/** This function is called periodically during operator control */
public void teleopInit() {
ColorImage image;
try {
image = camera.getImage();
image.write("unedited.jpg");
BinaryImage bImage = image.thresholdRGB(160, 255, 160, 255, 160, 255);
bImage.write("whitemask.jpg");
MonoImage mImage = image.getLuminancePlane();
mImage.write("luminancePlane.jpg");
image.free();
bImage.free();
} catch (NIVisionException e) {
System.out.println("Error retrieving image: NIVisionException");
e.printStackTrace();
} catch (AxisCameraException e) {
System.out.println("Error retrieving image: AxisCameraException");
e.printStackTrace();
}
}
public boolean processImage() {
boolean debugWriteImages = true;
boolean success = cam.freshImage();
if (success) {
try {
System.out.println("In Try loop");
ColorImage im = cam.getImage();
System.out.println("Got image");
if (debugWriteImages) {
im.write("image1.jpg");
System.out.println("Wrote color image");
}
BinaryImage thresholdIm =
im.thresholdRGB(redLow, redHigh, greenLow, greenHigh, blueLow, blueHigh);
if (debugWriteImages) {
thresholdIm.write("image2.jpg");
System.err.println("Wrote Threshold Image");
}
BinaryImage filteredBoxIm = thresholdIm.particleFilter(boxCriteria);
ParticleAnalysisReport[] xparticles = filteredBoxIm.getOrderedParticleAnalysisReports();
System.out.println(xparticles.length + " particles at " + Timer.getFPGATimestamp());
BinaryImage filteredInertiaIm = filteredBoxIm.particleFilter(inertiaCriteria);
ParticleAnalysisReport[] particles = filteredInertiaIm.getOrderedParticleAnalysisReports();
System.out.println(particles.length + " particles at " + Timer.getFPGATimestamp());
// Loop through targets, find highest one.
// Targets aren't found yet.
highTarget = Target.NullTarget;
target1 = Target.NullTarget;
target2 = Target.NullTarget;
target3 = Target.NullTarget;
target4 = Target.NullTarget;
System.out.println("Targets created");
double minY = IMAGE_HEIGHT; // Minimum y <-> higher in image.
for (int i = 0; i < particles.length; i++) {
Target t = new Target(i, particles[i]);
if (t.ratio > ratioMin && t.ratio < ratioMax) {
addTarget(t);
if (t.centerY <= minY) {
highTarget = t;
}
}
System.out.println(
"Target "
+ i
+ ": ("
+ t.centerX
+ ","
+ t.centerY
+ ") Distance: "
+ getDistance(t));
}
System.out.println("Best target: " + highTarget.index);
System.out.println("Distance to the target: " + getDistance(highTarget));
if (debugWriteImages) {
filteredBoxIm.write("image3.jpg");
filteredInertiaIm.write("image4.jpg");
System.out.println("Wrote Images");
}
// Free memory from images.
im.free();
thresholdIm.free();
filteredBoxIm.free();
filteredInertiaIm.free();
} catch (AxisCameraException ex) {
System.out.println("Axis Camera Exception Gotten" + ex.getMessage());
ex.printStackTrace();
} catch (NIVisionException ex) {
System.out.println("NIVision Exception Gotten - " + ex.getMessage());
ex.printStackTrace();
}
}
return success;
}
/**
* Analyzes an image taken by the Axis Camera, performing various functions to determine where the
* goal is and at what goal the robot is facing
*
* @param
* @return Array of doubles where the first value is the type of goal (2.0 high, 1.0 middle, 0.0
* no goal), the x-centered-normalized value, the y-centered-normalized value and the
* distance. If the distance is negative, no goal was found.
*/
public double[] analyze() {
double[] data = new double[3];
// [goal type, x-centered, y-centered, distance]
try {
ColorImage image = camera.getImage(); // Get image from camera
BinaryImage thresholdImage;
thresholdImage =
image.thresholdHSV(120, 120, 44, 80, 98, 100); // "Look" for objects in this HSV range
BinaryImage convexHullImage = thresholdImage.convexHull(false); // Fill in occluded rectangles
BinaryImage filteredImage =
convexHullImage.particleFilter(collection); // Find filled in rectangles
Scores scores[] = new Scores[filteredImage.getNumberParticles()];
for (int i = 0; i < scores.length; i++) {
ParticleAnalysisReport report =
filteredImage.getParticleAnalysisReport(i); // Get the report for each particle found
scores[i] = new Scores();
scores[i].rectangularity = scoreRectangularity(report);
scores[i].aspectRatioOuter = scoreAspectRatio(filteredImage, report, i, true);
scores[i].aspectRatioInner = scoreAspectRatio(filteredImage, report, i, false);
scores[i].xEdge = scoreXEdge(thresholdImage, report);
scores[i].yEdge = scoreYEdge(thresholdImage, report);
if (scoreCompare(scores[i], false)) {
double dist = computeDistance(thresholdImage, report, i, false);
System.out.println(
"particle: "
+ i
+ " is a High Goal centerX: "
+ report.center_mass_x_normalized
+ "centerY: "
+ report.center_mass_y_normalized);
System.out.println("Distance: " + dist);
data[0] = 2.0;
data[1] = report.center_mass_x_normalized;
data[2] = report.center_mass_y_normalized;
data[3] = dist;
} else if (scoreCompare(scores[i], true)) {
double dist = computeDistance(thresholdImage, report, i, false);
System.out.println(
"particle: "
+ i
+ " is a Middle Goal centerX: "
+ report.center_mass_x_normalized
+ "centerY: "
+ report.center_mass_y_normalized);
System.out.println("Distance: " + dist);
data[0] = 1.0;
data[1] = report.center_mass_x_normalized;
data[2] = report.center_mass_y_normalized;
data[3] = dist;
} else {
System.out.println(
"particle: "
+ i
+ " is not a goal centerX: "
+ report.center_mass_x_normalized
+ "centerY: "
+ report.center_mass_y_normalized);
data[0] = 0.0;
data[1] = report.center_mass_x_normalized;
data[2] = report.center_mass_y_normalized;
data[3] = -1.0;
}
System.out.println(
"rect: " + scores[i].rectangularity + "ARinner: " + scores[i].aspectRatioInner);
System.out.println(
"ARouter: "
+ scores[i].aspectRatioOuter
+ "xEdge: "
+ scores[i].xEdge
+ "yEdge: "
+ scores[i].yEdge);
}
/* MUST USE FREE FUNCTION: all images are currently allocated in C structures */
filteredImage.free();
convexHullImage.free();
thresholdImage.free();
image.free();
} // end analyze()
catch (AxisCameraException e) {
data[0] = 0.0;
data[1] = 0.0;
data[2] = 0.0;
data[3] = -1.0;
SmartDashboard.putString("ERROR: ", "Camera malfunction!");
} catch (NIVisionException ex) {
data[0] = 0.0;
data[1] = 0.0;
data[2] = 0.0;
data[3] = -1.0;
SmartDashboard.putString("ERROR: ", "NIVision Exception!");
}
return data;
}
public DetectedPoint[] getTargetCoordinates(TrackingCriteria criteria) {
// Most important bit of this code...
final long thisAlgorithmBecomingSkynetCost = 99999999;
ColorImage colorImage = null;
BinaryImage binaryImage = null;
BinaryImage resultImage = null;
DetectedPoint[] results = null;
try {
if (!USE_CAMERA) {
colorImage = new RGBImage("inputImage.jpg");
} else {
do {
colorImage = imageTrackingCamera.getImage();
} while (!imageTrackingCamera.freshImage());
}
int hueLow = criteria.getMinimumHue();
int hueHigh = criteria.getMaximumHue();
int saturationLow = criteria.getMinimumSaturation();
int saturationHigh = criteria.getMaximumSaturation();
int valueLow = criteria.getMinimumValue();
int valueHigh = criteria.getMaximumValue();
// Attempt to isolate the colours of the LED ring
binaryImage =
colorImage.thresholdHSV(
hueLow, hueHigh, saturationLow, saturationHigh, valueLow, valueHigh);
// Fill in any detected "particles" to make analysis easier
// See:
// http://zone.ni.com/reference/en-XX/help/372916L-01/nivisionconcepts/advanced_morphology_operations/
binaryImage.convexHull(true);
resultImage = binaryImage.removeSmallObjects(true, 3);
ParticleAnalysisReport[] reports = resultImage.getOrderedParticleAnalysisReports();
results = new DetectedPoint[reports.length];
int pointIndex = 0;
for (int i = 0; i < reports.length; i++) {
ParticleAnalysisReport report = reports[i];
int aspectRatio = report.boundingRectWidth / report.boundingRectHeight;
double area = report.particleArea;
double aspectError = (aspectRatio - criteria.getAspectRatio()) / criteria.getAspectRatio();
double areaError = (area - criteria.getParticleArea()) / criteria.getParticleArea();
aspectError = Math.abs(aspectError);
areaError = Math.abs(areaError);
if (aspectError < criteria.getAspectTolerance()
&& areaError < criteria.getAreaTolerance()) {
results[pointIndex] =
new DetectedPoint(report.center_mass_x_normalized, report.center_mass_y_normalized);
pointIndex++;
}
}
log(pointIndex + " point Index, " + results.length + " results.length");
// Remove the empty slots in the array
if (pointIndex < results.length) {
DetectedPoint[] compressedPoints = new DetectedPoint[pointIndex];
int x = 0;
for (int i = 0; i < results.length; i++) {
if (results[i] != null) {
compressedPoints[x] = results[i];
x++;
}
}
results = compressedPoints;
}
} catch (AxisCameraException ex) {
log("Unable to grab images from the image tracking camera");
ex.printStackTrace();
} catch (NIVisionException ex) {
log("Encountered a NIVisionException while trying to acquire coordinates");
ex.printStackTrace();
} finally {
try {
log("We're actually freeing things!");
// For debugging purposes
// colorImage.write("colorImage.jpg");
// binaryImage.write("binaryImage.jpg");
// resultImage.write("resultImage.jpg");
if (colorImage != null) colorImage.free();
if (binaryImage != null) binaryImage.free();
if (resultImage != null) resultImage.free();
colorImage = null;
binaryImage = null;
resultImage = null;
} catch (NIVisionException ex) {
// Really? Throw an exception while freeing memory?
log("Encountered an exception while freeing memory... Really NI? Really?");
ex.printStackTrace();
}
}
return results;
}
public void autonomous() {
try {
/**
* Do the image capture with the camera and apply the algorithm described above. This sample
* will either get images from the camera or from an image file stored in the top level
* directory in the flash memory on the cRIO. The file name in this case is "testImage.jpg"
*/
ColorImage image = cam.getImage(); // comment if using stored images
// ColorImage image; // next 2 lines read image from flash on cRIO
// image = new RGBImage("/testImage.jpg"); // get the sample image from the cRIO flash
BinaryImage thresholdImage =
image.thresholdHSV(60, 100, 90, 255, 20, 255); // keep only red objects
// thresholdImage.write("/threshold.bmp");
BinaryImage convexHullImage = thresholdImage.convexHull(false); // fill in occluded rectangles
// convexHullImage.write("/convexHull.bmp");
BinaryImage filteredImage = convexHullImage.particleFilter(cc); // filter out small particles
// filteredImage.write("/filteredImage.bmp");
ParticleAnalysisReport[] par = filteredImage.getOrderedParticleAnalysisReports();
double[] target = new double[] {image.getWidth() / 2.0, image.getHeight()};
double minDist = -1;
double[] minMid = new double[0];
// calculate closest rectangle
if (par.length == 0) {
done = true;
return;
}
for (int i = 0; i < par.length; i++) {
ParticleAnalysisReport p = par[i];
double[] mid =
new double[] {
p.boundingRectLeft + p.boundingRectWidth / 2.0,
p.boundingRectTop + p.boundingRectHeight / 2.0
};
double dist =
Math.sqrt(
(mid[0] - target[0]) * (mid[0] - target[0])
+ (mid[1] - target[1]) * (mid[1] - target[1]));
if (minDist == -1 || minDist > dist) {
minDist = dist;
minMid = mid;
}
}
if (minDist != -1) {
if (minMid[1] > target[1] + RobotMap.errorMargin) moveDown();
else if (minMid[1] < target[1] - RobotMap.errorMargin) moveUp();
else stopMove();
if (minMid[0] > target[0] + RobotMap.errorMargin) turnRight();
else if (minMid[0] < target[0] - RobotMap.errorMargin) turnLeft();
else turnStop();
if (stopped1 && stopped2) {
done = true;
return;
}
} else {
done = true;
return;
}
filteredImage.free();
convexHullImage.free();
thresholdImage.free();
image.free();
// } catch (AxisCameraException ex) { // this is needed if the
// camera.getImage() is called
// ex.printStackTrace();
} catch (NIVisionException ex) {
ex.printStackTrace();
} catch (AxisCameraException ace) {
ace.printStackTrace();
}
}
public TargetScores[] visionAnalyze() {
// TargetScores[] tScores_Out;// = new TargetScores[1][];
TargetScores[] tScores = null;
try {
/**
* Do the image capture with the camera and apply the algorithm described above. This sample
* will either get images from the camera or from an image file stored in the top level
* directory in the flash memory on the cRIO. The file name in this case is "testImage.jpg"
*/
ColorImage image = camera.getImage(); // comment if using stored images
// ColorImage image; // next 2 lines read image from flash on cRIO
// image = new RGBImage("/testImage.jpg"); // get the sample image from the cRIO flash
BinaryImage thresholdImage =
image.thresholdHSV(60, 100, 90, 255, 20, 255); // keep only red objects
// thresholdImage.write("/threshold.bmp");
BinaryImage convexHullImage = thresholdImage.convexHull(false); // fill in occluded rectangles
// convexHullImage.write("/convexHull.bmp");
BinaryImage filteredImage = convexHullImage.particleFilter(cc); // filter out small particles
// filteredImage.write("/filteredImage.bmp");
// iterate through each particle and score to see if it is a target
Scores scores[] = new Scores[filteredImage.getNumberParticles()];
tScores = new TargetScores[filteredImage.getNumberParticles()];
for (int i = 0; i < scores.length; i++) {
ParticleAnalysisReport report = filteredImage.getParticleAnalysisReport(i);
scores[i] = new Scores();
tScores[i] = new TargetScores();
scores[i].rectangularity = scoreRectangularity(report);
scores[i].aspectRatioOuter = scoreAspectRatio(filteredImage, report, i, true);
scores[i].aspectRatioInner = scoreAspectRatio(filteredImage, report, i, false);
scores[i].xEdge = scoreXEdge(thresholdImage, report);
scores[i].yEdge = scoreYEdge(thresholdImage, report);
if (scoreCompare(scores[i], false)) {
tScores[i].goal = TargetScores.high;
} else if (scoreCompare(scores[i], true)) {
tScores[i].goal = TargetScores.med;
}
tScores[i].yVal = report.center_mass_y;
tScores[i].xVal = report.center_mass_x;
tScores[i].yValAim = axisToAim('y', tScores[i].yVal);
/*
if(scoreCompare(scores[i], false))
{
System.out.println("particle: " + i + "is a High Goal centerX: " + report.center_mass_x_normalized + "centerY: " + report.center_mass_y_normalized);
System.out.println("Distance: " + computeDistance(thresholdImage, report, i, false));
} else if (scoreCompare(scores[i], true)) {
System.out.println("particle: " + i + "is a Middle Goal centerX: " + report.center_mass_x_normalized + "centerY: " + report.center_mass_y_normalized);
System.out.println("Distance: " + computeDistance(thresholdImage, report, i, true));
} else {
System.out.println("particle: " + i + "is not a goal centerX: " + report.center_mass_x_normalized + "centerY: " + report.center_mass_y_normalized);
}
System.out.println("rect: " + scores[i].rectangularity + "ARinner: " + scores[i].aspectRatioInner);
System.out.println("ARouter: " + scores[i].aspectRatioOuter + "xEdge: " + scores[i].xEdge + "yEdge: " + scores[i].yEdge);
*/
}
/**
* all images in Java must be freed after they are used since they are allocated out of C data
* structures. Not calling free() will cause the memory to accumulate over each pass of this
* loop.
*/
filteredImage.free();
convexHullImage.free();
thresholdImage.free();
image.free();
// tScores_Out = new TargetScores[tScores.length];
// tScores_Out = (TargetScores[])tScores.clone();
// myScores = scores;
} catch (AxisCameraException ex) { // this is needed if the camera.getImage() is called
ex.printStackTrace();
} catch (NIVisionException ex) {
ex.printStackTrace();
}
if (tScores == null) {
tScores = new TargetScores[1];
tScores[1] = new NoScores();
}
return tScores; // tScores_Out;
}
