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https://github.com/PhotonVision/photonvision
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ColourShape benchmark and moar docs (#11)
* Added benchmark * Rebase * [Server] ColouredShapePipeline Benchmarks and Documentation * [Server] ColouredShapePipeline Benchmarks and Documentation * Added benchmark * Rebase * [Server] ColouredShapePipeline Benchmarks and Documentation * [Server] ColouredShapePipeline Benchmarks and Documentation * [Server] ColouredShapePipeline Benchmarks and Documentation * [CSP] Rebase off master * [CSP] Remove unused variables * [CSP] Make circles Mat private and final
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@@ -31,12 +31,17 @@ import org.photonvision.vision.pipe.CVPipe;
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public class FindCirclesPipe
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extends CVPipe<Pair<Mat, List<Contour>>, List<CVShape>, FindCirclesPipe.FindCirclePipeParams> {
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// Output vector of found circles. Each vector is encoded as 3 or 4 element floating-point vector
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// (x,y,radius) or (x,y,radius,votes) .
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private final Mat circles = new Mat();
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/**
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* Runs the process for the pipe.
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* Runs the process for the pipe. The reason we need a separate pipe for circles is because if we
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* were to use the FindShapes pipe, we would have to assume that any shape more than 10-20+ sides
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* is a circle. Only issue with such approximation is that the user would no longer be able to
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* track shapes with 10-20+ sides. And hence, in order to overcome this edge case, we can use
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* HoughCircles which is more flexible and accurate for finding circles.
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*
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* @param in Input for pipe processing.
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* @param in Input for pipe processing. 8-bit, single-channel, grayscale input image.
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* @return Result of processing.
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*/
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@Override
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@@ -47,27 +52,40 @@ public class FindCirclesPipe
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Imgproc.HoughCircles(
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in.getLeft(),
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circles,
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// Detection method, see #HoughModes. The available methods are #HOUGH_GRADIENT and
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// #HOUGH_GRADIENT_ALT.
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Imgproc.HOUGH_GRADIENT,
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/*Inverse ratio of the accumulator resolution to the image resolution.
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For example, if dp=1 , the accumulator has the same resolution as the input image.
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If dp=2 , the accumulator has half as big width and height. For #HOUGH_GRADIENT_ALT the recommended value is dp=1.5,
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unless some small very circles need to be detected.
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*/
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1.0,
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params.minDist,
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params.maxCannyThresh,
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params.accuracy,
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params.minRadius,
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params.maxRadius);
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// Great, we now found the center point of the circle and it's radius, but we have no idea what
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// contour it corresponds to
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for (int x = 0; x < circles.cols(); x++) {
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// Grab the current circle we are looking at
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double[] c = circles.get(0, x);
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// Find the center points of that circle
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double x_center = c[0];
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double y_center = c[1];
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for (Contour contour : in.getRight()) {
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// Grab the moments of the current contour
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Moments mu = contour.getMoments();
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// Determine if the contour is within the threshold of the detected circle
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if (Math.abs(x_center - (mu.m10 / mu.m00)) <= params.allowableThreshold
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&& Math.abs(y_center - (mu.m01 / mu.m00)) <= params.allowableThreshold) {
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// If it is, then add it to the output array
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output.add(new CVShape(contour, ContourShape.Circle));
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}
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}
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}
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return output;
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}
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@@ -79,6 +97,17 @@ public class FindCirclesPipe
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private final int maxCannyThresh;
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private final int accuracy;
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/*
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* @params minDist - Minimum distance between the centers of the detected circles.
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* If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed.
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*
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* @param maxCannyThresh -First method-specific parameter. In case of #HOUGH_GRADIENT and #HOUGH_GRADIENT_ALT, it is the higher threshold of the two passed to the Canny edge detector (the lower one is twice smaller).
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* Note that #HOUGH_GRADIENT_ALT uses #Scharr algorithm to compute image derivatives, so the threshold value shough normally be higher, such as 300 or normally exposed and contrasty images.
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*
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*
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* @param allowableThreshold - When finding the corresponding contour, this is used to see how close a center should be to a contour for it to be considered THAT contour.
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* Should be increased with lower resolutions and decreased with higher resolution
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* */
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public FindCirclePipeParams(
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int allowableThreshold,
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int minRadius,
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@@ -49,6 +49,11 @@ public class FindPolygonPipe
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private CVShape getShape(Contour in) {
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int corners = getCorners(in);
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corners = getCorners(in);
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/*The contourShape enum has predefined shapes for Circles, Triangles, and Quads
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meaning any shape not fitting in those predefined shapes must be a custom shape.
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*/
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if (ContourShape.fromSides(corners) == null) {
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return new CVShape(in, ContourShape.Custom);
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}
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@@ -65,18 +70,21 @@ public class FindPolygonPipe
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}
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private int getCorners(Contour contour) {
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// Release previous approx
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approx.release();
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Imgproc.approxPolyDP(
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contour.getMat2f(),
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approx,
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// Converts an accuracy percentage between 1-100 to an epsilon
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params.accuracyPercentage / 600.0 * Imgproc.arcLength(contour.getMat2f(), true),
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true);
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// The height of the resultant approximation is the number of vertices
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return (int) approx.size().height;
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}
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public static class FindPolygonPipeParams {
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private final double accuracyPercentage;
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// Should be a value between 0-100
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public FindPolygonPipeParams(double accuracyPercentage) {
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this.accuracyPercentage = accuracyPercentage;
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}
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@@ -61,7 +61,7 @@ public class ColoredShapePipeline
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private CVPipeResult<List<TrackedTarget>> targetList;
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private final Point[] rectPoints = new Point[4];
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ColoredShapePipeline() {
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public ColoredShapePipeline() {
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settings = new ColoredShapePipelineSettings();
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}
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