mirror of https://github.com/opencv/opencv.git
Alexander Alekhin
5 years ago
commit
fb61f88b9c
29 changed files with 1063 additions and 310 deletions
@ -0,0 +1,75 @@ |
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import java.util.Arrays; |
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import org.opencv.core.*; |
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import org.opencv.highgui.HighGui; |
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import org.opencv.imgproc.Imgproc; |
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import org.opencv.video.Video; |
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import org.opencv.videoio.VideoCapture; |
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|
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|
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class Camshift { |
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public void run(String[] args) { |
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String filename = args[0]; |
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VideoCapture capture = new VideoCapture(filename); |
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if (!capture.isOpened()) { |
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System.out.println("Unable to open file!"); |
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System.exit(-1); |
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} |
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|
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Mat frame = new Mat(), hsv_roi = new Mat(), mask = new Mat(), roi; |
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// take the first frame of the video
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capture.read(frame); |
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//setup initial location of window
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Rect track_window = new Rect(300, 200, 100, 50); |
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|
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// set up the ROI for tracking
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roi = new Mat(frame, track_window); |
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Imgproc.cvtColor(roi, hsv_roi, Imgproc.COLOR_BGR2HSV); |
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Core.inRange(hsv_roi, new Scalar(0, 60, 32), new Scalar(180, 255, 255), mask); |
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|
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MatOfFloat range = new MatOfFloat(0, 256); |
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Mat roi_hist = new Mat(); |
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MatOfInt histSize = new MatOfInt(180); |
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MatOfInt channels = new MatOfInt(0); |
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Imgproc.calcHist(Arrays.asList(hsv_roi), channels, mask, roi_hist, histSize, range); |
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Core.normalize(roi_hist, roi_hist, 0, 255, Core.NORM_MINMAX); |
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|
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// Setup the termination criteria, either 10 iteration or move by atleast 1 pt
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TermCriteria term_crit = new TermCriteria(TermCriteria.EPS | TermCriteria.COUNT, 10, 1); |
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while (true) { |
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Mat hsv = new Mat() , dst = new Mat(); |
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capture.read(frame); |
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if (frame.empty()) { |
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break; |
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} |
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Imgproc.cvtColor(frame, hsv, Imgproc.COLOR_BGR2HSV); |
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Imgproc.calcBackProject(Arrays.asList(hsv), channels, roi_hist, dst, range, 1); |
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|
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// apply camshift to get the new location
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RotatedRect rot_rect = Video.CamShift(dst, track_window, term_crit); |
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|
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// Draw it on image
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Point[] points = new Point[4]; |
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rot_rect.points(points); |
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for (int i = 0; i < 4 ;i++) { |
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Imgproc.line(frame, points[i], points[(i+1)%4], new Scalar(255, 0, 0),2); |
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} |
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|
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HighGui.imshow("img2", frame); |
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int keyboard = HighGui.waitKey(30); |
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if (keyboard == 'q'|| keyboard == 27) { |
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break; |
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} |
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} |
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System.exit(0); |
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} |
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} |
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|
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public class CamshiftDemo { |
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public static void main(String[] args) { |
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System.loadLibrary(Core.NATIVE_LIBRARY_NAME); |
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new Camshift().run(args); |
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} |
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} |
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@ -0,0 +1,70 @@ |
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import java.util.Arrays; |
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import org.opencv.core.*; |
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import org.opencv.highgui.HighGui; |
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import org.opencv.imgproc.Imgproc; |
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import org.opencv.video.Video; |
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import org.opencv.videoio.VideoCapture; |
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|
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class Meanshift { |
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public void run(String[] args) { |
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String filename = args[0]; |
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VideoCapture capture = new VideoCapture(filename); |
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if (!capture.isOpened()) { |
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System.out.println("Unable to open file!"); |
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System.exit(-1); |
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} |
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Mat frame = new Mat(), hsv_roi = new Mat(), mask = new Mat(), roi; |
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|
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// take the first frame of the video
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capture.read(frame); |
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//setup initial location of window
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Rect track_window = new Rect(300, 200, 100, 50); |
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// setup initial location of window
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roi = new Mat(frame, track_window); |
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Imgproc.cvtColor(roi, hsv_roi, Imgproc.COLOR_BGR2HSV); |
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Core.inRange(hsv_roi, new Scalar(0, 60, 32), new Scalar(180, 255, 255), mask); |
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MatOfFloat range = new MatOfFloat(0, 256); |
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Mat roi_hist = new Mat(); |
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MatOfInt histSize = new MatOfInt(180); |
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MatOfInt channels = new MatOfInt(0); |
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Imgproc.calcHist(Arrays.asList(hsv_roi), channels, mask, roi_hist, histSize, range); |
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Core.normalize(roi_hist, roi_hist, 0, 255, Core.NORM_MINMAX); |
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// Setup the termination criteria, either 10 iteration or move by atleast 1 pt
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TermCriteria term_crit = new TermCriteria(TermCriteria.EPS | TermCriteria.COUNT, 10, 1); |
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while (true) { |
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Mat hsv = new Mat() , dst = new Mat(); |
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capture.read(frame); |
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if (frame.empty()) { |
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break; |
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} |
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Imgproc.cvtColor(frame, hsv, Imgproc.COLOR_BGR2HSV); |
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Imgproc.calcBackProject(Arrays.asList(hsv), channels, roi_hist, dst, range, 1); |
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// apply meanshift to get the new location
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Video.meanShift(dst, track_window, term_crit); |
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// Draw it on image
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Imgproc.rectangle(frame, track_window, new Scalar(255, 0, 0), 2); |
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HighGui.imshow("img2", frame); |
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int keyboard = HighGui.waitKey(30); |
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if (keyboard == 'q' || keyboard == 27) { |
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break; |
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} |
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} |
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System.exit(0); |
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} |
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} |
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|
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public class MeanshiftDemo { |
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public static void main(String[] args) { |
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System.loadLibrary(Core.NATIVE_LIBRARY_NAME); |
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new Meanshift().run(args); |
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} |
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} |
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@ -0,0 +1,96 @@ |
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import java.util.ArrayList; |
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import java.util.Random; |
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import org.opencv.core.*; |
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import org.opencv.highgui.HighGui; |
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import org.opencv.imgproc.Imgproc; |
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import org.opencv.video.Video; |
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import org.opencv.videoio.VideoCapture; |
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class OptFlow { |
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public void run(String[] args) { |
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String filename = args[0]; |
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VideoCapture capture = new VideoCapture(filename); |
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if (!capture.isOpened()) { |
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System.out.println("Unable to open this file"); |
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System.exit(-1); |
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} |
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// Create some random colors
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Scalar[] colors = new Scalar[100]; |
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Random rng = new Random(); |
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for (int i = 0 ; i < 100 ; i++) { |
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int r = rng.nextInt(256); |
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int g = rng.nextInt(256); |
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int b = rng.nextInt(256); |
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colors[i] = new Scalar(r, g, b); |
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} |
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Mat old_frame = new Mat() , old_gray = new Mat(); |
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// Since the function Imgproc.goodFeaturesToTrack requires MatofPoint
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// therefore first p0MatofPoint is passed to the function and then converted to MatOfPoint2f
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MatOfPoint p0MatofPoint = new MatOfPoint(); |
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capture.read(old_frame); |
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Imgproc.cvtColor(old_frame, old_gray, Imgproc.COLOR_BGR2GRAY); |
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Imgproc.goodFeaturesToTrack(old_gray, p0MatofPoint,100,0.3,7, new Mat(),7,false,0.04); |
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MatOfPoint2f p0 = new MatOfPoint2f(p0MatofPoint.toArray()) , p1 = new MatOfPoint2f(); |
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// Create a mask image for drawing purposes
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Mat mask = Mat.zeros(old_frame.size(), old_frame.type()); |
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while (true) { |
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Mat frame = new Mat(), frame_gray = new Mat(); |
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capture.read(frame); |
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if (frame.empty()) { |
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break; |
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} |
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Imgproc.cvtColor(frame, frame_gray, Imgproc.COLOR_BGR2GRAY); |
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// calculate optical flow
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MatOfByte status = new MatOfByte(); |
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MatOfFloat err = new MatOfFloat(); |
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TermCriteria criteria = new TermCriteria(TermCriteria.COUNT + TermCriteria.EPS,10,0.03); |
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Video.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, p1, status, err, new Size(15,15),2, criteria); |
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byte StatusArr[] = status.toArray(); |
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Point p0Arr[] = p0.toArray(); |
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Point p1Arr[] = p1.toArray(); |
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ArrayList<Point> good_new = new ArrayList<>(); |
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for (int i = 0; i<StatusArr.length ; i++ ) { |
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if (StatusArr[i] == 1) { |
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good_new.add(p1Arr[i]); |
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Imgproc.line(mask, p1Arr[i], p0Arr[i], colors[i],2); |
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Imgproc.circle(frame, p1Arr[i],5, colors[i],-1); |
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} |
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} |
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Mat img = new Mat(); |
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Core.add(frame, mask, img); |
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HighGui.imshow("Frame", img); |
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int keyboard = HighGui.waitKey(30); |
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if (keyboard == 'q' || keyboard == 27) { |
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break; |
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} |
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// Now update the previous frame and previous points
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old_gray = frame_gray.clone(); |
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Point[] good_new_arr = new Point[good_new.size()]; |
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good_new_arr = good_new.toArray(good_new_arr); |
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p0 = new MatOfPoint2f(good_new_arr); |
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} |
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System.exit(0); |
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} |
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} |
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public class OpticalFlowDemo { |
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public static void main(String[] args) { |
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System.loadLibrary(Core.NATIVE_LIBRARY_NAME); |
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new OptFlow().run(args); |
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} |
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} |
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@ -0,0 +1,72 @@ |
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import java.util.ArrayList; |
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import org.opencv.core.*; |
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import org.opencv.highgui.HighGui; |
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import org.opencv.imgproc.Imgproc; |
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import org.opencv.video.Video; |
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import org.opencv.videoio.VideoCapture; |
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class OptFlowDense { |
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public void run(String[] args) { |
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String filename = args[0]; |
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VideoCapture capture = new VideoCapture(filename); |
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if (!capture.isOpened()) { |
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//error in opening the video input
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System.out.println("Unable to open file!"); |
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System.exit(-1); |
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} |
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Mat frame1 = new Mat() , prvs = new Mat(); |
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capture.read(frame1); |
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Imgproc.cvtColor(frame1, prvs, Imgproc.COLOR_BGR2GRAY); |
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while (true) { |
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Mat frame2 = new Mat(), next = new Mat(); |
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capture.read(frame2); |
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if (frame2.empty()) { |
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break; |
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} |
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Imgproc.cvtColor(frame2, next, Imgproc.COLOR_BGR2GRAY); |
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Mat flow = new Mat(prvs.size(), CvType.CV_32FC2); |
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Video.calcOpticalFlowFarneback(prvs, next, flow,0.5,3,15,3,5,1.2,0); |
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// visualization
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ArrayList<Mat> flow_parts = new ArrayList<>(2); |
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Core.split(flow, flow_parts); |
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Mat magnitude = new Mat(), angle = new Mat(), magn_norm = new Mat(); |
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Core.cartToPolar(flow_parts.get(0), flow_parts.get(1), magnitude, angle,true); |
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Core.normalize(magnitude, magn_norm,0.0,1.0, Core.NORM_MINMAX); |
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float factor = (float) ((1.0/360.0)*(180.0/255.0)); |
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Mat new_angle = new Mat(); |
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Core.multiply(angle, new Scalar(factor), new_angle); |
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//build hsv image
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ArrayList<Mat> _hsv = new ArrayList<>() ; |
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Mat hsv = new Mat(), hsv8 = new Mat(), bgr = new Mat(); |
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_hsv.add(new_angle); |
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_hsv.add(Mat.ones(angle.size(), CvType.CV_32F)); |
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_hsv.add(magn_norm); |
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Core.merge(_hsv, hsv); |
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hsv.convertTo(hsv8, CvType.CV_8U, 255.0); |
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Imgproc.cvtColor(hsv8, bgr, Imgproc.COLOR_HSV2BGR); |
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HighGui.imshow("frame2", bgr); |
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int keyboard = HighGui.waitKey(30); |
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if (keyboard == 'q' || keyboard == 27) { |
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break; |
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} |
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prvs = next; |
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} |
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System.exit(0); |
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} |
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} |
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public class OpticalFlowDenseDemo { |
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public static void main(String[] args) { |
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System.loadLibrary(Core.NATIVE_LIBRARY_NAME); |
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new OptFlowDense().run(args); |
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} |
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} |
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from __future__ import print_function |
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import numpy as np |
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import cv2 as cv |
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import sys |
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def help(filename): |
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print ( |
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''' |
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{0} shows the usage of the OpenCV serialization functionality. \n\n |
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usage:\n |
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python3 {0} outputfile.yml.gz\n\n |
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The output file may be either in XML, YAML or JSON. You can even compress it\n |
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by specifying this in its extension like xml.gz yaml.gz etc... With\n |
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FileStorage you can serialize objects in OpenCV.\n\n |
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For example: - create a class and have it serialized\n |
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- use it to read and write matrices.\n |
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'''.format(filename) |
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) |
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class MyData: |
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A = 97 |
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X = np.pi |
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name = 'mydata1234' |
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def __repr__(self): |
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s = '{ name = ' + self.name + ', X = ' + str(self.X) |
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s = s + ', A = ' + str(self.A) + '}' |
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return s |
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## [inside] |
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def write(self, fs): |
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fs.write('MyData','{') |
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fs.write('A', self.A) |
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fs.write('X', self.X) |
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fs.write('name', self.name) |
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fs.write('MyData','}') |
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def read(self, node): |
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if (not node.empty()): |
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self.A = int(node.getNode('A').real()) |
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self.X = node.getNode('X').real() |
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self.name = node.getNode('name').string() |
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else: |
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self.A = self.X = 0 |
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self.name = '' |
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## [inside] |
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def main(argv): |
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if len(argv) != 2: |
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help(argv[0]) |
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exit(1) |
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# write |
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## [iomati] |
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R = np.eye(3,3) |
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T = np.zeros((3,1)) |
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## [iomati] |
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## [customIOi] |
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m = MyData() |
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## [customIOi] |
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filename = argv[1] |
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## [open] |
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s = cv.FileStorage(filename, cv.FileStorage_WRITE) |
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# or: |
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# s = cv.FileStorage() |
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# s.open(filename, cv.FileStorage_WRITE) |
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## [open] |
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## [writeNum] |
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s.write('iterationNr', 100) |
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## [writeNum] |
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## [writeStr] |
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s.write('strings', '[') |
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s.write('image1.jpg','Awesomeness') |
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s.write('../data/baboon.jpg',']') |
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## [writeStr] |
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|
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## [writeMap] |
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s.write ('Mapping', '{') |
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s.write ('One', 1) |
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s.write ('Two', 2) |
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s.write ('Mapping', '}') |
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## [writeMap] |
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|
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## [iomatw] |
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s.write ('R_MAT', R) |
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s.write ('T_MAT', T) |
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## [iomatw] |
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## [customIOw] |
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m.write(s) |
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## [customIOw] |
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## [close] |
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s.release() |
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## [close] |
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print ('Write Done.') |
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|
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# read |
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print ('\nReading: ') |
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s = cv.FileStorage() |
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s.open(filename, cv.FileStorage_READ) |
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## [readNum] |
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n = s.getNode('iterationNr') |
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itNr = int(n.real()) |
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## [readNum] |
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print (itNr) |
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|
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if (not s.isOpened()): |
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print ('Failed to open ', filename, file=sys.stderr) |
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help(argv[0]) |
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exit(1) |
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|
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## [readStr] |
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n = s.getNode('strings') |
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if (not n.isSeq()): |
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print ('strings is not a sequence! FAIL', file=sys.stderr) |
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exit(1) |
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for i in range(n.size()): |
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print (n.at(i).string()) |
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## [readStr] |
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|
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## [readMap] |
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n = s.getNode('Mapping') |
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print ('Two',int(n.getNode('Two').real()),'; ') |
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print ('One',int(n.getNode('One').real()),'\n') |
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## [readMap] |
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|
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## [iomat] |
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R = s.getNode('R_MAT').mat() |
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T = s.getNode('T_MAT').mat() |
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## [iomat] |
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## [customIO] |
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m.read(s.getNode('MyData')) |
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## [customIO] |
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|
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print ('\nR =',R) |
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print ('T =',T,'\n') |
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print ('MyData =','\n',m,'\n') |
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|
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## [nonexist] |
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print ('Attempt to read NonExisting (should initialize the data structure', |
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'with its default).') |
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m.read(s.getNode('NonExisting')) |
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print ('\nNonExisting =','\n',m) |
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## [nonexist] |
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|
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print ('\nTip: Open up',filename,'with a text editor to see the serialized data.') |
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|
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if __name__ == '__main__': |
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main(sys.argv) |
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