/**
* 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 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;
}