(src.get(x, y));
int rgb = (int) (255 * v / maxAbsValue);
dst.setRGB(x, y, rgb << 16 | rgb << 8 | rgb);
}
}
return dst;
}
@Test
public void checkRender() {
// Easier to make up a plane in this direction
Se3_F64 cameraToPlane = new Se3_F64();
ConvertRotation3D_F64.eulerToMatrix(
EulerType.XYZ, UtilAngle.degreeToRadian(0), 0, 0, cameraToPlane.getR());
cameraToPlane.getT().set(0, -5, 0);
Se3_F64 planeToCamera = cameraToPlane.invert(null);
CreateSyntheticOverheadViewMS<ImageFloat32> alg =
new CreateSyntheticOverheadViewMS<ImageFloat32>(
TypeInterpolate.BILINEAR, 3, ImageFloat32.class);
alg.configure(param, planeToCamera, centerX, centerY, cellSize, overheadW, overheadH);
MultiSpectral<ImageFloat32> input =
new MultiSpectral<ImageFloat32>(ImageFloat32.class, width, height, 3);
for (int i = 0; i < 3; i++) ImageMiscOps.fill(input.getBand(i), 10 + i);
MultiSpectral<ImageFloat32> output =
new MultiSpectral<ImageFloat32>(ImageFloat32.class, overheadW, overheadH, 3);
alg.process(input, output);
for (int i = 0; i < 3; i++) {
ImageFloat32 o = output.getBand(i);
// check parts that shouldn't be in view
assertEquals(0, o.get(0, 300), 1e-8);
assertEquals(0, o.get(5, 0), 1e-8);
assertEquals(0, o.get(5, 599), 1e-8);
// check areas that should be in view
assertEquals(10 + i, o.get(499, 300), 1e-8);
}
}
public synchronized void process(final BufferedImage input) {
this.input = input;
workImage = new BufferedImage(input.getWidth(), input.getHeight(), BufferedImage.TYPE_INT_RGB);
gray.reshape(input.getWidth(), input.getHeight());
ConvertBufferedImage.convertFrom(input, gray, true);
detectTarget();
SwingUtilities.invokeLater(
new Runnable() {
public void run() {
gui.setPreferredSize(new Dimension(input.getWidth(), input.getHeight()));
renderOutput();
}
});
}
public boolean estimateCameraPose(BufferedImage leftEye) {
if (!hasIntrinsic) return false;
gray.reshape(leftEye.getWidth(), leftEye.getHeight());
ConvertBufferedImage.convertFrom(leftEye, gray);
if (!target.process(gray)) return false;
if (!computeH.computeHomography(target.getDetectedPoints())) return false;
DenseMatrix64F H = computeH.getHomography();
targetToOrigin.set(decomposeH.decompose(H));
return true;
}
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;
}
private static BufferedImage colorizeSign(
ImageFloat32 src, BufferedImage dst, float maxAbsValue) {
for (int y = 0; y < src.height; y++) {
for (int x = 0; x < src.width; x++) {
float v = src.get(x, y);
int rgb;
if (v > 0) {
rgb = (int) (255 * v / maxAbsValue) << 16;
} else {
rgb = (int) (-255 * v / maxAbsValue) << 8;
}
dst.setRGB(x, y, rgb);
}
}
return dst;
}
@Override
public void renderTarget(ImageFloat32 original, List<CalibrationObservation> solutions) {
ImageMiscOps.fill(original, 255);
int numRows = config.numRows * 2 - 1;
int numCols = config.numCols * 2 - 1;
int square = original.getWidth() / (Math.max(numRows, numCols) + 4);
int targetWidth = square * numCols;
int targetHeight = square * numRows;
int x0 = (original.width - targetWidth) / 2;
int y0 = (original.height - targetHeight) / 2;
for (int i = 0; i < numRows; i += 2) {
int y = y0 + i * square;
for (int j = 0; j < numCols; j += 2) {
int x = x0 + j * square;
ImageMiscOps.fillRectangle(original, 0, x, y, square, square);
}
}
int pointsRow = numRows + 1;
int pointsCol = numCols + 1;
CalibrationObservation set = new CalibrationObservation();
int gridIndex = 0;
for (int i = 0; i < pointsRow; i++) {
for (int j = 0; j < pointsCol; j++, gridIndex++) {
double y = y0 + i * square;
double x = x0 + j * square;
set.add(new Point2D_F64(x, y), gridIndex);
}
}
solutions.add(set);
}
public static void process(ImageFloat32 input, ImageFloat32 output, int radius, float storage[]) {
int w = 2 * radius + 1;
if (storage == null) {
storage = new float[w * w];
} else if (storage.length < w * w) {
throw new IllegalArgumentException("'storage' must be at least of length " + (w * w));
}
for (int y = 0; y < radius; y++) {
int minI = y - radius;
int maxI = y + radius + 1;
if (minI < 0) minI = 0;
if (maxI > input.height) maxI = input.height;
for (int x = 0; x < input.width; x++) {
int minJ = x - radius;
int maxJ = x + radius + 1;
// bound it ot be inside the image
if (minJ < 0) minJ = 0;
if (maxJ > input.width) maxJ = input.width;
int index = 0;
for (int i = minI; i < maxI; i++) {
for (int j = minJ; j < maxJ; j++) {
storage[index++] = input.get(j, i);
}
}
// use quick select to avoid sorting the whole list
float median = QuickSelectArray.select(storage, index / 2, index);
output.set(x, y, median);
}
}
for (int y = input.height - radius; y < input.height; y++) {
int minI = y - radius;
int maxI = y + radius + 1;
if (minI < 0) minI = 0;
if (maxI > input.height) maxI = input.height;
for (int x = 0; x < input.width; x++) {
int minJ = x - radius;
int maxJ = x + radius + 1;
// bound it ot be inside the image
if (minJ < 0) minJ = 0;
if (maxJ > input.width) maxJ = input.width;
int index = 0;
for (int i = minI; i < maxI; i++) {
for (int j = minJ; j < maxJ; j++) {
storage[index++] = input.get(j, i);
}
}
// use quick select to avoid sorting the whole list
float median = QuickSelectArray.select(storage, index / 2, index);
output.set(x, y, median);
}
}
for (int y = radius; y < input.height - radius; y++) {
int minI = y - radius;
int maxI = y + radius + 1;
for (int x = 0; x < radius; x++) {
int minJ = x - radius;
int maxJ = x + radius + 1;
// bound it ot be inside the image
if (minJ < 0) minJ = 0;
if (maxJ > input.width) maxJ = input.width;
int index = 0;
for (int i = minI; i < maxI; i++) {
for (int j = minJ; j < maxJ; j++) {
storage[index++] = input.get(j, i);
}
}
// use quick select to avoid sorting the whole list
float median = QuickSelectArray.select(storage, index / 2, index);
output.set(x, y, median);
}
}
for (int y = radius; y < input.height - radius; y++) {
int minI = y - radius;
int maxI = y + radius + 1;
for (int x = input.width - radius; x < input.width; x++) {
int minJ = x - radius;
int maxJ = x + radius + 1;
// bound it ot be inside the image
if (minJ < 0) minJ = 0;
if (maxJ > input.width) maxJ = input.width;
int index = 0;
for (int i = minI; i < maxI; i++) {
for (int j = minJ; j < maxJ; j++) {
storage[index++] = input.get(j, i);
}
}
// use quick select to avoid sorting the whole list
float median = QuickSelectArray.select(storage, index / 2, index);
output.set(x, y, median);
}
}
}