one.empty3.feature20220726.jviolajones.Detector Maven / Gradle / Ivy
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//package one.empty3.feature20220726.jviolajones;
//
//import org.jdom2.Document;
//import org.jdom2.Element;
//import org.jdom2.input.SAXBuilder;
//
//import javaAnd.awt.image.imageio.ImageIO;
//import javaAnd.awt.*;
//import javaAnd.awt.image.BufferedImage;
//import java.io.FileInputStream;
//import java.io.InputStream;
//import java.util.List;
//import java.util.*;
//
//
//public class Detector {
// /*
// * The list of classifiers that the test image should pass to be considered as an image.
// */
// List stages;
// Point size;
//
// /*
// * Detector constructor.
// * Builds, from a XML file, the corresponding Haar cascade.
// *
// * @param filename The XML file (generated by OpenCV) describing the Haar cascade.
// */
// public Detector(String filename) throws java.io.FileNotFoundException {
// this(new FileInputStream(filename));
// }
//
// public org.jdom2.Element getChild(Element element, String childName) {
// return null;
// }
//
// public Detector(InputStream input) {
// Document document = null;
// Element racine;
// stages = new LinkedList();
// SAXBuilder sxb = new SAXBuilder();
// try {
// //On cr�e un nouveau document JDOM avec en argument le fichier XML
// //Le parsing est termin� ;)
// document = sxb.build(input);
// } catch (Exception e) {
// e.printStackTrace();
// }
//
// //On initialise un nouvel element racine avec l'element racine du document.
// racine = (Element) document.getRootElement().getChildren().get(0);
// Scanner scanner = new Scanner(racine.getChild("size").getText());
// size = new Point(scanner.nextInt(), scanner.nextInt());
// Iterator it = racine.getChild("stages").getChildren("_").iterator();
// while (it.hasNext()) {
// Element stage = (Element) it.next();
// float thres = Float.parseFloat(stage.getChild("stage_threshold").getText());
// //System.out.println(thres);
// Iterator it2 = stage.getChild("trees").getChildren("_").iterator();
// Stage st = new Stage(thres);
// while (it2.hasNext()) {
// Element tree = ((Element) it2.next());
// Tree t = new Tree();
// Iterator it4 = tree.getChildren("_").iterator();
// while (it4.hasNext()) {
// Element feature = (Element) it4.next();
// float thres2 = Float.parseFloat(feature.getChild("threshold").getText());
// int left_node = -1;
// float left_val = 0;
// boolean has_left_val = false;
// int right_node = -1;
// float right_val = 0;
// boolean has_right_val = false;
// Element e;
// if ((e = feature.getChild("left_val")) != null) {
// left_val = Float.parseFloat(e.getText());
// has_left_val = true;
// } else {
// left_node = Integer.parseInt(feature.getChild("left_node").getText());
// has_left_val = false;
// }
//
// if ((e = feature.getChild("right_val")) != null) {
// right_val = Float.parseFloat(e.getText());
// has_right_val = true;
// } else {
// right_node = Integer.parseInt(feature.getChild("right_node").getText());
// has_right_val = false;
// }
// Feature f = new Feature(thres2, left_val, left_node, has_left_val, right_val, right_node, has_right_val, size);
// Iterator it3 = feature.getChild("feature").getChild("rects").getChildren("_").iterator();
// while (it3.hasNext()) {
// String s = ((Element) it3.next()).getText().trim();
// //System.out.println(s);
// Rect r = Rect.fromString(s);
// f.add(r);
// }
//
// t.addFeature(f);
// }
// st.addTree(t);
// //System.out.println("Number of nodes in tree "+t.features.size());
// }
// //System.out.println("Number of trees : "+ st.trees.size());
// stages.add(st);
// }
// //System.out.println(stages.size());
// }
//
// public List getFaces(String filename, float baseScale, float scale_inc, float increment, int min_neighbors, boolean doCannyPruning) throws java.io.FileNotFoundException, java.io.IOException {
// return getFaces(new FileInputStream(filename), baseScale, scale_inc, increment, min_neighbors, doCannyPruning);
// }
//
// public List getFaces(InputStream input, float baseScale, float scale_inc, float increment, int min_neighbors, boolean doCannyPruning) throws java.io.FileNotFoundException, java.io.IOException {
// return getFaces(ImageIO.read(input), baseScale, scale_inc, increment, min_neighbors, doCannyPruning);
// }
//
// /*
// * Returns the list of detected objects in an image applying the Viola-Jones algorithm.
// *
// * The algorithm tests, from sliding windows on the image, of variable size, which regions should be considered as searched objects.
// * Please see Wikipedia for a description of the algorithm.
// *
// * @param image bufferedimage input
// * @param baseScale The initial ratio between the window size and the Haar classifier size (default 2).
// * @param scale_inc The scale increment of the window size, at each step (default 1.25).
// * @param increment The shift of the window at each sub-step, in terms of percentage of the window size.
// * @return the list of rectangles containing searched objects, expressed in pixels.
// */
// public List getFaces(BufferedImage image, float baseScale, float scale_inc, float increment, int min_neighbors, boolean doCannyPruning) {
// List ret = new ArrayList();
// int width = image.getWidth();
// int height = image.getHeight();
// float maxScale = (Math.min((width + 0.f) / size.x, (height + 0.0f) / size.y));
// int[][] grayImage = new int[width][height];
// int[][] img = new int[width][height];
// int[][] squares = new int[width][height];
// for (int i = 0; i < width; i++) {
// int col = 0;
// int col2 = 0;
// for (int j = 0; j < height; j++) {
// int c = image.getRGB(i, j);
// int red = (c & 0x00ff0000) >> 16;
// int green = (c & 0x0000ff00) >> 8;
// int blue = c & 0x000000ff;
// int value = (30 * red + 59 * green + 11 * blue) / 100;
// img[i][j] = value;
// grayImage[i][j] = (i > 0 ? grayImage[i - 1][j] : 0) + col + value;
// squares[i][j] = (i > 0 ? squares[i - 1][j] : 0) + col2 + value * value;
// col += value;
// col2 += value * value;
// }
// }
// int[][] canny = null;
// if (doCannyPruning)
// canny = getIntegralCanny(img);
// for (float scale = baseScale; scale < maxScale; scale *= scale_inc) {
// int step = (int) (scale * 24 * increment);
// int size = (int) (scale * 24);
// for (int i = 0; i < width - size; i += step) {
// for (int j = 0; j < height - size; j += step) {
// if (doCannyPruning) {
// int edges_density = canny[i + size][j + size] + canny[i][j] - canny[i][j + size] - canny[i + size][j];
// int d = edges_density / size / size;
// if (d < 20 || d > 100)
// continue;
// }
// boolean pass = true;
// int k = 0;
// for (Stage s : stages) {
//
// if (!s.pass(grayImage, squares, i, j, scale)) {
// pass = false;
// //System.out.println("Failed at Stage "+k);
// break;
// }
// k++;
// }
// if (pass) ret.add(new Rectangle(i, j, size, size));
// }
// }
// }
// return merge(ret, min_neighbors);
// }
//
// public int[][] getIntegralCanny(int[][] grayImage) {
// int[][] canny = new int[grayImage.length][grayImage[0].length];
// for (int i = 2; i < canny.length - 2; i++)
// for (int j = 2; j < canny[0].length - 2; j++) {
// int sum = 0;
// sum += 2 * grayImage[i - 2][j - 2];
// sum += 4 * grayImage[i - 2][j - 1];
// sum += 5 * grayImage[i - 2][j + 0];
// sum += 4 * grayImage[i - 2][j + 1];
// sum += 2 * grayImage[i - 2][j + 2];
// sum += 4 * grayImage[i - 1][j - 2];
// sum += 9 * grayImage[i - 1][j - 1];
// sum += 12 * grayImage[i - 1][j + 0];
// sum += 9 * grayImage[i - 1][j + 1];
// sum += 4 * grayImage[i - 1][j + 2];
// sum += 5 * grayImage[i + 0][j - 2];
// sum += 12 * grayImage[i + 0][j - 1];
// sum += 15 * grayImage[i + 0][j + 0];
// sum += 12 * grayImage[i + 0][j + 1];
// sum += 5 * grayImage[i + 0][j + 2];
// sum += 4 * grayImage[i + 1][j - 2];
// sum += 9 * grayImage[i + 1][j - 1];
// sum += 12 * grayImage[i + 1][j + 0];
// sum += 9 * grayImage[i + 1][j + 1];
// sum += 4 * grayImage[i + 1][j + 2];
// sum += 2 * grayImage[i + 2][j - 2];
// sum += 4 * grayImage[i + 2][j - 1];
// sum += 5 * grayImage[i + 2][j + 0];
// sum += 4 * grayImage[i + 2][j + 1];
// sum += 2 * grayImage[i + 2][j + 2];
//
// canny[i][j] = sum / 159;
// //System.out.println(canny[i][j]);
// }
// int[][] grad = new int[grayImage.length][grayImage[0].length];
// for (int i = 1; i < canny.length - 1; i++)
// for (int j = 1; j < canny[0].length - 1; j++) {
// int grad_x = -canny[i - 1][j - 1] + canny[i + 1][j - 1] - 2 * canny[i - 1][j] + 2 * canny[i + 1][j] - canny[i - 1][j + 1] + canny[i + 1][j + 1];
// int grad_y = canny[i - 1][j - 1] + 2 * canny[i][j - 1] + canny[i + 1][j - 1] - canny[i - 1][j + 1] - 2 * canny[i][j + 1] - canny[i + 1][j + 1];
// grad[i][j] = Math.abs(grad_x) + Math.abs(grad_y);
// //System.out.println(grad[i][j]);
// }
// //JFrame f = new JFrame();
// //f.setContentPane(new DessinChiffre(grad));
// //f.setVisible(true);
// for (int i = 0; i < canny.length; i++) {
// int col = 0;
// for (int j = 0; j < canny[0].length; j++) {
// int value = grad[i][j];
// canny[i][j] = (i > 0 ? canny[i - 1][j] : 0) + col + value;
// col += value;
// }
// }
// return canny;
// }
//
// public List merge(List rects, int min_neighbors) {
// List retour = new LinkedList();
// int[] ret = new int[rects.size()];
// int nb_classes = 0;
// for (int i = 0; i < rects.size(); i++) {
// boolean found = false;
// for (int j = 0; j < i; j++) {
// if (equals(rects.get(j), rects.get(i))) {
// found = true;
// ret[i] = ret[j];
// }
// }
// if (!found) {
// ret[i] = nb_classes;
// nb_classes++;
// }
// }
// //System.out.println(Arrays.toString(ret));
// int[] neighbors = new int[nb_classes];
// Rectangle[] rect = new Rectangle[nb_classes];
// for (int i = 0; i < nb_classes; i++) {
// neighbors[i] = 0;
// rect[i] = new Rectangle(0, 0, 0, 0);
// }
// for (int i = 0; i < rects.size(); i++) {
// neighbors[ret[i]]++;
// rect[ret[i]].x += rects.get(i).x;
// rect[ret[i]].y += rects.get(i).y;
// rect[ret[i]].height += rects.get(i).height;
// rect[ret[i]].width += rects.get(i).width;
// }
// for (int i = 0; i < nb_classes; i++) {
// int n = neighbors[i];
// if (n >= min_neighbors) {
// Rectangle r = new Rectangle(0, 0, 0, 0);
// r.x = (rect[i].x * 2 + n) / (2 * n);
// r.y = (rect[i].y * 2 + n) / (2 * n);
// r.width = (rect[i].width * 2 + n) / (2 * n);
// r.height = (rect[i].height * 2 + n) / (2 * n);
// retour.add(r);
// }
// }
// return retour;
// }
//
// public boolean equals(Rectangle r1, Rectangle r2) {
// int distance = (int) (r1.width * 0.2);
//
// /*return r2.x <= r1.x + distance &&
// r2.x >= r1.x - distance &&
// r2.y <= r1.y + distance &&
// r2.y >= r1.y - distance &&
// r2.width <= (int)( r1.width * 1.2 ) &&
// (int)( r2.width * 1.2 ) >= r1.width;*/
// if (r2.x <= r1.x + distance &&
// r2.x >= r1.x - distance &&
// r2.y <= r1.y + distance &&
// r2.y >= r1.y - distance &&
// r2.width <= (int) (r1.width * 1.2) &&
// (int) (r2.width * 1.2) >= r1.width) return true;
// if (r1.x >= r2.x && r1.x + r1.width <= r2.x + r2.width && r1.y >= r2.y && r1.y + r1.height <= r2.y + r2.height)
// return true;
// return false;
// }
//}