/**
* ****************************************************************************************************************************************
*/
private static List<List<PointIndex_I32>> getCandidates(
BufferedImage image,
int blurRadius,
float threshLow,
float threshHigh,
double toleranceDist,
double toleranceAngle,
boolean dynamicThreshold) {
List<List<PointIndex_I32>> candidates = new ArrayList<List<PointIndex_I32>>();
ImageFloat32 input = ConvertBufferedImage.convertFromSingle(image, null, ImageFloat32.class);
ImageUInt8 binary = new ImageUInt8(input.width, input.height);
// Finds edges inside the image
CannyEdge<ImageFloat32, ImageFloat32> canny =
FactoryEdgeDetectors.canny(
blurRadius, false, dynamicThreshold, ImageFloat32.class, ImageFloat32.class);
canny.process(input, threshLow, threshHigh, binary);
List<Contour> contours = BinaryImageOps.contour(binary, rule, null);
for (Contour c : contours) {
// Only the external contours are relevant.
List<PointIndex_I32> vertices =
ShapeFittingOps.fitPolygon(c.external, true, toleranceDist, toleranceAngle, 100);
candidates.add(vertices);
}
return candidates;
}
/**
* Detects contours inside the binary image generated by canny. Only the external contour is
* relevant. Often easier to deal with than working with Canny edges directly.
*/
public static void fitCannyBinary(ImageFloat32 input) {
BufferedImage displayImage =
new BufferedImage(input.width, input.height, BufferedImage.TYPE_INT_RGB);
ImageUInt8 binary = new ImageUInt8(input.width, input.height);
// Finds edges inside the image
CannyEdge<ImageFloat32, ImageFloat32> canny =
FactoryEdgeDetectors.canny(2, false, true, ImageFloat32.class, ImageFloat32.class);
canny.process(input, 0.1f, 0.3f, binary);
List<Contour> contours = BinaryImageOps.contour(binary, 8, null);
Graphics2D g2 = displayImage.createGraphics();
g2.setStroke(new BasicStroke(2));
// used to select colors for each line
Random rand = new Random(234);
for (Contour c : contours) {
// Only the external contours are relevant.
List<PointIndex_I32> vertexes =
ShapeFittingOps.fitPolygon(c.external, true, toleranceDist, toleranceAngle, 100);
g2.setColor(new Color(rand.nextInt()));
VisualizeShapes.drawPolygon(vertexes, true, g2);
}
ShowImages.showWindow(displayImage, "Canny Contour");
}
/**
* Fits a sequence of line-segments into a sequence of points found using the Canny edge detector.
* In this case the points are not connected in a loop. The canny detector produces a more complex
* tree and the fitted points can be a bit noisy compared to the others.
*/
public static void fitCannyEdges(ImageFloat32 input) {
BufferedImage displayImage =
new BufferedImage(input.width, input.height, BufferedImage.TYPE_INT_RGB);
// Finds edges inside the image
CannyEdge<ImageFloat32, ImageFloat32> canny =
FactoryEdgeDetectors.canny(2, true, true, ImageFloat32.class, ImageFloat32.class);
canny.process(input, 0.1f, 0.3f, null);
List<EdgeContour> contours = canny.getContours();
Graphics2D g2 = displayImage.createGraphics();
g2.setStroke(new BasicStroke(2));
// used to select colors for each line
Random rand = new Random(234);
for (EdgeContour e : contours) {
g2.setColor(new Color(rand.nextInt()));
for (EdgeSegment s : e.segments) {
// fit line segments to the point sequence. Note that loop is false
List<PointIndex_I32> vertexes =
ShapeFittingOps.fitPolygon(s.points, false, toleranceDist, toleranceAngle, 100);
VisualizeShapes.drawPolygon(vertexes, false, g2);
}
}
ShowImages.showWindow(displayImage, "Canny Trace");
}
/** 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");
}
public static void main(String[] args) throws IOException {
if (args.length == 0) {
System.out.println(
"usage: crop-objects [OPTION]... FILE [DIR]\n"
+ "crops detected objects from image FILE and writes their subimages to files. \n"
+ "Can specify the DIR in which to create the files, otherwise subimage files are "
+ "created in the same directory as FILE is in by default. \n"
+ "-t [n] [m] set the high and low threshold values. n and m are values between 0 and 1.");
System.exit(1);
}
// interpret options and read arguments
if (args[0].equals("-t")) {
threshLow = Float.parseFloat(args[1]);
threshHigh = Float.parseFloat(args[2]);
filename = args[3];
if (args.length == 5) {
dir = args[4];
}
} else {
filename = args[0];
if (args.length == 2) {
dir = args[1];
}
}
// get path to directory file is in
String name = FilenameUtils.removeExtension(filename);
// get image
BufferedImage image = UtilImageIO.loadImage(new File(filename).getAbsolutePath());
if (image == null) {
System.out.println(
"usage: crop-objects [OPTION]... FILE [DIR]\n"
+ "crops detected objects from image FILE and writes their subimages to files. \n"
+ "Can specify the DIR in which to create the files, otherwise subimage files are "
+ "created in the same directory as FILE is in by default. \n"
+ "-t [n] [m] set the high and low threshold values. n and m are values between 0 and 1.");
System.exit(1);
}
minsize = (int) (0.1 * Math.min(image.getHeight(), image.getWidth()));
// find objects in image
// generate candidate contours
ArrayList<List<PointIndex_I32>> objects = new ArrayList<List<PointIndex_I32>>();
List<BufferedImage> results = new ArrayList<BufferedImage>();
List<List<PointIndex_I32>> candidates = new ArrayList<List<PointIndex_I32>>();
ImageFloat32 input = ConvertBufferedImage.convertFromSingle(image, null, ImageFloat32.class);
BufferedImage bw =
ConvertBufferedImage.convertTo(
input, new BufferedImage(image.getWidth(), image.getHeight(), image.getType()));
File binaryfile = new File(name + "_" + "binary.png");
ImageIO.write(bw, "png", binaryfile);
ImageUInt8 binary = new ImageUInt8(input.width, input.height);
// Finds edges inside the image
CannyEdge<ImageFloat32, ImageFloat32> canny =
FactoryEdgeDetectors.canny(
blurRadius, true, dynamicThreshold, ImageFloat32.class, ImageFloat32.class);
canny.process(input, threshLow, threshHigh, binary);
List<Contour> contours = BinaryImageOps.contour(binary, rule, null);
BufferedImage visualBinary = VisualizeBinaryData.renderBinary(binary, null);
File cannyfile = new File(name + "_" + "canny.png");
ImageIO.write(visualBinary, "png", cannyfile);
BufferedImage cannyContour =
VisualizeBinaryData.renderExternal(contours, null, binary.width, binary.height, null);
File cannyContourfile = new File(name + "_" + "contour.png");
ImageIO.write(cannyContour, "png", cannyContourfile);
for (Contour c : contours) {
// Only the external contours are relevant.
List<PointIndex_I32> vertices =
ShapeFittingOps.fitPolygon(c.external, true, toleranceDist, toleranceAngle, 100);
candidates.add(vertices);
}
for (List<PointIndex_I32> vertices : candidates) {
try {
Candidate c = new Candidate(vertices, image);
if (c.size(minsize)) {
c.rotate();
results.add(c.getImage());
objects.add(vertices);
}
} catch (Exception e) {
System.out.println("Error creating candidate from contour " + e.getMessage());
}
}
// write subimages of objects to files
int i = 0;
for (BufferedImage obj : results) {
// print images to file
try {
File outputfile = new File(name + "_" + i + ".png");
i++;
ImageIO.write(obj, "png", outputfile);
} catch (IOException e) {
System.out.println("Error writing subimages" + e.getMessage());
}
}
// draw objects onto original image and save
Draw.drawPolygons(objects, image);
File outputfile = new File(name + "_" + "annotated.png");
ImageIO.write(image, "png", outputfile);
}