NI Vision Code Example Not Working

I was attempting to use the example vision code from the newest NI Vision library however it created an error. Has anyone else found this to be true or have I done something wrong?

Please post the example and the error so we can help diagnose the issue.

package $package;

import java.lang.Math;
import java.util.Comparator;
import java.util.Vector;


import edu.wpi.first.wpilibj.CameraServer;
import edu.wpi.first.wpilibj.SampleRobot;
import edu.wpi.first.wpilibj.Timer;
import edu.wpi.first.wpilibj.smartdashboard.SmartDashboard;

 * Example of finding yellow totes based on color.
 * This example utilizes an image file, which you need to copy to the roboRIO
 * To use a camera you will have to integrate the appropriate camera details with this example.
 * To use a USB camera instead, see the SimpelVision and AdvancedVision examples for details
 * on using the USB camera. To use an Axis Camera, see the AxisCamera example for details on
 * using an Axis Camera.
 * Sample omages can be found here:
public class Robot extends SampleRobot {
        //A structure to hold measurements of a particle
        public class ParticleReport implements Comparator<ParticleReport>, Comparable<ParticleReport>{
            double PercentAreaToImageArea;
            double Area;
            double ConvexHullArea;
            double BoundingRectLeft;
            double BoundingRectTop;
            double BoundingRectRight;
            double BoundingRectBottom;

            public int compareTo(ParticleReport r)
                return (int)(r.Area - this.Area);

            public int compare(ParticleReport r1, ParticleReport r2)
                return (int)(r1.Area - r2.Area);

        //Structure to represent the scores for the various tests used for target identification
        public class Scores {
            double Trapezoid;
            double LongAspect;
            double ShortAspect;
            double AreaToConvexHullArea;

        Image frame;
        Image binaryFrame;
        int imaqError;

        NIVision.Range TOTE_HUE_RANGE = new NIVision.Range(24, 49);    //Default hue range for yellow tote
        NIVision.Range TOTE_SAT_RANGE = new NIVision.Range(67, 255);    //Default saturation range for yellow tote
        NIVision.Range TOTE_VAL_RANGE = new NIVision.Range(49, 255);    //Default value range for yellow tote
        double AREA_MINIMUM = 0.5; //Default Area minimum for particle as a percentage of total image area
        double LONG_RATIO = 2.22; //Tote long side = 26.9 / Tote height = 12.1 = 2.22
        double SHORT_RATIO = 1.4; //Tote short side = 16.9 / Tote height = 12.1 = 1.4
        double SCORE_MIN = 75.0;  //Minimum score to be considered a tote
        double VIEW_ANGLE = 49.4; //View angle fo camera, set to Axis m1011 by default, 64 for m1013, 51.7 for 206, 52 for HD3000 square, 60 for HD3000 640x480
        NIVision.ParticleFilterCriteria2 criteria] = new NIVision.ParticleFilterCriteria2[1];
        NIVision.ParticleFilterOptions2 filterOptions = new NIVision.ParticleFilterOptions2(0,0,1,1);
        Scores scores = new Scores();

        public void robotInit() {
            // create images
            frame = NIVision.imaqCreateImage(ImageType.IMAGE_RGB, 0);
            binaryFrame = NIVision.imaqCreateImage(ImageType.IMAGE_U8, 0);
            criteria[0] = new NIVision.ParticleFilterCriteria2(NIVision.MeasurementType.MT_AREA_BY_IMAGE_AREA, AREA_MINIMUM, 100.0, 0, 0);

            //Put default values to SmartDashboard so fields will appear
            SmartDashboard.putNumber("Tote hue min", TOTE_HUE_RANGE.minValue);
            SmartDashboard.putNumber("Tote hue max", TOTE_HUE_RANGE.maxValue);
            SmartDashboard.putNumber("Tote sat min", TOTE_SAT_RANGE.minValue);
            SmartDashboard.putNumber("Tote sat max", TOTE_SAT_RANGE.maxValue);
            SmartDashboard.putNumber("Tote val min", TOTE_VAL_RANGE.minValue);
            SmartDashboard.putNumber("Tote val max", TOTE_VAL_RANGE.maxValue);
            SmartDashboard.putNumber("Area min %", AREA_MINIMUM);

        public void autonomous() {
            while (isAutonomous() && isEnabled())
                //read file in from disk. For this example to run you need to copy image20.jpg from the SampleImages folder to the
                //directory shown below using FTP or SFTP:
                NIVision.imaqReadFile(frame, "/home/lvuser/SampleImages/image20.jpg");

                //Update threshold values from SmartDashboard. For performance reasons it is recommended to remove this after calibration is finished.
                TOTE_HUE_RANGE.minValue = (int)SmartDashboard.getNumber("Tote hue min", TOTE_HUE_RANGE.minValue);
                TOTE_HUE_RANGE.maxValue = (int)SmartDashboard.getNumber("Tote hue max", TOTE_HUE_RANGE.maxValue);
                TOTE_SAT_RANGE.minValue = (int)SmartDashboard.getNumber("Tote sat min", TOTE_SAT_RANGE.minValue);
                TOTE_SAT_RANGE.maxValue = (int)SmartDashboard.getNumber("Tote sat max", TOTE_SAT_RANGE.maxValue);
                TOTE_VAL_RANGE.minValue = (int)SmartDashboard.getNumber("Tote val min", TOTE_VAL_RANGE.minValue);
                TOTE_VAL_RANGE.maxValue = (int)SmartDashboard.getNumber("Tote val max", TOTE_VAL_RANGE.maxValue);

                //Threshold the image looking for yellow (tote color)
                NIVision.imaqColorThreshold(binaryFrame, frame, 255, NIVision.ColorMode.HSV, TOTE_HUE_RANGE, TOTE_SAT_RANGE, TOTE_VAL_RANGE);

                //Send particle count to dashboard
                int numParticles = NIVision.imaqCountParticles(binaryFrame, 1);
                SmartDashboard.putNumber("Masked particles", numParticles);

                //Send masked image to dashboard to assist in tweaking mask.

                //filter out small particles
                float areaMin = (float)SmartDashboard.getNumber("Area min %", AREA_MINIMUM);
                criteria[0].lower = areaMin;
                imaqError = NIVision.imaqParticleFilter4(binaryFrame, binaryFrame, criteria, filterOptions, null);

                //Send particle count after filtering to dashboard
                numParticles = NIVision.imaqCountParticles(binaryFrame, 1);
                SmartDashboard.putNumber("Filtered particles", numParticles);

                if(numParticles > 0)
                    //Measure particles and sort by particle size
                    Vector<ParticleReport> particles = new Vector<ParticleReport>();
                    for(int particleIndex = 0; particleIndex < numParticles; particleIndex++)
                        ParticleReport par = new ParticleReport();
                        par.PercentAreaToImageArea = NIVision.imaqMeasureParticle(binaryFrame, particleIndex, 0, NIVision.MeasurementType.MT_AREA_BY_IMAGE_AREA);
                        par.Area = NIVision.imaqMeasureParticle(binaryFrame, particleIndex, 0, NIVision.MeasurementType.MT_AREA);
                        par.ConvexHullArea = NIVision.imaqMeasureParticle(binaryFrame, particleIndex, 0, NIVision.MeasurementType.MT_CONVEX_HULL_AREA);
                        par.BoundingRectTop = NIVision.imaqMeasureParticle(binaryFrame, particleIndex, 0, NIVision.MeasurementType.MT_BOUNDING_RECT_TOP);
                        par.BoundingRectLeft = NIVision.imaqMeasureParticle(binaryFrame, particleIndex, 0, NIVision.MeasurementType.MT_BOUNDING_RECT_LEFT);
                        par.BoundingRectBottom = NIVision.imaqMeasureParticle(binaryFrame, particleIndex, 0, NIVision.MeasurementType.MT_BOUNDING_RECT_BOTTOM);
                        par.BoundingRectRight = NIVision.imaqMeasureParticle(binaryFrame, particleIndex, 0, NIVision.MeasurementType.MT_BOUNDING_RECT_RIGHT);

                    //This example only scores the largest particle. Extending to score all particles and choosing the desired one is left as an exercise
                    //for the reader. Note that the long and short side scores expect a single tote and will not work for a stack of 2 or more totes.
                    //Modification of the code to accommodate 2 or more stacked totes is left as an exercise for the reader.
                    scores.Trapezoid = TrapezoidScore(particles.elementAt(0));
                    SmartDashboard.putNumber("Trapezoid", scores.Trapezoid);
                    scores.LongAspect = LongSideScore(particles.elementAt(0));
                    SmartDashboard.putNumber("Long Aspect", scores.LongAspect);
                    scores.ShortAspect = ShortSideScore(particles.elementAt(0));
                    SmartDashboard.putNumber("Short Aspect", scores.ShortAspect);
                    scores.AreaToConvexHullArea = ConvexHullAreaScore(particles.elementAt(0));
                    SmartDashboard.putNumber("Convex Hull Area", scores.AreaToConvexHullArea);
                    boolean isTote = scores.Trapezoid > SCORE_MIN && (scores.LongAspect > SCORE_MIN || scores.ShortAspect > SCORE_MIN) && scores.AreaToConvexHullArea > SCORE_MIN;
                    boolean isLong = scores.LongAspect > scores.ShortAspect;

                    //Send distance and tote status to dashboard. The bounding rect, particularly the horizontal center (left - right) may be useful for rotating/driving towards a tote
                    SmartDashboard.putBoolean("IsTote", isTote);
                    SmartDashboard.putNumber("Distance", computeDistance(binaryFrame, particles.elementAt(0), isLong));
                } else {
                    SmartDashboard.putBoolean("IsTote", false);

                Timer.delay(0.005);                // wait for a motor update time

        public void operatorControl() {
            while(isOperatorControl() && isEnabled()) {
                Timer.delay(0.005);                // wait for a motor update time

        //Comparator function for sorting particles. Returns true if particle 1 is larger
        static boolean CompareParticleSizes(ParticleReport particle1, ParticleReport particle2)
            //we want descending sort order
            return particle1.PercentAreaToImageArea > particle2.PercentAreaToImageArea;

         * Converts a ratio with ideal value of 1 to a score. The resulting function is piecewise
         * linear going from (0,0) to (1,100) to (2,0) and is 0 for all inputs outside the range 0-2
        double ratioToScore(double ratio)
            return (Math.max(0, Math.min(100*(1-Math.abs(1-ratio)), 100)));

         * Method to score convex hull area. This scores how "complete" the particle is. Particles with large holes will score worse than a filled in shape
        double ConvexHullAreaScore(ParticleReport report)
            return ratioToScore((report.Area/report.ConvexHullArea)*1.18);

         * Method to score if the particle appears to be a trapezoid. Compares the convex hull (filled in) area to the area of the bounding box.
         * The expectation is that the convex hull area is about 95.4% of the bounding box area for an ideal tote.
        double TrapezoidScore(ParticleReport report)
            return ratioToScore(report.ConvexHullArea/((report.BoundingRectRight-report.BoundingRectLeft)*(report.BoundingRectBottom-report.BoundingRectTop)*.954));

         * Method to score if the aspect ratio of the particle appears to match the long side of a tote.
        double LongSideScore(ParticleReport report)
            return ratioToScore(((report.BoundingRectRight-report.BoundingRectLeft)/(report.BoundingRectBottom-report.BoundingRectTop))/LONG_RATIO);

         * Method to score if the aspect ratio of the particle appears to match the short side of a tote.
        double ShortSideScore(ParticleReport report){
            return ratioToScore(((report.BoundingRectRight-report.BoundingRectLeft)/(report.BoundingRectBottom-report.BoundingRectTop))/SHORT_RATIO);

         * Computes the estimated distance to a target using the width of the particle in the image. For more information and graphics
         * showing the math behind this approach see the Vision Processing section of the ScreenStepsLive documentation.
         * @param image The image to use for measuring the particle estimated rectangle
         * @param report The Particle Analysis Report for the particle
         * @param isLong Boolean indicating if the target is believed to be the long side of a tote
         * @return The estimated distance to the target in feet.
        double computeDistance (Image image, ParticleReport report, boolean isLong) {
            double normalizedWidth, targetWidth;
            NIVision.GetImageSizeResult size;

            size = NIVision.imaqGetImageSize(image);
            normalizedWidth = 2*(report.BoundingRectRight - report.BoundingRectLeft)/size.width;
            targetWidth = isLong ? 26.0 : 16.9;

            return  targetWidth/(normalizedWidth*12*Math.tan(VIEW_ANGLE*Math.PI/(180*2)));

This is the example that came with the NI Vision Library however


Gives an error that the setImage() method does not exist

Remove the

import edu.wpi.first.wpilibj.CameraServer;

line, and replace that with


I’ll fix the examples. The issue is it’s attempting to use the new CameraServer. However, we do recommend switching to the new CameraServer and OpenCV, as the LabVIEW and SmartDashboard camera viewers will not by default connect to the NiVision camera server.

Thank you so much

Is there a way to configure the SmartDashboard to work with the NIVision CameraServer? We just want to post a processed NIVision image back to the dashboard. Previously we used CameraServer.getInstance().setImage().

I think the repo here has the code to add the old viewer back in, but I don’t know exactly how to install it.