项目：2014CataBot
文件：ImagingUtils.java
/**
* Computes a score (0-100) comparing the aspect ratio to the ideal aspect
* ratio for the target. This method uses the equivalent rectangle sides to
* determine aspect ratio as it performs better as the target gets skewed by
* moving to the left or right. The equivalent rectangle is the rectangle
* with sides x and y where particle area= x*y and particle perimeter= 2x+2y
*
* @param image The image containing the particle to score,needed to
* performa additional measurements
* @param report The Particle Analysis Report for the particle,used for the
* width,height,and particle number
* @param outer Indicates whether the particle aspect ratio should be
* compared to the ratio for the inner target or the outer
* @return The aspect ratio score (0-100)
*/
public static double scoreAspectRatio(BinaryImage image,ParticleAnalysisReport report,int particleNumber,boolean outer) throws NIVisionException {
double rectLong,rectShort,aspectRatio,idealAspectRatio;
rectLong = NIVision.MeasureParticle(image.image,particleNumber,false,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_LONG_SIDE);
rectShort = NIVision.MeasureParticle(image.image,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_SHORT_SIDE);
//idealAspectRatio = outer ? (62/29) : (62/20); //Dimensions of goal opening + 4 inches on all 4 sides for reflective tape
idealAspectRatio = outer ? (43 / 32) : (39 / 28);
//Divide width by height to measure aspect ratio
aspectRatio = report.boundingRectWidth / (double) report.boundingRectHeight;
/*if(report.boundingRectWidth > report.boundingRectHeight){
//particle is wider than it is tall,divide long by short
aspectRatio = 100*(1-Math.abs((1-((rectLong/rectShort)/idealAspectRatio))));
} else {
//particle is taller than it is wide,divide short by long
aspectRatio = 100*(1-Math.abs((1-((rectShort/rectLong)/idealAspectRatio))));
}*/
return aspectRatio;
//return (Math.max(0,Math.min(aspectRatio,100.0))); //force to be in range 0-100
}
项目：2014CataBot
文件：ImagingUtils.java
/**
* Computes a score based on the match between a template profile and the
* particle profile in the X direction. This method uses the the column
* averages and the profile defined at the top of the sample to look for the
* solid vertical edges with a hollow center.
*
* @param image The image to use,should be the image before the convex hull
* is performed
* @param report The Particle Analysis Report for the particle
*
* @return The X Edge score (0-100)
*/
public static double scoreXEdge(BinaryImage image,ParticleAnalysisReport report) throws NIVisionException {
double total = 0;
Linearaverages averages;
NIVision.Rect rect = new NIVision.Rect(report.boundingRectTop,report.boundingRectLeft,report.boundingRectHeight,report.boundingRectWidth);
averages = NIVision.getLinearaverages(image.image,Linearaverages.LinearaveragesMode.IMAQ_COLUMN_AVERAGES,rect);
float columnAverages[] = averages.getColumnAverages();
for (int i = 0; i < (columnAverages.length); i++) {
if (xMin[(i * (XMINSIZE - 1) / columnAverages.length)] < columnAverages[i]
&& columnAverages[i] < xMax[i * (XMAXSIZE - 1) / columnAverages.length]) {
totaL++;
}
}
total = 100 * total / (columnAverages.length);
return total;
}
项目：2014CataBot
文件：ImagingUtils.java
/**
* Computes a score based on the match between a template profile and the
* particle profile in the Y direction. This method uses the the row
* averages and the profile defined at the top of the sample to look for the
* solid horizontal edges with a hollow center
*
* @param image The image to use,should be the image before the convex hull
* is performed
* @param report The Particle Analysis Report for the particle
*
* @return The Y Edge score (0-100)
*
*/
public static double scoreYEdge(BinaryImage image,Linearaverages.LinearaveragesMode.IMAQ_ROW_AVERAGES,rect);
float rowAverages[] = averages.getRowAverages();
for (int i = 0; i < (rowAverages.length); i++) {
if (yMin[(i * (YMINSIZE - 1) / rowAverages.length)] < rowAverages[i]
&& rowAverages[i] < yMax[i * (YMAXSIZE - 1) / rowAverages.length]) {
totaL++;
}
}
total = 100 * total / (rowAverages.length);
return total;
}
项目：Aerial-Assist
文件：AxisCameraM1101.java
/**
* Computes a score (0-100) comparing the aspect ratio to the ideal aspect
* ratio for the target. This method uses the equivalent rectangle sides to
* determine aspect ratio as it performs better as the target gets skewed by
* moving to the left or right. The equivalent rectangle is the rectangle
* with sides x and y where particle area,xy and particle perimeter,2x+2y
*
* @param image The image containing the particle to score,needed to
* perform additional measurements
* @param report The Particle Analysis Report for the particle,and particle number
* @param outer Indicates whether the particle aspect ratio should be
* compared to the ratio for the inner target or the outer
* @return The aspect ratio score (0-100)
*/
private double scoreAspectRatio(BinaryImage image,ParticleAnalysisReport
report,boolean vertical) throws
NIVisionException {
double rectLong,MeasurementType.IMAQ_MT_EQUIVALENT_RECT_LONG_SIDE);
rectShort = NIVision.MeasureParticle(image.image,MeasurementType.IMAQ_MT_EQUIVALENT_RECT_SHORT_SIDE);
idealAspectRatio = vertical ? (4.0 / 32) : (23.5 / 4);
if (report.boundingRectWidth > report.boundingRectHeight) {
aspectRatio = ratioToscore((rectLong / rectShort)/idealAspectRatio);
} else {
aspectRatio = ratioToscore((rectShort / rectLong)/idealAspectRatio);
}
return aspectRatio;
}
项目：2014RobotCode
文件：CameraDetection.java
public double scoreAspectRatio(BinaryImage image,boolean vertical) throws NIVisionException
{
double rectLong,idealAspectRatio;
rectLong = NIVision.MeasureParticle(image.image,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_LONG_SIDE);
rectShort = NIVision.MeasureParticle(image.image,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_SHORT_SIDE);
idealAspectRatio = vertical ? (4.0/32) : (23.5/4); //Vertical reflector 4" wide x 32" tall,horizontal 23.5" wide x 4" tall
//Divide width by height to measure aspect ratio
if(report.boundingRectWidth > report.boundingRectHeight){
//particle is wider than it is tall,divide long by short
aspectRatio = ratioToscore((rectLong/rectShort)/idealAspectRatio);
} else {
//particle is taller than it is wide,divide short by long
aspectRatio = ratioToscore((rectShort/rectLong)/idealAspectRatio);
}
return aspectRatio;
}
/**
* Computes a score (0-100) comparing the aspect ratio to the ideal aspect
* ratio for the target. This method uses the equivalent rectangle sides to
* determine aspect ratio as it performs better as the target gets skewed by
* moving to the left or right. The equivalent rectangle is the rectangle
* with sides x and y where particle area= x*y and particle perimeter= 2x+2y
*
* @param image The image containing the particle to score,and particle number
* @param outer Indicates whether the particle aspect ratio should be
* compared to the ratio for the inner target or the outer
* @return The aspect ratio score (0-100)
*/
private static double scoreAspectRatio(BinaryImage image,boolean vertical) throws NIVisionException {
double rectLong,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_SHORT_SIDE);
idealAspectRatio = vertical ? (4.0 / 32) : (23.5 / 4); //Vertical reflector 4" wide x 32" tall,horizontal 23.5" wide x 4" tall
//Divide width by height to measure aspect ratio
if (report.boundingRectWidth > report.boundingRectHeight) {
//particle is wider than it is tall,divide long by short
aspectRatio = ratioToscore((rectLong / rectShort) / idealAspectRatio);
} else {
//particle is taller than it is wide,divide short by long
aspectRatio = ratioToscore((rectShort / rectLong) / idealAspectRatio);
}
return aspectRatio;
}
项目：FRCTesting
文件：ImageUtils.java
/**
* Computes a score (0-100) comparing the aspect ratio to the ideal aspect
* ratio for the target. This method uses the equivalent rectangle sides to
* determine aspect ratio as it performs better as the target gets skewed by
* moving to the left or right. The equivalent rectangle is the rectangle
* with sides x and y where particle area= x*y and particle perimeter= 2x+2y
*
* @param image The image containing the particle to score,100.0))); //force to be in range 0-100
}
项目：FRCTesting
文件：ImageUtils.java
/**
* Computes a score based on the match between a template profile and the
* particle profile in the X direction. This method uses the the column
* averages and the profile defined at the top of the sample to look for the
* solid vertical edges with a hollow center.
*
* @param image The image to use,rect);
float columnAverages[] = averages.getColumnAverages();
for (int i = 0; i < (columnAverages.length); i++) {
if (xMin[(i * (XMINSIZE - 1) / columnAverages.length)] < columnAverages[i]
&& columnAverages[i] < xMax[i * (XMAXSIZE - 1) / columnAverages.length]) {
totaL++;
}
}
total = 100 * total / (columnAverages.length);
return total;
}
项目：FRCTesting
文件：ImageUtils.java
/**
* Computes a score based on the match between a template profile and the
* particle profile in the Y direction. This method uses the the row
* averages and the profile defined at the top of the sample to look for the
* solid horizontal edges with a hollow center
*
* @param image The image to use,rect);
float rowAverages[] = averages.getRowAverages();
for (int i = 0; i < (rowAverages.length); i++) {
if (yMin[(i * (YMINSIZE - 1) / rowAverages.length)] < rowAverages[i]
&& rowAverages[i] < yMax[i * (YMAXSIZE - 1) / rowAverages.length]) {
totaL++;
}
}
total = 100 * total / (rowAverages.length);
return total;
}
项目：2014_software
文件：HotGoalDetector.java
public void getimages(String imageAppend)
{
try
{
ColorImage image = camera.getimage();
if(imageWriteLevel >= 1 && imageWriteLevel <= 3)
{
NIVision.writeFile(image.image,"/ColorImage" + imageAppend + ".jpg");
System.out.println("Saving Color Image");
}
}
catch(Throwable t)
{
t.printstacktrace();
}
}
项目：2014_software
文件：HotGoalDetector.java
public double scoreAspectRatio(BinaryImage image,boolean vertical) throws NIVisionException
{
double rectLong,horizontal 23.5" wide x 4" tall
if (report.boundingRectWidth > report.boundingRectHeight)
{
aspectRatio = ratioToscore((rectLong / rectShort) / idealAspectRatio);
}
else
{
aspectRatio = ratioToscore((rectShort / rectLong) / idealAspectRatio);
}
return aspectRatio;
}
项目：2014_software
文件：HotGoalDetector.java
public double scoreAspectRatioOnRotatedImage(BinaryImage image,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_SHORT_SIDE);
idealAspectRatio = vertical ? (32.0 / 4) : (4/23.5); //Vertical reflector 4" wide x 32" tall,horizontal 23.5" wide x 4" tall
if (report.boundingRectWidth > report.boundingRectHeight)
{
aspectRatio = ratioToscore((rectLong / rectShort) / idealAspectRatio);
}
else
{
aspectRatio = ratioToscore((rectShort / rectLong) / idealAspectRatio);
}
return aspectRatio;
}
项目：FRC623Robot2014
文件：VisionController.java
/**
* Computes a score (0-100) comparing the aspect ratio to the ideal aspect
* ratio for the target. This method uses the equivalent rectangle sides to
* determine aspect ratio as it performs better as the target gets skewed by
* moving to the left or right. The equivalent rectangle is the rectangle
* with sides x and y where particle area= x*y and particle perimeter= 2x+2y
*
* @param image The image containing the particle to score,divide short by long
aspectRatio = ratioToscore((rectShort / rectLong) / idealAspectRatio);
}
return aspectRatio;
}
项目：2013ultimate-ascent
文件：GRTVisionTracker.java
/**
* Computes a score (0-100) comparing the aspect ratio to the ideal aspect ratio for the target. This method uses
* the equivalent rectangle sides to determine aspect ratio as it performs better as the target gets skewed by moving
* to the left or right. The equivalent rectangle is the rectangle with sides x and y where particle area= x*y
* and particle perimeter= 2x+2y
*
* @param image The image containing the particle to score,needed to performa additional measurements
* @param report The Particle Analysis Report for the particle,used for the width,and particle number
* @param outer Indicates whether the particle aspect ratio should be compared to the ratio for the inner target or the outer
* @return The aspect ratio score (0-100)
*/
public double scoreAspectRatio(BinaryImage image,boolean outer) throws NIVisionException
{
double rectLong,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_SHORT_SIDE);
//idealAspectRatio = outer ? (62/29) : (62/20); //Dimensions of goal opening + 4 inches on all 4 sides for reflective tape
//yonatan - change back
idealAspectRatio = outer ? (62/29) : (62/40); //Dimensions of goal opening + 4 inches on all 4 sides for reflective tape
//Divide width by height to measure aspect ratio
if(report.boundingRectWidth > report.boundingRectHeight){
//particle is wider than it is tall,divide long by short
aspectRatio = 100*(1-Math.abs((1-((rectLong/rectShort)/idealAspectRatio))));
} else {
//particle is taller than it is wide,divide short by long
aspectRatio = 100*(1-Math.abs((1-((rectShort/rectLong)/idealAspectRatio))));
}
return (Math.max(0,100.0))); //force to be in range 0-100
}
项目：2013ultimate-ascent
文件：GRTVisionTracker.java
/**
* Computes a score based on the match between a template profile and the particle profile in the X direction. This method uses the
* the column averages and the profile defined at the top of the sample to look for the solid vertical edges with
* a hollow center.
*
* @param image The image to use,should be the image before the convex hull is performed
* @param report The Particle Analysis Report for the particle
*
* @return The X Edge score (0-100)
*/
public double scoreXEdge(BinaryImage image,ParticleAnalysisReport report) throws NIVisionException
{
double total = 0;
Linearaverages averages;
NIVision.Rect rect = new NIVision.Rect(report.boundingRectTop,rect);
float columnAverages[] = averages.getColumnAverages();
for(int i=0; i < (columnAverages.length); i++){
if(xMin[(i*(XMINSIZE-1)/columnAverages.length)] < columnAverages[i]
&& columnAverages[i] < xMax[i*(XMAXSIZE-1)/columnAverages.length]){
totaL++;
}
}
total = 100*total/(columnAverages.length);
return total;
}
项目：2013ultimate-ascent
文件：GRTVisionTracker.java
/**
* Computes a score based on the match between a template profile and the particle profile in the Y direction. This method uses the
* the row averages and the profile defined at the top of the sample to look for the solid horizontal edges with
* a hollow center
*
* @param image The image to use,should be the image before the convex hull is performed
* @param report The Particle Analysis Report for the particle
*
* @return The Y Edge score (0-100)
*
*/
public double scoreYEdge(BinaryImage image,rect);
float rowAverages[] = averages.getRowAverages();
for(int i=0; i < (rowAverages.length); i++){
if(yMin[(i*(YMINSIZE-1)/rowAverages.length)] < rowAverages[i]
&& rowAverages[i] < yMax[i*(YMAXSIZE-1)/rowAverages.length]){
totaL++;
}
}
total = 100*total/(rowAverages.length);
return total;
}
项目：grtframeworkv7
文件：GRTVisionTracker.java
/**
* Computes a score (0-100) comparing the aspect ratio to the ideal aspect ratio for the target. This method uses
* the equivalent rectangle sides to determine aspect ratio as it performs better as the target gets skewed by moving
* to the left or right. The equivalent rectangle is the rectangle with sides x and y where particle area= x*y
* and particle perimeter= 2x+2y
*
* @param image The image containing the particle to score,100.0))); //force to be in range 0-100
}
项目：grtframeworkv7
文件：GRTVisionTracker.java
/**
* Computes a score based on the match between a template profile and the particle profile in the X direction. This method uses the
* the column averages and the profile defined at the top of the sample to look for the solid vertical edges with
* a hollow center.
*
* @param image The image to use,rect);
float columnAverages[] = averages.getColumnAverages();
for(int i=0; i < (columnAverages.length); i++){
if(xMin[(i*(XMINSIZE-1)/columnAverages.length)] < columnAverages[i]
&& columnAverages[i] < xMax[i*(XMAXSIZE-1)/columnAverages.length]){
totaL++;
}
}
total = 100*total/(columnAverages.length);
return total;
}
项目：grtframeworkv7
文件：GRTVisionTracker.java
/**
* Computes a score based on the match between a template profile and the particle profile in the Y direction. This method uses the
* the row averages and the profile defined at the top of the sample to look for the solid horizontal edges with
* a hollow center
*
* @param image The image to use,rect);
float rowAverages[] = averages.getRowAverages();
for(int i=0; i < (rowAverages.length); i++){
if(yMin[(i*(YMINSIZE-1)/rowAverages.length)] < rowAverages[i]
&& rowAverages[i] < yMax[i*(YMAXSIZE-1)/rowAverages.length]){
totaL++;
}
}
total = 100*total/(rowAverages.length);
return total;
}
项目：Team_1482_2013
文件：vision.java
/**
* Computes a score (0-100) comparing the aspect ratio to the ideal aspect ratio for the target. This method uses
* the equivalent rectangle sides to determine aspect ratio as it performs better as the target gets skewed by moving
* to the left or right. The equivalent rectangle is the rectangle with sides x and y where particle area= x*y
* and particle perimeter= 2x+2y
*
* @param image The image containing the particle to score,needed to perform additional measurements
* @param report The Particle Analysis Report for the particle,and particle number
* @param outer Indicates whether the particle aspect ratio should be compared to the ratio for the inner target or the outer
* @return The aspect ratio score (0-100)
*/
public double scoreAspectRatio(BinaryImage image,divide short by long
aspectRatio = ratioToscore((rectShort/rectLong)/idealAspectRatio);
}
return aspectRatio;
}
项目：Aerial-Assist
文件：AxisCameraM1101.java
/**
* Computes the estimated distance to a target using the height 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 outer True if the particle should be treated as an outer target,* false to treat it as a center target.
* @return The estimated distance to the target in inches.
*/
private double computedistance(BinaryImage image,int particleNumber) throws NIVisionException {
double rectLong,height;
int targetHeight;
rectLong = NIVision.MeasureParticle(image.image,MeasurementType.IMAQ_MT_EQUIVALENT_RECT_LONG_SIDE);
height = Math.min(report.boundingRectHeight,rectLong);
targetHeight = 32;
return Y_IMAGE_RES * targetHeight / (height * 12 * 2
* Math.tan(VIEW_ANGLE * Math.PI / (180 * 2)));
}
项目：2014RobotCode
文件：CameraDetection.java
double computedistance (BinaryImage image,int particleNumber) throws NIVisionException {
double rectLong,height;
int targetHeight;
rectLong = NIVision.MeasureParticle(image.image,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_LONG_SIDE);
//using the smaller of the estimated rectangle long side and the bounding rectangle height results in better performance
//on skewed rectangles
height = Math.min(report.boundingRectHeight,rectLong);
targetHeight = 32;
return Y_IMAGE_RES * targetHeight / (height * 12 * 2 * Math.tan(VIEW_ANGLE*Math.PI/(180*2)));
}
项目：2014_software
文件：HotGoalDetector.java
public void init()
{
cc = new CriteriaCollection();
cc.addCriteria(NIVision.MeasurementType.IMAQ_MT_AREA,AREA_MINIMUM,65535,false);
ledState = Relay.Value.kOff;
}
项目：2014_software
文件：HotGoalDetector.java
double computedistance(BinaryImage image,int particleNumber) throws NIVisionException
{
double rectLong,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_LONG_SIDE);
height = Math.min(report.boundingRectHeight,rectLong);
targetHeight = 32;
return Y_IMAGE_RES * targetHeight / (height * 12 * 2 * Math.tan(VIEW_ANGLE * Math.PI / (180 * 2)));
}
项目：2014_software
文件：HotGoalDetector.java
项目：FRC623Robot2014
文件：VisionController.java
private VisionController() {
camera = AxisCamera.getInstance();
cc = new CriteriaCollection(); // create the criteria for the particle filter
cc.addCriteria(NIVision.MeasurementType.IMAQ_MT_AREA,false);
target = new TargetReport();
verticalTargets = new int[MAX_PARTICLES];
horizontalTargets = new int[MAX_PARTICLES];
}
项目：2013ultimate-ascent
文件：GRTVisionTracker.java
public GRTVisionTracker(AxisCamera cam) {
super("Vision Tracker",NUM_DATA);
this.camera = cam;
this.cc = new CriteriaCollection(); // create the criteria for the particle filter
cc.addCriteria(NIVision.MeasurementType.IMAQ_MT_AREA,500,false);
X_IMAGE_RES = camera.getResolution().width;
listeners = new Vector();
}
项目：2013ultimate-ascent
文件：GRTVisionTracker.java
/**
* Computes the estimated distance to a target using the height 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 outer True if the particle should be treated as an outer target,false to treat it as a center target
* @return The estimated distance to the target in Inches.
*/
double computedistance (BinaryImage image,boolean outer) throws NIVisionException {
double rectShort,width,height;
double targetWidth,targetHeight;
rectShort = NIVision.MeasureParticle(image.image,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_SHORT_SIDE);
//using the smaller of the estimated rectangle short side and the bounding rectangle height results in better performance
//on skewed rectangles
//height = Math.min(report.boundingRectHeight,rectShort);
width = report.boundingRectWidth;
height = report.boundingRectHeight;
//targetHeight = outer ? 29 : 21;
//changed by Yonatan Oren//
//need to change this back to 29/21 for for real ultimate ascent//
targetWidth = 16;
targetHeight = 9.75;
////
// System.out.println("rectShort: " + rectShort);
// System.out.println("height: " + height);
// System.out.println("boundingRectHeight: " + report.boundingRectHeight);
//changed by Yonatan Oren//
//return X_IMAGE_RES * targetHeight / (height * 12 * 2 * Math.tan(VIEW_ANGLE*Math.PI/(180*2)));
//return 240.0 * targetWidth / (width * Math.tan(VIEW_ANGLE*Math.PI/(180*2)));
return 360.0 * targetHeight / (height * Math.tan(VIEW_ANGLE*Math.PI/(180*2)));
//4800 / 62 * tan(
}
项目：grtframeworkv7
文件：GRTVisionTracker.java
public GRTVisionTracker(AxisCamera cam) {
super("Vision Tracker",false);
X_IMAGE_RES = camera.getResolution().width;
listeners = new Vector();
}
项目：grtframeworkv7
文件：GRTVisionTracker.java
/**
* Computes the estimated distance to a target using the height 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 outer True if the particle should be treated as an outer target,rectShort);
width = report.boundingRectWidth;
height = report.boundingRectHeight;
//targetHeight = outer ? 29 : 21;
//changed by Yonatan Oren//
//need to change this back to 29/21 for for real ultimate ascent//
targetWidth = 16;
targetHeight = 9.75;
////
// System.out.println("rectShort: " + rectShort);
// System.out.println("height: " + height);
// System.out.println("boundingRectHeight: " + report.boundingRectHeight);
//changed by Yonatan Oren//
//return X_IMAGE_RES * targetHeight / (height * 12 * 2 * Math.tan(VIEW_ANGLE*Math.PI/(180*2)));
//return 240.0 * targetWidth / (width * Math.tan(VIEW_ANGLE*Math.PI/(180*2)));
return 360.0 * targetHeight / (height * Math.tan(VIEW_ANGLE*Math.PI/(180*2)));
//4800 / 62 * tan(
}
public CameraSubsystem() {
// super(kp,ki,kd);
try {
cam = AxisCamera.getInstance();
cam.writeResolution(AxisCamera.ResolutionT.k320x240);
}
catch(Exception e) {
cam = null;
System.out.println("Could not connect to camera.");
}
cc.addCriteria(NIVision.MeasurementType.IMAQ_MT_BOUNDING_RECT_HEIGHT,MIN_HEIGHT,MAX_HEIGHT,true);
cc.addCriteria(NIVision.MeasurementType.IMAQ_MT_BOUNDING_RECT_WIDTH,MIN_WIDTH,MAX_WIDTH,true);
// this.setSetpoint(160);
// this.setAbsolutetolerance(.03);
}
项目：Team_1482_2013
文件：vision.java
/**
* Computes the estimated distance to a target using the height 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 outer True if the particle should be treated as an outer target,false to treat it as a center target
* @return The estimated distance to the target in Inches.
*/
double computedistance (BinaryImage image,rectLong);
targetHeight = 32;
return Y_IMAGE_RES * targetHeight / (height * 12 * 2 * Math.tan(VIEW_ANGLE*Math.PI/(180*2)));
}
项目：Aerial-Assist
文件：AxisCameraM1101.java
public AxisCameraM1101() {
camera = AxisCamera.getInstance();
criteriaCollection = new CriteriaCollection();
criteriaCollection.addCriteria(NIVision.MeasurementType.IMAQ_MT_AREA,true);
}
项目：2014RobotCode
文件：CameraDetection.java
public CameraDetection(){
//camera = AxisCamera.getInstance();
System.out.println("Started Camera.");
cc = new CriteriaCollection(); // create the criteria for the particle filter
cc.addCriteria(NIVision.MeasurementType.IMAQ_MT_AREA,false);
}
public void init() {
camera = AxisCamera.getInstance();
cc = new CriteriaCollection();
cc.addCriteria(NIVision.MeasurementType.IMAQ_MT_AREA,200,65536,false);
}
项目：Team_1482_2013
文件：vision.java
vision() {
camera = AxisCamera.getInstance("10.14.82.12");
cc = new CriteriaCollection(); // create the criteria for the particle filter
cc.addCriteria(NIVision.MeasurementType.IMAQ_MT_AREA,false);
}
项目：Team_1482_2013
文件：vision.java
public void robotinit() {
//camera = AxisCamera.getInstance(); // get an instance of the camera
cc = new CriteriaCollection(); // create the criteria for the particle filter
cc.addCriteria(NIVision.MeasurementType.IMAQ_MT_AREA,false);
}
项目：2014CataBot
文件：ImagingUtils.java
/**
* Computes the estimated distance to a target using the height 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 outer True if the particle should be treated as an outer target,* false to treat it as a center target
* @return The estimated distance to the target in Inches.
*/
public static double computedistance(BinaryImage image,boolean outer) throws NIVisionException {
double rectShort,height;
int targetHeight;
rectShort = NIVision.MeasureParticle(image.image,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_SHORT_SIDE);
//using the smaller of the estimated rectangle short side and the bounding rectangle height results in better performance
//on skewed rectangles
height = Math.min(report.boundingRectHeight,rectShort);
targetHeight = outer ? 29 : 21;
return X_IMAGE_RES * targetHeight / (height * 12 * 2 * Math.tan(VIEW_ANGLE * Math.PI / (180 * 2)));
}
/**
* Computes the estimated distance to a target using the height 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 outer True if the particle should be treated as an outer target,* false to treat it as a center target
* @return The estimated distance to the target in Inches.
*/
private static double computedistance(BinaryImage image,NIVision.MeasurementType.IMAQ_MT_EQUIVALENT_RECT_LONG_SIDE);
//using the smaller of the estimated rectangle long side and the bounding rectangle height results in better performance
//on skewed rectangles
height = Math.min(report.boundingRectHeight,rectLong);
targetHeight = 32;
return Y_IMAGE_RES * targetHeight / (height * 12 * 2 * Math.tan(VIEW_ANGLE * Math.PI / (180 * 2)));
}
项目：FRCTesting
文件：ImageUtils.java
/**
* Computes the estimated distance to a target using the height 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 outer True if the particle should be treated as an outer target,rectShort);
targetHeight = outer ? 29 : 21;
return X_IMAGE_RES * targetHeight / (height * 12 * 2 * Math.tan(VIEW_ANGLE * Math.PI / (180 * 2)));
}
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