Difference between revisions of "Example Fiducial Square Image"
From BoofCV
Jump to navigationJump to searchm |
m |
||
Line 8: | Line 8: | ||
Example Code: | Example Code: | ||
* [https://github.com/lessthanoptimal/BoofCV/blob/v0. | * [https://github.com/lessthanoptimal/BoofCV/blob/v0.19/examples/src/boofcv/examples/fiducial/ExampleFiducialImage.java ExampleFiducialImage.java] | ||
Concepts: | Concepts: | ||
Line 34: | Line 34: | ||
public static void main(String[] args) { | public static void main(String[] args) { | ||
String | String imagePath = "../data/applet/fiducial/image/examples/"; | ||
String patternPath = "../data/applet/fiducial/image/patterns/"; | |||
String imageName = " | String imageName = "image00.jpg"; | ||
// String imageName = " | // String imageName = "image01.jpg"; | ||
// String imageName = " | // String imageName = "image02.jpg"; | ||
// load the lens distortion parameters and the input image | // load the lens distortion parameters and the input image | ||
IntrinsicParameters param = UtilIO.loadXML( | IntrinsicParameters param = UtilIO.loadXML(imagePath + "intrinsic.xml"); | ||
BufferedImage input = | BufferedImage input = loadImage(imagePath + imageName); | ||
ImageFloat32 original = ConvertBufferedImage.convertFrom(input, true, ImageType.single(ImageFloat32.class)); | ImageFloat32 original = ConvertBufferedImage.convertFrom(input, true, ImageType.single(ImageFloat32.class)); | ||
// Detect the fiducial | // Detect the fiducial | ||
SquareImage_to_FiducialDetector<ImageFloat32> detector = FactoryFiducial. | SquareImage_to_FiducialDetector<ImageFloat32> detector = FactoryFiducial. | ||
squareImageRobust(new ConfigFiducialImage( | squareImageRobust(new ConfigFiducialImage(), 6, ImageFloat32.class); | ||
// squareImageFast(new ConfigFiducialImage(0.1), 100, ImageFloat32.class); | // squareImageFast(new ConfigFiducialImage(0.1), 100, ImageFloat32.class); | ||
// give it a description of all the targets | // give it a description of all the targets | ||
ImageFloat32 dog | double width = 4; // 4 cm | ||
detector. | detector.addPatternImage(loadImage(patternPath + "ke.png", ImageFloat32.class), 100, width); | ||
detector.addPatternImage(loadImage(patternPath + "dog.png", ImageFloat32.class), 100, width); | |||
ImageFloat32 | detector.addPatternImage(loadImage(patternPath + "yu.png", ImageFloat32.class), 100, width); | ||
detector. | detector.addPatternImage(loadImage(patternPath + "yu_inverted.png", ImageFloat32.class), 100, width); | ||
detector.addPatternImage(loadImage(patternPath + "pentarose.png", ImageFloat32.class), 100, width); | |||
detector.addPatternImage(loadImage(patternPath + "text_boofcv.png", ImageFloat32.class), 100, width); | |||
detector.addPatternImage(loadImage(patternPath + "leaf01.png", ImageFloat32.class), 100, width); | |||
detector.addPatternImage(loadImage(patternPath + "leaf02.png", ImageFloat32.class), 100, width); | |||
detector.addPatternImage(loadImage(patternPath + "hand01.png", ImageFloat32.class), 100, width); | |||
detector.addPatternImage(loadImage(patternPath + "chicken.png", ImageFloat32.class), 100, width); | |||
detector.addPatternImage(loadImage(patternPath + "h2o.png", ImageFloat32.class), 100, width); | |||
detector.addPatternImage(loadImage(patternPath + "yinyang.png", ImageFloat32.class), 100, width); | |||
detector.setIntrinsic(param); | detector.setIntrinsic(param); | ||
Line 66: | Line 75: | ||
for (int i = 0; i < detector.totalFound(); i++) { | for (int i = 0; i < detector.totalFound(); i++) { | ||
System.out.println("Target ID = "+detector.getId(i)); | System.out.println("Target ID = "+detector.getId(i)); | ||
detector. | detector.getFiducialToCamera(i, targetToSensor); | ||
System.out.println("Location:"); | System.out.println("Location:"); | ||
System.out.println(targetToSensor); | System.out.println(targetToSensor); | ||
VisualizeFiducial.drawCube(targetToSensor,param, | VisualizeFiducial.drawNumbers(targetToSensor,param,detector.getId(i), g2); | ||
VisualizeFiducial.drawCube(targetToSensor,param,detector.getWidth(i), 3, g2); | |||
} | } | ||
ShowImages.showWindow(input,"Fiducials"); | ShowImages.showWindow(input,"Fiducials",true); | ||
} | } | ||
} | } | ||
</syntaxhighlight> | </syntaxhighlight> |
Revision as of 05:07, 16 September 2015
Demonstration how to detect square image fiducials. After the fiducial detector has been created a description of each image it detects is passed in. These images are converted into binary images and resized if needed. A large number of unique fiducials can be detected with a linear growth in computational time.
Example Code:
Concepts:
- Fiducials
- Pose estimation
Relevant Examples/Tutorials:
Relevant Applets:
Example Code
/**
* Detects square binary fiducials inside an image, writes out there pose, and visualizes a virtual flat cube
* above them in the input image.
*
* @author Peter Abeles
*/
public class ExampleFiducialImage {
public static void main(String[] args) {
String imagePath = "../data/applet/fiducial/image/examples/";
String patternPath = "../data/applet/fiducial/image/patterns/";
String imageName = "image00.jpg";
// String imageName = "image01.jpg";
// String imageName = "image02.jpg";
// load the lens distortion parameters and the input image
IntrinsicParameters param = UtilIO.loadXML(imagePath + "intrinsic.xml");
BufferedImage input = loadImage(imagePath + imageName);
ImageFloat32 original = ConvertBufferedImage.convertFrom(input, true, ImageType.single(ImageFloat32.class));
// Detect the fiducial
SquareImage_to_FiducialDetector<ImageFloat32> detector = FactoryFiducial.
squareImageRobust(new ConfigFiducialImage(), 6, ImageFloat32.class);
// squareImageFast(new ConfigFiducialImage(0.1), 100, ImageFloat32.class);
// give it a description of all the targets
double width = 4; // 4 cm
detector.addPatternImage(loadImage(patternPath + "ke.png", ImageFloat32.class), 100, width);
detector.addPatternImage(loadImage(patternPath + "dog.png", ImageFloat32.class), 100, width);
detector.addPatternImage(loadImage(patternPath + "yu.png", ImageFloat32.class), 100, width);
detector.addPatternImage(loadImage(patternPath + "yu_inverted.png", ImageFloat32.class), 100, width);
detector.addPatternImage(loadImage(patternPath + "pentarose.png", ImageFloat32.class), 100, width);
detector.addPatternImage(loadImage(patternPath + "text_boofcv.png", ImageFloat32.class), 100, width);
detector.addPatternImage(loadImage(patternPath + "leaf01.png", ImageFloat32.class), 100, width);
detector.addPatternImage(loadImage(patternPath + "leaf02.png", ImageFloat32.class), 100, width);
detector.addPatternImage(loadImage(patternPath + "hand01.png", ImageFloat32.class), 100, width);
detector.addPatternImage(loadImage(patternPath + "chicken.png", ImageFloat32.class), 100, width);
detector.addPatternImage(loadImage(patternPath + "h2o.png", ImageFloat32.class), 100, width);
detector.addPatternImage(loadImage(patternPath + "yinyang.png", ImageFloat32.class), 100, width);
detector.setIntrinsic(param);
detector.detect(original);
// print the results
Graphics2D g2 = input.createGraphics();
Se3_F64 targetToSensor = new Se3_F64();
for (int i = 0; i < detector.totalFound(); i++) {
System.out.println("Target ID = "+detector.getId(i));
detector.getFiducialToCamera(i, targetToSensor);
System.out.println("Location:");
System.out.println(targetToSensor);
VisualizeFiducial.drawNumbers(targetToSensor,param,detector.getId(i), g2);
VisualizeFiducial.drawCube(targetToSensor,param,detector.getWidth(i), 3, g2);
}
ShowImages.showWindow(input,"Fiducials",true);
}
}