public IplImage correctGamma(IplImage img) {
// get image intensity
// img.applyGamma(d);
IplImage gray = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);
cvCvtColor(img, gray, CV_RGB2GRAY);
BufferedImage buffImg = img.getBufferedImage();
BufferedImage buffGray = gray.getBufferedImage();
double grayArr[] = new double[gray.width() * gray.height()];
int counter = 0;
for (int i = 0; i < gray.width(); i++) {
for (int j = 0; j < gray.height(); j++) {
grayArr[counter] = buffGray.getRGB(i, j);
counter++;
}
}
double imgSd = new StandardDeviation().evaluate(grayArr);
double imgMean = new Mean().evaluate(grayArr);
double y = 0;
if (imgMean > 0.5) y = 1 + (Math.abs(0.5 - imgMean) / imgSd);
else y = 1 / (1 + (Math.abs(0.5 - imgMean) / imgSd));
img.applyGamma(y);
return img;
}
/**
* Find the most likely person based on a detection. Returns the index, and stores the confidence
* value into pConfidence.
*
* @param projectedTestFace the projected test face
* @param pConfidencePointer a pointer containing the confidence value
* @param iTestFace the test face index
* @return the index
*/
private int findNearestNeighbor(float projectedTestFace[], FloatPointer pConfidencePointer) {
double leastDistSq = Double.MAX_VALUE;
int i = 0;
int iTrain = 0;
int iNearest = 0;
LOGGER.info("................");
LOGGER.info("find nearest neighbor from " + nTrainFaces + " training faces");
for (iTrain = 0; iTrain < nTrainFaces; iTrain++) {
// LOGGER.info("considering training face " + (iTrain + 1));
double distSq = 0;
for (i = 0; i < nEigens; i++) {
// LOGGER.debug(" projected test face distance from eigenface " + (i + 1) + " is " +
// projectedTestFace[i]);
float projectedTrainFaceDistance = (float) projectedTrainFaceMat.get(iTrain, i);
float d_i = projectedTestFace[i] - projectedTrainFaceDistance;
distSq +=
d_i
* d_i; // / eigenValMat.data_fl().get(i); // Mahalanobis distance (might give
// better results than Eucalidean distance)
// if (iTrain < 5) {
// LOGGER.info(" ** projected training face " + (iTrain + 1) + " distance from
// eigenface " + (i + 1) + " is " + projectedTrainFaceDistance);
// LOGGER.info(" distance between them " + d_i);
// LOGGER.info(" distance squared " + distSq);
// }
}
if (distSq < leastDistSq) {
leastDistSq = distSq;
iNearest = iTrain;
LOGGER.info(
" training face "
+ (iTrain + 1)
+ " is the new best match, least squared distance: "
+ leastDistSq);
}
}
// Return the confidence level based on the Euclidean distance,
// so that similar images should give a confidence between 0.5 to 1.0,
// and very different images should give a confidence between 0.0 to 0.5.
float pConfidence =
(float) (1.0f - Math.sqrt(leastDistSq / (float) (nTrainFaces * nEigens)) / 255.0f);
pConfidencePointer.put(pConfidence);
LOGGER.info(
"training face " + (iNearest + 1) + " is the final best match, confidence " + pConfidence);
return iNearest;
}
/** usage: java HoughLines imageDir\imageName TransformType */
public static void main(String[] args) {
String fileName =
args.length >= 1 ? args[0] : "pic1.png"; // if no params provided, compute the defaut image
IplImage src = cvLoadImage(fileName, 0);
IplImage dst;
IplImage colorDst;
CvMemStorage storage = cvCreateMemStorage(0);
CvSeq lines = new CvSeq();
CanvasFrame source = new CanvasFrame("Source");
CanvasFrame hough = new CanvasFrame("Hough");
if (src == null) {
System.out.println("Couldn't load source image.");
return;
}
dst = cvCreateImage(cvGetSize(src), src.depth(), 1);
colorDst = cvCreateImage(cvGetSize(src), src.depth(), 3);
cvCanny(src, dst, 50, 200, 3);
cvCvtColor(dst, colorDst, CV_GRAY2BGR);
/*
* apply the probabilistic hough transform
* which returns for each line deteced two points ((x1, y1); (x2,y2))
* defining the detected segment
*/
if (args.length == 2 && args[1].contentEquals("probabilistic")) {
System.out.println("Using the Probabilistic Hough Transform");
lines = cvHoughLines2(dst, storage, CV_HOUGH_PROBABILISTIC, 1, Math.PI / 180, 40, 50, 10);
for (int i = 0; i <= lines.total(); i++) {
// from JavaCPP, the equivalent of the C code:
// CvPoint* line = (CvPoint*)cvGetSeqElem(lines,i);
// CvPoint first=line[0], second=line[1]
// is:
// CvPoint first=line.position(0), secon=line.position(1);
Pointer line = cvGetSeqElem(lines, i);
CvPoint pt1 = new CvPoint(line).position(0);
CvPoint pt2 = new CvPoint(line).position(1);
System.out.println("Line spotted: ");
System.out.println("\t pt1: " + pt1);
System.out.println("\t pt2: " + pt2);
cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0); // draw the segment on the image
}
}
/*
* Apply the multiscale hough transform which returns for each line two float parameters (rho, theta)
* rho: distance from the origin of the image to the line
* theta: angle between the x-axis and the normal line of the detected line
*/
else if (args.length == 2 && args[1].contentEquals("multiscale")) {
System.out.println("Using the multiscale Hough Transform"); //
lines = cvHoughLines2(dst, storage, CV_HOUGH_MULTI_SCALE, 1, Math.PI / 180, 40, 1, 1);
for (int i = 0; i < lines.total(); i++) {
CvPoint2D32f point = new CvPoint2D32f(cvGetSeqElem(lines, i));
float rho = point.x();
float theta = point.y();
double a = Math.cos((double) theta), b = Math.sin((double) theta);
double x0 = a * rho, y0 = b * rho;
CvPoint
pt1 =
new CvPoint((int) Math.round(x0 + 1000 * (-b)), (int) Math.round(y0 + 1000 * (a))),
pt2 =
new CvPoint((int) Math.round(x0 - 1000 * (-b)), (int) Math.round(y0 - 1000 * (a)));
System.out.println("Line spoted: ");
System.out.println("\t rho= " + rho);
System.out.println("\t theta= " + theta);
cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0);
}
}
/*
* Default: apply the standard hough transform. Outputs: same as the multiscale output.
*/
else {
System.out.println("Using the Standard Hough Transform");
lines = cvHoughLines2(dst, storage, CV_HOUGH_STANDARD, 1, Math.PI / 180, 90, 0, 0);
for (int i = 0; i < lines.total(); i++) {
CvPoint2D32f point = new CvPoint2D32f(cvGetSeqElem(lines, i));
float rho = point.x();
float theta = point.y();
double a = Math.cos((double) theta), b = Math.sin((double) theta);
double x0 = a * rho, y0 = b * rho;
CvPoint
pt1 =
new CvPoint((int) Math.round(x0 + 1000 * (-b)), (int) Math.round(y0 + 1000 * (a))),
pt2 =
new CvPoint((int) Math.round(x0 - 1000 * (-b)), (int) Math.round(y0 - 1000 * (a)));
System.out.println("Line spotted: ");
System.out.println("\t rho= " + rho);
System.out.println("\t theta= " + theta);
cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0);
}
}
source.showImage(src);
hough.showImage(colorDst);
source.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
hough.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
}
public static void captureFrame() {
// ---------These objects allow us to edit the variables used in the scalar polygon
// recognition------
JLabel blueMaxValueLabel = new JLabel("Max Blue Value");
JTextField blueMaxValueField = new JTextField("255.0", 5);
JLabel blueMinValueLabel = new JLabel("Min Blue Value");
JTextField blueMinValueField = new JTextField("100.0", 5);
JLabel greenMaxValueLabel = new JLabel("Max Green Value");
JTextField greenMaxValueField = new JTextField("255.0", 5);
JLabel greenMinValueLabel = new JLabel("Min Green Value");
JTextField greenMinValueField = new JTextField("215.0", 5);
JLabel redMaxValueLabel = new JLabel("Max Red Value");
JTextField redMaxValueField = new JTextField("45.0", 5);
JLabel redMinValueLabel = new JLabel("Min Red Value");
JTextField redMinValueField = new JTextField("0.0", 5);
JLabel yLabel = new JLabel("Y");
JTextField yValue = new JTextField(5);
boolean hotZone = false;
// ---------------------------------End object lists-------------------------------------
String source = "http://*****:*****@10.12.59.11/mjpg/video.mjpg";
FrameGrabber grabber = new OpenCVFrameGrabber(source); // new VideoInputFrameGrabber(0);
try {
Thread.sleep(1000);
} catch (InterruptedException ex) {
Logger.getLogger(CaptureImage.class.getName()).log(Level.SEVERE, null, ex);
}
CanvasFrame canvas = new CanvasFrame("WebCam");
canvas.setDefaultCloseOperation(javax.swing.JFrame.EXIT_ON_CLOSE);
CanvasFrame before = new CanvasFrame("before");
before.setDefaultCloseOperation(javax.swing.JFrame.HIDE_ON_CLOSE);
GridBagLayout gridBag = new GridBagLayout();
before.setLayout(gridBag);
GridBagConstraints gbc = new GridBagConstraints();
gbc.fill = GridBagConstraints.VERTICAL;
gridBag.setConstraints(before.getComponent(0), gbc);
gbc.fill = GridBagConstraints.NONE;
gbc.gridx = 1;
gbc.gridy = 0;
before.add(blueMaxValueLabel, gbc);
gbc.gridx = 2;
before.add(blueMaxValueField, gbc);
gbc.gridx = 3;
before.add(blueMinValueLabel, gbc);
gbc.gridx = 4;
before.add(blueMinValueField, gbc);
// before.add(blueMinValueField);
gbc.gridx = 1;
gbc.gridy = 2;
before.add(greenMaxValueLabel, gbc);
gbc.gridx = 2;
before.add(greenMaxValueField, gbc);
gbc.gridx = 3;
before.add(greenMinValueLabel, gbc);
gbc.gridx = 4;
before.add(greenMinValueField, gbc);
// before.add(greenMinValueField);
gbc.gridx = 1;
gbc.gridy = 3;
before.add(redMaxValueLabel, gbc);
gbc.gridx = 2;
before.add(redMaxValueField, gbc);
gbc.gridx = 3;
before.add(redMinValueLabel, gbc);
gbc.gridx = 4;
before.add(redMinValueField, gbc);
before.add(yLabel);
before.add(yValue);
// before.add(redMinValueField);
int numOfScreens = 39;
// String loadingPic = "C:\\loadingScreen\\loadingScreen"
// + (((int) (Math.random() * numOfScreens)) + 1) + ".bmp";
int failedGrabs = 0;
NetworkTable.setTeam(
1259); // Capture image requires the setTeam method because it does not have use
// Smartdashboard which already assigns a team number in the from of a network table
NetworkTable.setIPAddress("10.12.59.2");
NetworkTable.setClientMode();
NetworkTable.getTable("SmartDashboard").putBoolean("TestTable", hotZone);
while (true) {
try {
// try {
// IplImage splashScreen = new IplImage(cvLoadImage(loadingPic));
// canvas.showImage(splashScreen);
// } catch (Exception e) {
// }
grabber.start();
IplImage img;
// IplImage hsv;
// IplImage canny;
IplImage displayImg;
IplImage dst;
PolygonFinder polyFind = new PolygonFinder();
// try {
// NetworkTable.getTable("camera").putNumber("distance", 0);
// NetworkTable.getTable("camera").putBoolean("hotZone", false);
// } catch (Exception e) {
// }
while (true) {
while (true) {
try {
// System.out.println("grabbing...");
img = new IplImage(grabber.grab());
displayImg = new IplImage(cvCreateImage(img.cvSize(), img.depth(), img.nChannels()));
cvCopy(img, displayImg, null);
// System.out.println("Frame GRABBED!");
break;
} catch (Exception e) {
failedGrabs++;
System.out.println(failedGrabs);
if (failedGrabs > 10) {
grabber = new OpenCVFrameGrabber(source);
grabber.start();
failedGrabs = 0;
}
continue;
}
}
// PolygonFinder polyFind = new PolygonFinder(img);
// ArrayList<PolygonStructure> polygons = polyFind.findPolygons(4);
// for (int i = 0; i < polygons.size(); i++) {
// polygons.get(i).drawShape(img, CvScalar.MAGENTA);
// }
// canvas.showImage(img);
// return;
if (img != null) {
// cvSaveImage("originalcapture.jpg", img);
}
// IplImage gray = cvCreateImage(cvGetSize(img), img.depth(), 1 );
// hsv = new IplImage(cvCreateImage(cvGetSize(img), img.depth(), 3));
dst = new IplImage(cvCreateImage(cvGetSize(img), img.depth(), 1));
// cvCvtColor(img, gray, CV_RGB2GRAY);
// cvCvtColor(img, hsv, CV_BGR2HSV);
// if(hsv != null) {
// cvSaveImage("hsv.jpg", hsv);
// }
// 30 20 0; 70 140 60
// 50 175 75 //// 100 255 225
// cvInRangeS(hsv, cvScalar(0, 200, 0, 0), cvScalar(150, 255, 255, 0), dst);
// cvDrawLine(img, new CvPoint(0, 360), new CvPoint(639, 360), CvScalar.BLACK, 240, 8, 0);
// cvInRangeS(img, cvScalar(100, 215, 0, 0), cvScalar(255, 255, 45, 0), dst); This is the
// original
// Code used to set max and min values for bgr scale in scalars VVV
cvInRangeS(
img,
cvScalar(
(new Double(blueMinValueField.getText())).doubleValue(),
(new Double(greenMinValueField.getText())).doubleValue(),
(new Double(redMinValueField.getText())).doubleValue(),
0),
cvScalar(
(new Double(blueMaxValueField.getText())).doubleValue(),
(new Double(greenMaxValueField.getText())).doubleValue(),
(new Double(redMaxValueField.getText())).doubleValue(),
0),
dst);
// NEED TO FLIP MAX IN MIN POSITION, MIN IS IN MAX POSITION
// cvInRangeS(img, cvScalar(0, 0, 0, 0), cvScalar(255, 255, 255, 0), dst);
// cvDilate( dst, dst, null, 1 );
cvSmooth(dst, dst, CV_MEDIAN, 1, 1, 0, 0);
// cvCanny(gray, dst, 50, 100, 3);
// cvCvtColor(hsv, gray, CV_RGB2GRAY);
// canvas.showImage(img);
// before.showImage(dst);
IplImage newDst =
new IplImage(cvCloneImage(img)); // cvCreateImage(cvGetSize(img), img.depth(), 3));
cvCvtColor(dst, newDst, CV_GRAY2BGR);
// cvConvexHull2(newDst, null, CV_CLOCKWISE, 0);
before.showImage(newDst);
polyFind.setImage(newDst);
ArrayList<PolygonStructure> polygons = new ArrayList<PolygonStructure>();
int i;
// before.showImage(newDst);
for (i = 4; i < 5; i++) {
for (PolygonStructure ps : polyFind.findPolygons(i)) {
polygons.add(ps);
}
}
for (int c = 0; c < polygons.size(); c++) {
for (int d = 0; d < polygons.size(); d++) {
if (c == d) {
break;
}
if (polygons
.get(c)
.getPolygon()
.contains(polygons.get(d).getPolygon().getBounds2D())) {
polygons.remove(d);
if (d < c) {
c--;
}
d--;
}
}
}
for (int c = 0; c < polygons.size(); c++) {
for (int d = 0; d < polygons.size(); d++) {
if (c == d) {
break;
}
if (polygons
.get(c)
.getPolygon()
.contains(
polygons.get(d).getPolygon().getBounds().getCenterX(),
polygons.get(d).getPolygon().getBounds().getCenterY())) {
polygons.remove(d);
if (d < c) {
c--;
}
d--;
}
}
}
// if
// (tempPoly.getVertex(0).x()<vertices[0].x()&&tempPoly.getVertex(1).x()>vertices[0].x()
//
// &&tempPoly.getVertex(1).y()<vertices[0].y()&&tempPoly.getVertex(2).y()>vertices[0].y())
// {
// isInside = true;
// break;
// }
for (i = 0; i < polygons.size(); i++) {
if (polygons.size() < 2) {
hotZone = false;
} else {
hotZone = true;
}
CvScalar polyColor = CvScalar.MAGENTA;
switch (i) {
case 0:
{
polyColor = CvScalar.RED;
// System.out.println("Center X: "
// + (320 - ((polygons.get(i).getVertex(3).x()
// + polygons.get(i).getVertex(2).x()) / 2))
// + "\tCenter Y: "
// + (240 - ((polygons.get(i).getVertex(3).y()
// + (polygons.get(i).getVertex(2).y())) / 2)));
double x =
(320
- ((polygons.get(i).getVertex(3).x() + polygons.get(i).getVertex(2).x())
/ 2));
double angle =
(480
- ((polygons.get(i).getVertex(3).y() + (polygons.get(i).getVertex(2).y()))
/ 2));
// double distance = 5182.2043151825 * Math.pow(angle, -1);
double distance = 514.7318 * Math.pow(angle - 220, -1.2);
// double distance;
if (angle < 317) {
distance = -0.370786516853933 * angle + 133.977528089888;
} else if (angle > 316 && angle < 325) {
distance = -0.184697808038669 * angle + 74.9375184489134;
} else if (angle > 324 && angle < 362) {
distance = -0.140145789191636 * angle + 60.5198480748917;
} else if (angle > 360) {
distance = -0.0702258215380136 * angle + 35.3150512441271;
}
for (int c = 0; c < 4; c++) {
System.out.println("Vertex " + c + ":" + polygons.get(i).getVertex(c).y());
}
yValue.setText("" + angle);
// hotZone = true;
break;
}
case 1:
{
// Hot zone
polyColor = CvScalar.BLUE;
break;
}
case 2:
{
polyColor = CvScalar.GREEN;
break;
}
case 3:
{
polyColor = CvScalar.YELLOW;
break;
}
}
// polygons.get(i).drawShape(img, polyColor);
cvLine(
displayImg,
polygons.get(i).getVertices()[3],
polygons.get(i).getVertices()[0],
polyColor,
3,
CV_AA,
0);
cvLine(
displayImg,
polygons.get(i).getVertices()[0],
polygons.get(i).getVertices()[1],
polyColor,
3,
CV_AA,
0);
cvDrawCircle(displayImg, polygons.get(i).getVertices()[0], 3, CvScalar.GRAY, 1, 8, 0);
cvLine(
displayImg,
polygons.get(i).getVertices()[1],
polygons.get(i).getVertices()[2],
polyColor,
3,
CV_AA,
0);
cvDrawCircle(
displayImg, polygons.get(i).getVertices()[1], 3, CvScalar.MAGENTA, 1, 8, 0);
cvLine(
displayImg,
polygons.get(i).getVertices()[2],
polygons.get(i).getVertices()[3],
polyColor,
3,
CV_AA,
0);
cvDrawCircle(displayImg, polygons.get(i).getVertices()[2], 3, CvScalar.BLACK, 1, 8, 0);
cvDrawCircle(displayImg, polygons.get(i).getVertices()[3], 3, CvScalar.CYAN, 1, 8, 0);
// System.out.println("Polygon " + i + "\t" + polygons.get(i).getVertices()[0]);
}
try {
// NetworkTable.getTable("camera").beginTransaction();
// NetworkTable.getTable("camera").putNumber("distance",
// distance);
// NetworkTable.getTable("camera").putNumber("x", x);
NetworkTable.getTable("camera").putBoolean("hotZone", hotZone);
// NetworkTable.getTable("camera").endTransaction();
} catch (Exception e) {
}
if (displayImg != null) {
// cvSaveImage("aftercapture.jpg", dst);
cvDrawLine(
displayImg, new CvPoint(300, 240), new CvPoint(340, 240), CvScalar.WHITE, 2, 8, 0);
cvDrawLine(
displayImg, new CvPoint(320, 220), new CvPoint(320, 260), CvScalar.WHITE, 2, 8, 0);
canvas.showImage(displayImg);
} else {
// System.out.println("Null Image");
}
// cvReleaseImage(gray);
cvReleaseImage(newDst);
// cvReleaseImage(img);
// cvReleaseImage(hsv);
cvReleaseImage(displayImg);
cvReleaseImage(dst);
// Thread.sleep(50);
}
// System.out.println("5");
// grabber.stop();
} catch (Exception e) {
e.printStackTrace();
}
grabber = new OpenCVFrameGrabber(source);
}
}