A slightly modified (updated for 2013 libraries) version of the Miss Daisy 2012 robot vision code.
git-svn-id: https://robotics.mvla.net/svn/frc971/2013/trunk/src@4110 f308d9b7-e957-4cde-b6ac-9a88185e7312
diff --git a/DaisyCV/.classpath b/DaisyCV/.classpath
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+<?xml version="1.0" encoding="UTF-8"?>
+<classpath>
+ <classpathentry kind="src" path="src"/>
+ <classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER"/>
+ <classpathentry kind="lib" path="C:/Program Files/SmartDashboard/SmartDashboard.jar" sourcepath="C:/sourcecontrolled/FIRSTforge/SmartDashboard/trunk/smartdashboard/src">
+ <attributes>
+ <attribute name="javadoc_location" value="jar:file:/C:/WindRiver/WPILib/SmartDashboard.javadoc.zip!/"/>
+ </attributes>
+ </classpathentry>
+ <classpathentry kind="lib" path="C:/Program Files/SmartDashboard/extensions/WPICameraExtension.jar" sourcepath="C:/sourcecontrolled/FIRSTforge/SmartDashboard/trunk/extensions"/>
+ <classpathentry kind="lib" path="C:/Program Files/SmartDashboard/extensions/lib/javacpp.jar"/>
+ <classpathentry kind="lib" path="C:/Program Files/SmartDashboard/extensions/lib/javacv.jar">
+ <attributes>
+ <attribute name="org.eclipse.jdt.launching.CLASSPATH_ATTR_LIBRARY_PATH_ENTRY" value="C:/Program Files/WPIJavaCV/OpenCV_2.2.0/bin"/>
+ </attributes>
+ </classpathentry>
+ <classpathentry kind="lib" path="C:/Program Files/SmartDashboard/extensions/lib/javacv-windows-x86.jar">
+ <attributes>
+ <attribute name="org.eclipse.jdt.launching.CLASSPATH_ATTR_LIBRARY_PATH_ENTRY" value="C:/Program Files/WPIJavaCV/JavaCV_2.2.0/javacv-bin"/>
+ </attributes>
+ </classpathentry>
+ <classpathentry kind="lib" path="C:/Program Files/SmartDashboard/extensions/lib/WPIJavaCV.jar" sourcepath="C:/sourcecontrolled/FIRSTforge/SmartDashboard/trunk/WPIJavaCV/src"/>
+ <classpathentry kind="lib" path="C:/WindRiver/WPILib/desktop-lib/networktables-desktop.jar" sourcepath="C:/WindRiver/WPILib/desktop-lib/networktables-desktop.src.zip">
+ <attributes>
+ <attribute name="javadoc_location" value="jar:file:/C:/WindRiver/WPILib/desktop-lib/networktables-desktop.javadoc.zip!/"/>
+ </attributes>
+ </classpathentry>
+ <classpathentry kind="output" path="bin"/>
+</classpath>
diff --git a/DaisyCV/.project b/DaisyCV/.project
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+++ b/DaisyCV/.project
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+<?xml version="1.0" encoding="UTF-8"?>
+<projectDescription>
+ <name>DaisyCV</name>
+ <comment></comment>
+ <projects>
+ </projects>
+ <buildSpec>
+ <buildCommand>
+ <name>org.eclipse.jdt.core.javabuilder</name>
+ <arguments>
+ </arguments>
+ </buildCommand>
+ </buildSpec>
+ <natures>
+ <nature>org.eclipse.jdt.core.javanature</nature>
+ </natures>
+</projectDescription>
diff --git a/DaisyCV/green-test-images/image-01.jpg b/DaisyCV/green-test-images/image-01.jpg
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diff --git a/DaisyCV/green-test-images/image-02.jpg b/DaisyCV/green-test-images/image-02.jpg
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diff --git a/DaisyCV/green-test-images/image-03.jpg b/DaisyCV/green-test-images/image-03.jpg
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diff --git a/DaisyCV/green-test-images/image-08.jpg b/DaisyCV/green-test-images/image-08.jpg
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diff --git a/DaisyCV/green-test-images/image-09.jpg b/DaisyCV/green-test-images/image-09.jpg
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diff --git a/DaisyCV/green-test-images/image-11.jpg b/DaisyCV/green-test-images/image-11.jpg
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diff --git a/DaisyCV/green-test-images/image-12.jpg b/DaisyCV/green-test-images/image-12.jpg
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diff --git a/DaisyCV/src/edu/missdaisy/smartdashboard/daisycv/DaisyCVWidget.java b/DaisyCV/src/edu/missdaisy/smartdashboard/daisycv/DaisyCVWidget.java
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+++ b/DaisyCV/src/edu/missdaisy/smartdashboard/daisycv/DaisyCVWidget.java
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+package edu.missdaisy.smartdashboard.daisycv;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.NoSuchElementException;
+import java.util.Scanner;
+import java.util.TreeMap;
+
+import javax.imageio.ImageIO;
+
+import com.googlecode.javacv.CanvasFrame;
+import com.googlecode.javacv.cpp.opencv_core;
+import com.googlecode.javacv.cpp.opencv_core.CvSize;
+import com.googlecode.javacv.cpp.opencv_core.IplImage;
+import com.googlecode.javacv.cpp.opencv_imgproc;
+import com.googlecode.javacv.cpp.opencv_imgproc.IplConvKernel;
+
+import edu.wpi.first.smartdashboard.camera.WPICameraExtension;
+import edu.wpi.first.smartdashboard.gui.DashboardFrame;
+import edu.wpi.first.smartdashboard.robot.Robot;
+import edu.wpi.first.wpijavacv.DaisyExtensions;
+import edu.wpi.first.wpijavacv.WPIBinaryImage;
+import edu.wpi.first.wpijavacv.WPIColor;
+import edu.wpi.first.wpijavacv.WPIColorImage;
+import edu.wpi.first.wpijavacv.WPIContour;
+import edu.wpi.first.wpijavacv.WPIImage;
+import edu.wpi.first.wpijavacv.WPIPoint;
+import edu.wpi.first.wpijavacv.WPIPolygon;
+
+/* HOW TO GET THIS COMPILING:
+ * 1. Install the SmartDashboard using the installer (if on Windows)
+ * 1a. Verify that the OpenCV libraries are in your PATH (on Windows)
+ * 2. Add the following libraries to the project:
+ * SmartDashboard.jar
+ * extensions/WPICameraExtension.jar
+ * lib/NetworkTable_Client.jar
+ * extensions/lib/javacpp.jar
+ * extensions/lib/javacv-*your environment*.jar
+ * extensions/lib/javacv.jar
+ * extensions/lib/WPIJavaCV.jar
+ *
+ */
+/**
+ * @author jrussell
+ */
+@SuppressWarnings("serial")
+public class DaisyCVWidget extends WPICameraExtension
+{
+ public static final String NAME = "DaisyCV Target Tracker";
+ private WPIColor targetColor = new WPIColor(255, 0, 0);
+
+ // Constants that need to be tuned
+ private static final double kNearlyHorizontalSlope = Math.tan(Math.toRadians(20));
+ private static final double kNearlyVerticalSlope = Math.tan(Math.toRadians(90-20));
+ private static final int kMinWidth = 20;
+ private static final int kMaxWidth = 200;
+ private static final double kRangeOffset = 0.0;
+ private static final int kHoleClosingIterations = 9;
+
+ private static final double kShooterOffsetDeg = -1.55;
+ private static final double kHorizontalFOVDeg = 47.0;
+
+ private static final double kVerticalFOVDeg = 480.0/640.0*kHorizontalFOVDeg;
+ private static final double kCameraHeightIn = 54.0;
+ private static final double kCameraPitchDeg = 21.0;
+ private static final double kTopTargetHeightIn = 98.0 + 2.0 + 9.0; // 98 to rim, +2 to bottom of target, +9 to center of target
+
+ private TreeMap<Double, Double> rangeTable;
+
+ private boolean m_debugMode = false;
+
+ // Store JavaCV temporaries as members to reduce memory management during processing
+ private CvSize size = null;
+ private WPIContour[] contours;
+ private ArrayList<WPIPolygon> polygons;
+ private IplConvKernel morphKernel;
+ private IplImage bin;
+ private IplImage hsv;
+ private IplImage hue;
+ private IplImage sat;
+ private IplImage val;
+ private WPIPoint linePt1;
+ private WPIPoint linePt2;
+ private int horizontalOffsetPixels;
+
+ public DaisyCVWidget()
+ {
+ this(false);
+ }
+
+ public DaisyCVWidget(boolean debug)
+ {
+ m_debugMode = debug;
+ morphKernel = IplConvKernel.create(3, 3, 1, 1, opencv_imgproc.CV_SHAPE_RECT, null);
+
+ rangeTable = new TreeMap<Double,Double>();
+ //rangeTable.put(110.0, 3800.0+kRangeOffset);
+ //rangeTable.put(120.0, 3900.0+kRangeOffset);
+ //rangeTable.put(130.0, 4000.0+kRangeOffset);
+ rangeTable.put(140.0, 3434.0+kRangeOffset);
+ rangeTable.put(150.0, 3499.0+kRangeOffset);
+ rangeTable.put(160.0, 3544.0+kRangeOffset);
+ rangeTable.put(170.0, 3574.0+kRangeOffset);
+ rangeTable.put(180.0, 3609.0+kRangeOffset);
+ rangeTable.put(190.0, 3664.0+kRangeOffset);
+ rangeTable.put(200.0, 3854.0+kRangeOffset);
+ rangeTable.put(210.0, 4034.0+kRangeOffset);
+ rangeTable.put(220.0, 4284.0+kRangeOffset);
+ rangeTable.put(230.0, 4434.0+kRangeOffset);
+ rangeTable.put(240.0, 4584.0+kRangeOffset);
+ rangeTable.put(250.0, 4794.0+kRangeOffset);
+ rangeTable.put(260.0, 5034.0+kRangeOffset);
+ rangeTable.put(270.0, 5234.0+kRangeOffset);
+
+ DaisyExtensions.init();
+ }
+
+
+ public double getRPMsForRange(double range)
+ {
+ double lowKey = -1.0;
+ double lowVal = -1.0;
+ for( double key : rangeTable.keySet() )
+ {
+ if( range < key )
+ {
+ double highVal = rangeTable.get(key);
+ if( lowKey > 0.0 )
+ {
+ double m = (range-lowKey)/(key-lowKey);
+ return lowVal+m*(highVal-lowVal);
+ }
+ else
+ return highVal;
+ }
+ lowKey = key;
+ lowVal = rangeTable.get(key);
+ }
+
+ return 5234.0+kRangeOffset;
+ }
+
+ @Override
+ public WPIImage processImage(WPIColorImage rawImage)
+ {
+ double heading = 0.0;
+
+ // Get the current heading of the robot first
+ if( !m_debugMode )
+ {
+ try
+ {
+ heading = Robot.getTable().getNumber("Heading");
+ }
+ catch( NoSuchElementException e)
+ {
+ }
+ catch( IllegalArgumentException e )
+ {
+ }
+ }
+
+ if( size == null || size.width() != rawImage.getWidth() || size.height() != rawImage.getHeight() )
+ {
+ size = opencv_core.cvSize(rawImage.getWidth(),rawImage.getHeight());
+ bin = IplImage.create(size, 8, 1);
+ hsv = IplImage.create(size, 8, 3);
+ hue = IplImage.create(size, 8, 1);
+ sat = IplImage.create(size, 8, 1);
+ val = IplImage.create(size, 8, 1);
+ horizontalOffsetPixels = (int)Math.round(kShooterOffsetDeg*(size.width()/kHorizontalFOVDeg));
+ linePt1 = new WPIPoint(size.width()/2+horizontalOffsetPixels,size.height()-1);
+ linePt2 = new WPIPoint(size.width()/2+horizontalOffsetPixels,0);
+ }
+ // Get the raw IplImages for OpenCV
+ IplImage input = DaisyExtensions.getIplImage(rawImage);
+
+ // Convert to HSV color space
+ opencv_imgproc.cvCvtColor(input, hsv, opencv_imgproc.CV_BGR2HSV);
+ opencv_core.cvSplit(hsv, hue, sat, val, null);
+
+ // Threshold each component separately
+ // Hue
+ // NOTE: Red is at the end of the color space, so you need to OR together
+ // a thresh and inverted thresh in order to get points that are red
+ opencv_imgproc.cvThreshold(hue, bin, 60-15, 255, opencv_imgproc.CV_THRESH_BINARY);
+ opencv_imgproc.cvThreshold(hue, hue, 60+15, 255, opencv_imgproc.CV_THRESH_BINARY_INV);
+
+ // Saturation
+ opencv_imgproc.cvThreshold(sat, sat, 200, 255, opencv_imgproc.CV_THRESH_BINARY);
+
+ // Value
+ opencv_imgproc.cvThreshold(val, val, 55, 255, opencv_imgproc.CV_THRESH_BINARY);
+
+ // Combine the results to obtain our binary image which should for the most
+ // part only contain pixels that we care about
+ opencv_core.cvAnd(hue, bin, bin, null);
+ opencv_core.cvAnd(bin, sat, bin, null);
+ opencv_core.cvAnd(bin, val, bin, null);
+
+ // Uncomment the next two lines to see the raw binary image
+ //CanvasFrame result = new CanvasFrame("binary");
+ //result.showImage(bin.getBufferedImage());
+
+ // Fill in any gaps using binary morphology
+ opencv_imgproc.cvMorphologyEx(bin, bin, null, morphKernel, opencv_imgproc.CV_MOP_CLOSE, kHoleClosingIterations);
+
+ // Uncomment the next two lines to see the image post-morphology
+ //CanvasFrame result2 = new CanvasFrame("morph");
+ //result2.showImage(bin.getBufferedImage());
+
+ // Find contours
+ WPIBinaryImage binWpi = DaisyExtensions.makeWPIBinaryImage(bin);
+ contours = DaisyExtensions.findConvexContours(binWpi);
+
+ polygons = new ArrayList<WPIPolygon>();
+ for (WPIContour c : contours)
+ {
+ double ratio = ((double) c.getHeight()) / ((double) c.getWidth());
+ if (ratio < 1.0 && ratio > 0.5 && c.getWidth() > kMinWidth && c.getWidth() < kMaxWidth)
+ {
+ polygons.add(c.approxPolygon(20));
+ }
+ }
+
+ WPIPolygon square = null;
+ int highest = Integer.MAX_VALUE;
+
+ for (WPIPolygon p : polygons)
+ {
+ if (p.isConvex() && p.getNumVertices() == 4)
+ {
+ // We passed the first test...we fit a rectangle to the polygon
+ // Now do some more tests
+
+ WPIPoint[] points = p.getPoints();
+ // We expect to see a top line that is nearly horizontal, and two side lines that are nearly vertical
+ int numNearlyHorizontal = 0;
+ int numNearlyVertical = 0;
+ for( int i = 0; i < 4; i++ )
+ {
+ double dy = points[i].getY() - points[(i+1) % 4].getY();
+ double dx = points[i].getX() - points[(i+1) % 4].getX();
+ double slope = Double.MAX_VALUE;
+ if( dx != 0 )
+ slope = Math.abs(dy/dx);
+
+ if( slope < kNearlyHorizontalSlope )
+ ++numNearlyHorizontal;
+ else if( slope > kNearlyVerticalSlope )
+ ++numNearlyVertical;
+ }
+
+ if(numNearlyHorizontal >= 1 && numNearlyVertical == 2)
+ {
+ rawImage.drawPolygon(p, WPIColor.BLUE, 2);
+
+ int pCenterX = (p.getX() + (p.getWidth() / 2));
+ int pCenterY = (p.getY() + (p.getHeight() / 2));
+
+ rawImage.drawPoint(new WPIPoint(pCenterX, pCenterY), targetColor, 5);
+ if (pCenterY < highest) // Because coord system is funny
+ {
+ square = p;
+ highest = pCenterY;
+ }
+ }
+ }
+ else
+ {
+ rawImage.drawPolygon(p, WPIColor.YELLOW, 1);
+ }
+ }
+
+ if (square != null)
+ {
+ double x = square.getX() + (square.getWidth() / 2);
+ x = (2 * (x / size.width())) - 1;
+ double y = square.getY() + (square.getHeight() / 2);
+ y = -((2 * (y / size.height())) - 1);
+
+ double azimuth = this.boundAngle0to360Degrees(x*kHorizontalFOVDeg/2.0 + heading - kShooterOffsetDeg);
+ double range = (kTopTargetHeightIn-kCameraHeightIn)/Math.tan((y*kVerticalFOVDeg/2.0 + kCameraPitchDeg)*Math.PI/180.0);
+ double rpms = getRPMsForRange(range);
+
+ if (!m_debugMode)
+ {
+
+// Robot.getTable().beginTransaction();
+ Robot.getTable().putBoolean("found", true);
+ Robot.getTable().putNumber("azimuth", azimuth);
+ Robot.getTable().putNumber("rpms", rpms);
+// Robot.getTable().endTransaction();
+ } else
+ {
+ System.out.println("Target found");
+ System.out.println("x: " + x);
+ System.out.println("y: " + y);
+ System.out.println("azimuth: " + azimuth);
+ System.out.println("range: " + range);
+ System.out.println("rpms: " + rpms);
+ }
+ rawImage.drawPolygon(square, targetColor, 7);
+ } else
+ {
+
+ if (!m_debugMode)
+ {
+ Robot.getTable().putBoolean("found", false);
+ } else
+ {
+ System.out.println("Target not found");
+ }
+ }
+
+ // Draw a crosshair
+ rawImage.drawLine(linePt1, linePt2, targetColor, 2);
+
+ DaisyExtensions.releaseMemory();
+
+ //System.gc();
+
+ return rawImage;
+ }
+
+ private double boundAngle0to360Degrees(double angle)
+ {
+ // Naive algorithm
+ while(angle >= 360.0)
+ {
+ angle -= 360.0;
+ }
+ while(angle < 0.0)
+ {
+ angle += 360.0;
+ }
+ return angle;
+ }
+
+ public static void main(String[] args)
+ {
+ if (args.length == 0)
+ {
+ System.out.println("Usage: Arguments are paths to image files to test the program on");
+ return;
+ }
+
+ DashboardFrame frame = new DashboardFrame(false); // suggested 2013 adaptation
+ frame.getPrefs();
+
+ // Create the widget
+ DaisyCVWidget widget = new DaisyCVWidget(true);
+ CanvasFrame original = new CanvasFrame("Raw");
+ CanvasFrame result = new CanvasFrame("Result");
+
+ long totalTime = 0;
+ for (int i = 0; i < args.length; i++)
+ {
+ // Load the image
+ WPIColorImage rawImage = null;
+ try
+ {
+ rawImage = new WPIColorImage(ImageIO.read(new File(args[i%args.length])));
+ } catch (IOException e)
+ {
+ System.err.println("Could not find file!");
+ return;
+ }
+
+ //shows the raw image before processing to eliminate the possibility
+ //that both may be the modified image.
+ original.showImage(rawImage.getBufferedImage());
+
+ WPIImage resultImage = null;
+
+ // Process image
+ long startTime, endTime;
+ startTime = System.nanoTime();
+ resultImage = widget.processImage(rawImage);
+ endTime = System.nanoTime();
+
+ // Display results
+ totalTime += (endTime - startTime);
+ double milliseconds = (double) (endTime - startTime) / 1000000.0;
+ System.out.format("Processing took %.2f milliseconds%n", milliseconds);
+ System.out.format("(%.2f frames per second)%n", 1000.0 / milliseconds);
+
+ result.showImage(resultImage.getBufferedImage());
+
+ System.out.println("Waiting for ENTER to continue to next image or exit...");
+ Scanner console = new Scanner(System.in);
+ console.nextLine();
+ }
+
+ if (original.isVisible())
+ {
+ original.setVisible(false);
+ original.dispose();
+ }
+ if (result.isVisible())
+ {
+ result.setVisible(false);
+ result.dispose();
+ }
+
+ double milliseconds = (double) (totalTime) / 1000000.0 / (args.length);
+ System.out.format("AVERAGE:%.2f milliseconds%n", milliseconds);
+ System.out.format("(%.2f frames per second)%n", 1000.0 / milliseconds);
+ System.exit(0);
+ }
+}
diff --git a/DaisyCV/src/edu/wpi/first/wpijavacv/DaisyExtensions.java b/DaisyCV/src/edu/wpi/first/wpijavacv/DaisyExtensions.java
new file mode 100644
index 0000000..41f12a1
--- /dev/null
+++ b/DaisyCV/src/edu/wpi/first/wpijavacv/DaisyExtensions.java
@@ -0,0 +1,89 @@
+package edu.wpi.first.wpijavacv;
+
+import java.util.ArrayList;
+
+import com.googlecode.javacv.cpp.opencv_core;
+import com.googlecode.javacv.cpp.opencv_core.CvMemStorage;
+import com.googlecode.javacv.cpp.opencv_core.CvSeq;
+import com.googlecode.javacv.cpp.opencv_core.IplImage;
+import com.googlecode.javacv.cpp.opencv_imgproc;
+
+/**
+ *
+ * @author jrussell
+ */
+public class DaisyExtensions
+{
+ public static CvSeq getCvSeq(WPIContour contour)
+ {
+ return contour.getCVSeq();
+ }
+
+ public static WPIContour makeWPIContour(CvSeq seq)
+ {
+ return new WPIContour(seq);
+ }
+
+ public static WPIGrayscaleImage makeWPIGrayscaleImage(IplImage arr)
+ {
+ IplImage tempImage = IplImage.create(arr.cvSize(), arr.depth(), 1);
+ opencv_core.cvCopy(arr, tempImage);
+ return new WPIGrayscaleImage(tempImage);
+ }
+
+ public static WPIColorImage makeWPIColorImage(IplImage arr)
+ {
+ IplImage tempImage = IplImage.create(arr.cvSize(), arr.depth(), 1);
+ opencv_core.cvCopy(arr, tempImage);
+ return new WPIColorImage(tempImage);
+ }
+
+ public static WPIBinaryImage makeWPIBinaryImage(IplImage arr)
+ {
+ IplImage tempImage = IplImage.create(arr.cvSize(), arr.depth(), 1);
+ opencv_core.cvCopy(arr, tempImage);
+ return new WPIBinaryImage(tempImage);
+ }
+
+ public static IplImage getIplImage(WPIImage image)
+ {
+ return image.image;
+ }
+
+ private static CvMemStorage storage;
+// private static ArrayList<CvSeq> thingsToDispose;
+
+ public static void init()
+ {
+ storage = CvMemStorage.create();
+ }
+
+ public static WPIContour[] findConvexContours(WPIBinaryImage image)
+ {
+ image.validateDisposed();
+
+ IplImage tempImage = IplImage.create(image.image.cvSize(), image.image.depth(), 1);
+
+ opencv_core.cvCopy(image.image, tempImage);
+
+ CvSeq contours = new CvSeq();
+ opencv_imgproc.cvFindContours(tempImage, storage, contours, 256, opencv_imgproc.CV_RETR_LIST, opencv_imgproc.CV_CHAIN_APPROX_TC89_KCOS);
+ ArrayList<WPIContour> results = new ArrayList<WPIContour>();
+ while (!WPIDisposable.isNull(contours)) {
+ CvSeq convexContour = opencv_imgproc.cvConvexHull2(contours, storage, opencv_imgproc.CV_CLOCKWISE, 1);
+ WPIContour contour = new WPIContour(opencv_core.cvCloneSeq(convexContour, storage));
+ results.add(contour);
+ contours = contours.h_next();
+ }
+
+ tempImage.release();
+ WPIContour[] array = new WPIContour[results.size()];
+ return results.toArray(array);
+ }
+
+ public static void releaseMemory()
+ {
+ opencv_core.cvClearMemStorage(storage);
+ }
+
+}
