Difference between revisions of "Example Calibrate Planar Mono"

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This example demonstrates how to use a high level calibration class that automatically detects calibration targets as viewed from a single (monocular) camera in a set of images.  After processing the images the intrinsic camera parameters and lens distortion are saved to an XML file.  Both the square grid and chessboard patterns are supported by this example.  For a full description of the calibration process and instruction on how to do it yourself see the tutorial linked to below.
This example demonstrates how to use a high level calibration class that automatically detects calibration targets as viewed from a single (monocular) camera in a set of images.  After processing the images the intrinsic camera parameters and lens distortion are saved to an XML file.  Both the square grid and chessboard patterns are supported by this example.  For a full description of the calibration process and instruction on how to do it yourself see the tutorial linked to below.


Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.19/examples/src/boofcv/examples/calibration/ExampleCalibrateMonocularPlanar.java ExampleCalibrateMonocularPlanar.java]
Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v1.1.0/examples/src/main/java/boofcv/examples/calibration/ExampleCalibrateMonocular.java ExampleCalibrateMonocular.java]


Calibration Tutorial: [[Tutorial_Camera_Calibration|Wikipage]]
Calibration Tutorial: [[Tutorial_Camera_Calibration|Wikipage]]
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* Lens distortion
* Lens distortion
* Intrinsic parameters
* Intrinsic parameters
Relevant Applets:
* [[Applet_Calibrate_Planar_Mono| Monocular Calibration]]
* [[Applet_Remove_Lens_Distortion| Removing Lens Distortion]]


Related Examples:
Related Examples:
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<syntaxhighlight lang="java">
<syntaxhighlight lang="java">
/**
/**
  * Example of how to calibrate a single (monocular) camera using a high level interface that processes images of planar
  * Example of how to calibrate a single (monocular) camera using a high level interface. Depending on the calibration
  * calibration targets.  The entire calibration target must be observable in the image and for best results images
  * target detector and target type, the entire target might need to be visible in the image. All camera images
  * should be in focus and not blurred. For a lower level example of camera calibration which processes a set of
  * should be in focus and that target evenly spread through out the images. In particular the edges of the image
  * observed calibration points see {@link ExampleCalibrateMonocularPlanar}.
  * should be covered.
  *
  *
  * After processing both intrinsic camera parameters and lens distortion are estimated. Square grid and chessboard
  * After processing both intrinsic camera parameters and lens distortion are estimated. Square grid and chessboard
  * targets are demonstrated by this example. See calibration tutorial for a discussion of different target types
  * targets are demonstrated by this example. See calibration tutorial for a discussion of different target types
  * and how to collect good calibration images.
  * and how to collect good calibration images.
  *
  *
  * All the image processing and calibration is taken care of inside of {@link CalibrateMonoPlanar}. The code below
  * All the image processing and calibration is taken care of inside of {@link CalibrateMonoPlanar}. The code below
  * loads calibration images as inputs, calibrates, and saves results to an XML file. See in code comments for tuning
  * loads calibration images as inputs, calibrates, and saves results to an XML file. See in code comments for tuning
  * and implementation issues.
  * and implementation issues.
  *
  *
* @author Peter Abeles
  * @see CalibrateMonoPlanar
  * @see CalibrateMonoPlanar
*
* @author Peter Abeles
  */
  */
public class ExampleCalibrateMonocularPlanar {
public class ExampleCalibrateMonocular {
public static void main( String[] args ) {
DetectSingleFiducialCalibration detector;
List<String> images;


// Detects the target and calibration point inside the target
// Regular Circle Example
PlanarCalibrationDetector detector;
// detector = FactoryFiducialCalibration.circleRegularGrid(null, new ConfigGridDimen(/*numRows*/ 8, /*numCols*/ 10, 1.5, 2.5));
// images = UtilIO.listByPrefix(UtilIO.pathExample("calibration/mono/Sony_DSC-HX5V_CircleRegular"),"image", null);


// List of calibration images
// Hexagonal Circle Example
List<String> images;
// detector = FactoryFiducialCalibration.circleHexagonalGrid(null, new ConfigGridDimen(/*numRows*/ 24, /*numCols*/ 28, 1, 1.2));
// images = UtilIO.listByPrefix(UtilIO.pathExample("calibration/mono/Sony_DSC-HX5V_CircleHexagonal"),"image", null);


/**
// Square Grid example
* Images from Zhang's website.  Square grid pattern.
// detector = FactoryFiducialCalibration.squareGrid(null, new ConfigGridDimen(/*numRows*/ 4, /*numCols*/ 3, 30, 30));
*/
// images = UtilIO.listByPrefix(UtilIO.pathExample("calibration/stereo/Bumblebee2_Square"),"left", null);
private void setupZhang99() {
// Creates a detector and specifies its physical characteristics
detector = FactoryPlanarCalibrationTarget.detectorSquareGrid(new ConfigSquareGrid(15, 15, 0.5, 7.0 / 18.0));


// load image list
// ECoCheck Example
String directory = "../data/evaluation/calibration/mono/PULNiX_CCD_6mm_Zhang";
// detector = new MultiToSingleFiducialCalibration(FactoryFiducialCalibration.
images = BoofMiscOps.directoryList(directory,"CalibIm");
// ecocheck(null, ConfigECoCheckMarkers.
}
// singleShape(/*numRows*/ 9, /*numCols*/ 7, /*num markers*/ 1, /* square size */ 30)));
// images = UtilIO.listByPrefix(UtilIO.pathExample("calibration/stereo/Zed_ecocheck"), "left", null);


/**
// Chessboard Example
* Images collected from a Bumblee Bee stereo camera.  Large amounts of radial distortion. Chessboard pattern.
detector = FactoryFiducialCalibration.chessboardX(null,
*/
new ConfigGridDimen(/*numRows*/ 7,/*numCols*/ 5,/*shapeSize*/ 30));
private void setupBumbleBee() {
images = UtilIO.listByPrefix(UtilIO.pathExample("calibration/stereo/Bumblebee2_Chess"), "left", null);
// Creates a detector and specifies its physical characteristics
detector = FactoryPlanarCalibrationTarget.detectorChessboard(new ConfigChessboard(5,7, 30));


// load image list
// Declare and setup the calibration algorithm
String directory = "../data/evaluation/calibration/stereo/Bumblebee2_Chess";
var calibrator = new CalibrateMonoPlanar();
images = BoofMiscOps.directoryList(directory,"left");
}


/**
// tell it type type of target and which intrinsic parameters to estimate
* Process calibration images, compute intrinsic parameters, save to a file
calibrator.configurePinhole(
*/
/*assumeZeroSkew*/ true,
public void process() {
/*numRadialParam*/ 2,
/*includeTangential*/ false);


// Declare and setup the calibration algorithm
var usedImages = new ArrayList<String>();
CalibrateMonoPlanar calibrationAlg = new CalibrateMonoPlanar(detector);
for (String n : images) {
BufferedImage input = UtilImageIO.loadImageNotNull(n);
GrayF32 image = ConvertBufferedImage.convertFrom(input, (GrayF32)null);
if (detector.process(image)) {
// Need to tell it the image shape and the layout once
if (usedImages.isEmpty())
calibrator.initialize(image.getWidth(), image.getHeight(), List.of(detector.getLayout()));


// tell it type type of target and which parameters to estimate
calibrator.addImage(detector.getDetectedPoints().copy());
calibrationAlg.configure( true, 2, false);
usedImages.add(n);
 
} else {
for( String n : images ) {
System.err.println("Failed to detect target in " + n);
BufferedImage input = UtilImageIO.loadImage(n);
if( n != null ) {
ImageFloat32 image = ConvertBufferedImage.convertFrom(input,(ImageFloat32)null);
if( !calibrationAlg.addImage(image) )
System.err.println("Failed to detect target in "+n);
}
}
}
}
// process and compute intrinsic parameters
// process and compute intrinsic parameters
IntrinsicParameters intrinsic = calibrationAlg.process();
CameraPinholeBrown intrinsic = calibrator.process();


// save results to a file and print out
// save results to a file and print out
UtilIO.saveXML(intrinsic, "intrinsic.xml");
CalibrationIO.save(intrinsic, "intrinsic.yaml");


calibrationAlg.printStatistics();
System.out.println(calibrator.computeQualityText(usedImages));
System.out.println();
System.out.println();
System.out.println("--- Intrinsic Parameters ---");
System.out.println("--- Intrinsic Parameters ---");
System.out.println();
System.out.println();
intrinsic.print();
intrinsic.print();
}
public static void main( String args[] ) {
ExampleCalibrateMonocularPlanar alg = new ExampleCalibrateMonocularPlanar();
// which target should it process
// alg.setupZhang99();
alg.setupBumbleBee();
// compute and save results
alg.process();
}
}
}
}
</syntaxhighlight>
</syntaxhighlight>

Latest revision as of 18:05, 9 September 2023

This example demonstrates how to use a high level calibration class that automatically detects calibration targets as viewed from a single (monocular) camera in a set of images. After processing the images the intrinsic camera parameters and lens distortion are saved to an XML file. Both the square grid and chessboard patterns are supported by this example. For a full description of the calibration process and instruction on how to do it yourself see the tutorial linked to below.

Example File: ExampleCalibrateMonocular.java

Calibration Tutorial: Wikipage

Concepts:

  • Camera calibration
  • Lens distortion
  • Intrinsic parameters

Related Examples:

Example Code

/**
 * Example of how to calibrate a single (monocular) camera using a high level interface. Depending on the calibration
 * target detector and target type, the entire target might need to be visible in the image. All camera images
 * should be in focus and that target evenly spread through out the images. In particular the edges of the image
 * should be covered.
 *
 * After processing both intrinsic camera parameters and lens distortion are estimated. Square grid and chessboard
 * targets are demonstrated by this example. See calibration tutorial for a discussion of different target types
 * and how to collect good calibration images.
 *
 * All the image processing and calibration is taken care of inside of {@link CalibrateMonoPlanar}. The code below
 * loads calibration images as inputs, calibrates, and saves results to an XML file. See in code comments for tuning
 * and implementation issues.
 *
 * @author Peter Abeles
 * @see CalibrateMonoPlanar
 */
public class ExampleCalibrateMonocular {
	public static void main( String[] args ) {
		DetectSingleFiducialCalibration detector;
		List<String> images;

		// Regular Circle Example
//		detector = FactoryFiducialCalibration.circleRegularGrid(null, new ConfigGridDimen(/*numRows*/ 8, /*numCols*/ 10, 1.5, 2.5));
//		images = UtilIO.listByPrefix(UtilIO.pathExample("calibration/mono/Sony_DSC-HX5V_CircleRegular"),"image", null);

		// Hexagonal Circle Example
//		detector = FactoryFiducialCalibration.circleHexagonalGrid(null, new ConfigGridDimen(/*numRows*/ 24, /*numCols*/ 28, 1, 1.2));
//		images = UtilIO.listByPrefix(UtilIO.pathExample("calibration/mono/Sony_DSC-HX5V_CircleHexagonal"),"image", null);

		// Square Grid example
//		detector = FactoryFiducialCalibration.squareGrid(null, new ConfigGridDimen(/*numRows*/ 4, /*numCols*/ 3, 30, 30));
//		images = UtilIO.listByPrefix(UtilIO.pathExample("calibration/stereo/Bumblebee2_Square"),"left", null);

		// ECoCheck Example
//		detector = new MultiToSingleFiducialCalibration(FactoryFiducialCalibration.
//				ecocheck(null, ConfigECoCheckMarkers.
//						singleShape(/*numRows*/ 9, /*numCols*/ 7, /*num markers*/ 1, /* square size */ 30)));
//		images = UtilIO.listByPrefix(UtilIO.pathExample("calibration/stereo/Zed_ecocheck"), "left", null);

		// Chessboard Example
		detector = FactoryFiducialCalibration.chessboardX(null,
				new ConfigGridDimen(/*numRows*/ 7,/*numCols*/ 5,/*shapeSize*/ 30));
		images = UtilIO.listByPrefix(UtilIO.pathExample("calibration/stereo/Bumblebee2_Chess"), "left", null);

		// Declare and setup the calibration algorithm
		var calibrator = new CalibrateMonoPlanar();

		// tell it type type of target and which intrinsic parameters to estimate
		calibrator.configurePinhole(
				/*assumeZeroSkew*/ true,
				/*numRadialParam*/ 2,
				/*includeTangential*/ false);

		var usedImages = new ArrayList<String>();
		for (String n : images) {
			BufferedImage input = UtilImageIO.loadImageNotNull(n);
			GrayF32 image = ConvertBufferedImage.convertFrom(input, (GrayF32)null);
			if (detector.process(image)) {
				// Need to tell it the image shape and the layout once
				if (usedImages.isEmpty())
					calibrator.initialize(image.getWidth(), image.getHeight(), List.of(detector.getLayout()));

				calibrator.addImage(detector.getDetectedPoints().copy());
				usedImages.add(n);
			} else {
				System.err.println("Failed to detect target in " + n);
			}
		}
		// process and compute intrinsic parameters
		CameraPinholeBrown intrinsic = calibrator.process();

		// save results to a file and print out
		CalibrationIO.save(intrinsic, "intrinsic.yaml");

		System.out.println(calibrator.computeQualityText(usedImages));
		System.out.println();
		System.out.println("--- Intrinsic Parameters ---");
		System.out.println();
		intrinsic.print();
	}
}