// javadoc: AlignMTB::process(src, dst, times, response)
public void process(List<Mat> src, List<Mat> dst, Mat times, Mat response) {
Mat src_mat = Converters.vector_Mat_to_Mat(src);
Mat dst_mat = Converters.vector_Mat_to_Mat(dst);
process_0(nativeObj, src_mat.nativeObj, dst_mat.nativeObj, times.nativeObj, response.nativeObj);
return;
}
// javadoc: AlignMTB::process(src, dst)
public void process(List<Mat> src, List<Mat> dst) {
Mat src_mat = Converters.vector_Mat_to_Mat(src);
Mat dst_mat = Converters.vector_Mat_to_Mat(dst);
process_1(nativeObj, src_mat.nativeObj, dst_mat.nativeObj);
return;
}
/**
* Detects keypoints in an image (first variant) or image set (second variant).
*
* @param images Image set.
* @param keypoints The detected keypoints. In the second variant of the method <code>keypoints[i]
* </code> is a set of keypoints detected in <code>images[i]</code>.
* @see <a
* href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_feature_detectors.html#featuredetector-detect">org.opencv.features2d.FeatureDetector.detect</a>
*/
public void detect(List<Mat> images, List<MatOfKeyPoint> keypoints) {
Mat images_mat = Converters.vector_Mat_to_Mat(images);
Mat keypoints_mat = new Mat();
detect_3(nativeObj, images_mat.nativeObj, keypoints_mat.nativeObj);
Converters.Mat_to_vector_vector_KeyPoint(keypoints_mat, keypoints);
return;
}
private static Bitmap imgtrafo(
Bitmap image1,
Bitmap image2,
int p1_x,
int p1_y,
int p2_x,
int p2_y,
int p3_x,
int p3_y,
int p4_x,
int p4_y) {
// set output size same size as input
int resultWidth = image1.getWidth();
int resultHeight = image1.getHeight();
Mat inputMat = new Mat(image1.getWidth(), image1.getHeight(), CvType.CV_32FC1);
Utils.bitmapToMat(image1, inputMat);
Mat outputMat = new Mat(resultWidth, resultHeight, CvType.CV_32FC1);
Point ocvPIn1 = new Point(p1_x, p1_y);
Point ocvPIn2 = new Point(p2_x, p2_y);
Point ocvPIn3 = new Point(p3_x, p3_y);
Point ocvPIn4 = new Point(p4_x, p4_y);
List<Point> source = new ArrayList<Point>();
source.add(ocvPIn1);
source.add(ocvPIn2);
source.add(ocvPIn3);
source.add(ocvPIn4);
Mat inputQuad = Converters.vector_Point2f_to_Mat(source);
Point ocvPOut1 = new Point(256, 40); // manually set
Point ocvPOut2 = new Point(522, 62);
Point ocvPOut3 = new Point(455, 479);
Point ocvPOut4 = new Point(134, 404);
List<Point> dest = new ArrayList<Point>();
dest.add(ocvPOut1);
dest.add(ocvPOut2);
dest.add(ocvPOut3);
dest.add(ocvPOut4);
Mat outputQuad = Converters.vector_Point2f_to_Mat(dest);
Mat perspectiveTransform = Imgproc.getPerspectiveTransform(inputQuad, outputQuad);
Imgproc.warpPerspective(
inputMat, outputMat, perspectiveTransform, new Size(resultWidth, resultHeight)); // ?
Bitmap output = Bitmap.createBitmap(resultWidth, resultHeight, Bitmap.Config.RGB_565);
Utils.matToBitmap(outputMat, output);
return output;
}
public static void draw3dAxis(
Mat frame, CameraParameters cp, Scalar color, double height, Mat Rvec, Mat Tvec) {
// Mat objectPoints = new Mat(4,3,CvType.CV_32FC1);
MatOfPoint3f objectPoints = new MatOfPoint3f();
Vector<Point3> points = new Vector<Point3>();
points.add(new Point3(0, 0, 0));
points.add(new Point3(height, 0, 0));
points.add(new Point3(0, height, 0));
points.add(new Point3(0, 0, height));
objectPoints.fromList(points);
MatOfPoint2f imagePoints = new MatOfPoint2f();
Calib3d.projectPoints(
objectPoints, Rvec, Tvec, cp.getCameraMatrix(), cp.getDistCoeff(), imagePoints);
List<Point> pts = new Vector<Point>();
Converters.Mat_to_vector_Point(imagePoints, pts);
Core.line(frame, pts.get(0), pts.get(1), color, 2);
Core.line(frame, pts.get(0), pts.get(2), color, 2);
Core.line(frame, pts.get(0), pts.get(3), color, 2);
Core.putText(frame, "X", pts.get(1), Core.FONT_HERSHEY_SIMPLEX, 0.5, color, 2);
Core.putText(frame, "Y", pts.get(2), Core.FONT_HERSHEY_SIMPLEX, 0.5, color, 2);
Core.putText(frame, "Z", pts.get(3), Core.FONT_HERSHEY_SIMPLEX, 0.5, color, 2);
}
public static Mat warp(Mat inputMat, Mat startM, int factor) {
int resultWidth = 400 * factor;
int resultHeight = 240 * factor;
Mat outputMat = new Mat(resultWidth, resultHeight, CvType.CV_8UC4);
Point ocvPOut1 = new Point(0, 0);
Point ocvPOut2 = new Point(0, resultHeight);
Point ocvPOut3 = new Point(resultWidth, resultHeight);
Point ocvPOut4 = new Point(resultWidth, 0);
List<Point> dest = new ArrayList<Point>();
dest.add(ocvPOut1);
dest.add(ocvPOut2);
dest.add(ocvPOut3);
dest.add(ocvPOut4);
Mat endM = Converters.vector_Point2f_to_Mat(dest);
Mat perspectiveTransform = Imgproc.getPerspectiveTransform(startM, endM);
Imgproc.warpPerspective(
inputMat,
outputMat,
perspectiveTransform,
new Size(resultWidth, resultHeight),
Imgproc.INTER_AREA);
Imgproc.GaussianBlur(outputMat, outputMat, new org.opencv.core.Size(5, 5), 5);
Imgproc.resize(outputMat, outputMat, new Size(resultWidth / factor, resultHeight / factor));
Imgproc.threshold(outputMat, outputMat, 127, 255, Imgproc.THRESH_TOZERO);
return outputMat;
}
// javadoc: buildOpticalFlowPyramid(img, pyramid, winSize, maxLevel, withDerivatives, pyrBorder,
// derivBorder, tryReuseInputImage)
public static int buildOpticalFlowPyramid(
Mat img,
List<Mat> pyramid,
Size winSize,
int maxLevel,
boolean withDerivatives,
int pyrBorder,
int derivBorder,
boolean tryReuseInputImage) {
Mat pyramid_mat = new Mat();
int retVal =
buildOpticalFlowPyramid_0(
img.nativeObj,
pyramid_mat.nativeObj,
winSize.width,
winSize.height,
maxLevel,
withDerivatives,
pyrBorder,
derivBorder,
tryReuseInputImage);
Converters.Mat_to_vector_Mat(pyramid_mat, pyramid);
pyramid_mat.release();
return retVal;
}
/**
* Constructs the image pyramid which can be passed to "calcOpticalFlowPyrLK".
*
* @param img 8-bit input image.
* @param pyramid output pyramid.
* @param winSize window size of optical flow algorithm. Must be not less than <code>winSize
* </code> argument of "calcOpticalFlowPyrLK". It is needed to calculate required padding for
* pyramid levels.
* @param maxLevel 0-based maximal pyramid level number.
* @see <a
* href="http://docs.opencv.org/modules/video/doc/motion_analysis_and_object_tracking.html#buildopticalflowpyramid">org.opencv.video.Video.buildOpticalFlowPyramid</a>
*/
public static int buildOpticalFlowPyramid(
Mat img, List<Mat> pyramid, Size winSize, int maxLevel) {
Mat pyramid_mat = new Mat();
int retVal =
buildOpticalFlowPyramid_1(
img.nativeObj, pyramid_mat.nativeObj, winSize.width, winSize.height, maxLevel);
Converters.Mat_to_vector_Mat(pyramid_mat, pyramid);
return retVal;
}
// javadoc: Subdiv2D::getVoronoiFacetList(idx, facetList, facetCenters)
public void getVoronoiFacetList(
MatOfInt idx, List<MatOfPoint2f> facetList, MatOfPoint2f facetCenters) {
Mat idx_mat = idx;
Mat facetList_mat = new Mat();
Mat facetCenters_mat = facetCenters;
getVoronoiFacetList_0(
nativeObj, idx_mat.nativeObj, facetList_mat.nativeObj, facetCenters_mat.nativeObj);
Converters.Mat_to_vector_vector_Point2f(facetList_mat, facetList);
facetList_mat.release();
return;
}
public void setMatVector(String name, List<Mat> value) {
Mat value_mat = Converters.vector_Mat_to_Mat(value);
setMatVector_0(nativeObj, name, value_mat.nativeObj);
return;
}
public List<Mat> getMatVector(String name) {
List<Mat> retVal = new ArrayList<Mat>();
Mat retValMat = new Mat(getMatVector_0(nativeObj, name));
Converters.Mat_to_vector_Mat(retValMat, retVal);
return retVal;
}
public static void getSquare(Mat imgSource) {
Mat sourceImage = imgSource.clone();
Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BGR2GRAY);
// convert the image to black and white does (8 bit)
Imgproc.Canny(imgSource, imgSource, 50, 50);
// apply gaussian blur to smoothen lines of dots
Imgproc.GaussianBlur(imgSource, imgSource, new org.opencv.core.Size(5, 5), 5);
// find the contours
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(
imgSource, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
double maxArea = -1;
int maxAreaIdx = -1;
// Log.d("size",Integer.toString(contours.size()));
MatOfPoint temp_contour = contours.get(0); // the largest is at the
// index 0 for starting
// point
MatOfPoint2f approxCurve = new MatOfPoint2f();
MatOfPoint largest_contour = contours.get(0);
// largest_contour.ge
List<MatOfPoint> largest_contours = new ArrayList<MatOfPoint>();
// Imgproc.drawContours(imgSource,contours, -1, new Scalar(0, 255, 0),
// 1);
for (int idx = 0; idx < contours.size(); idx++) {
temp_contour = contours.get(idx);
double contourarea = Imgproc.contourArea(temp_contour);
// compare this contour to the previous largest contour found
if (contourarea > maxArea) {
// check if this contour is a square
MatOfPoint2f new_mat = new MatOfPoint2f(temp_contour.toArray());
int contourSize = (int) temp_contour.total();
MatOfPoint2f approxCurve_temp = new MatOfPoint2f();
Imgproc.approxPolyDP(new_mat, approxCurve_temp, contourSize * 0.05, true);
if (approxCurve_temp.total() == 4) {
maxArea = contourarea;
maxAreaIdx = idx;
approxCurve = approxCurve_temp;
largest_contour = temp_contour;
}
}
}
Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BayerBG2RGB);
double[] temp_double;
temp_double = approxCurve.get(0, 0);
Point p1 = new Point(temp_double[0], temp_double[1]);
// Core.circle(imgSource,p1,55,new Scalar(0,0,255));
// Imgproc.warpAffine(sourceImage, dummy, rotImage,sourceImage.size());
temp_double = approxCurve.get(1, 0);
Point p2 = new Point(temp_double[0], temp_double[1]);
// Core.circle(imgSource,p2,150,new Scalar(255,255,255));
temp_double = approxCurve.get(2, 0);
Point p3 = new Point(temp_double[0], temp_double[1]);
// Core.circle(imgSource,p3,200,new Scalar(255,0,0));
temp_double = approxCurve.get(3, 0);
Point p4 = new Point(temp_double[0], temp_double[1]);
// Core.circle(imgSource,p4,100,new Scalar(0,0,255));
List<Point> source = getCorners(p1, p2, p3, p4);
for (Point p : source) {
// System.out.println(p);
}
Mat startM = Converters.vector_Point2f_to_Mat(source);
// Imgproc.cvtColor(sourceImage, sourceImage, Imgproc.COLOR_BGR2GRAY);
Mat result = warp(sourceImage, startM, 5);
// result = warp(result,result,1);
// Imgproc.cvtColor(result, result, Imgproc.COLOR_BGR2GRAY);
Highgui.imwrite(output, result);
// System.out.println("Done");
// return result;
}