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Merge pull request opencv#16366 from themechanicalcoder:features2D-tu…
…torial-python * Add python version of panorama_stitching_rotating_camera and perspective_correction * Updated code * added in the docs * added python code in the docs * docs change * Add java tutorial as well * Add toggle in documentation * Added the link for Java code * format code * Refactored code
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89 changes: 89 additions & 0 deletions
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samples/java/tutorial_code/features2D/Homography/PanoramaStitchingRotatingCamera.java
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| import java.util.ArrayList; | ||
| import java.util.List; | ||
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| import org.opencv.core.*; | ||
| import org.opencv.core.Range; | ||
| import org.opencv.highgui.HighGui; | ||
| import org.opencv.imgcodecs.Imgcodecs; | ||
| import org.opencv.imgproc.Imgproc; | ||
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| class PanoramaStitchingRotatingCameraRun { | ||
| void basicPanoramaStitching (String[] args) { | ||
| String img1path = args[0], img2path = args[1]; | ||
| Mat img1 = new Mat(), img2 = new Mat(); | ||
| img1 = Imgcodecs.imread(img1path); | ||
| img2 = Imgcodecs.imread(img2path); | ||
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| //! [camera-pose-from-Blender-at-location-1] | ||
| Mat c1Mo = new Mat( 4, 4, CvType.CV_64FC1 ); | ||
| c1Mo.put(0 ,0 ,0.9659258723258972, 0.2588190734386444, 0.0, 1.5529145002365112, | ||
| 0.08852133899927139, -0.3303661346435547, -0.9396926164627075, -0.10281121730804443, | ||
| -0.24321036040782928, 0.9076734185218811, -0.342020183801651, 6.130080699920654, | ||
| 0, 0, 0, 1 ); | ||
| //! [camera-pose-from-Blender-at-location-1] | ||
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| //! [camera-pose-from-Blender-at-location-2] | ||
| Mat c2Mo = new Mat( 4, 4, CvType.CV_64FC1 ); | ||
| c2Mo.put(0, 0, 0.9659258723258972, -0.2588190734386444, 0.0, -1.5529145002365112, | ||
| -0.08852133899927139, -0.3303661346435547, -0.9396926164627075, -0.10281121730804443, | ||
| 0.24321036040782928, 0.9076734185218811, -0.342020183801651, 6.130080699920654, | ||
| 0, 0, 0, 1); | ||
| //! [camera-pose-from-Blender-at-location-2] | ||
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| //! [camera-intrinsics-from-Blender] | ||
| Mat cameraMatrix = new Mat(3, 3, CvType.CV_64FC1); | ||
| cameraMatrix.put(0, 0, 700.0, 0.0, 320.0, 0.0, 700.0, 240.0, 0, 0, 1 ); | ||
| //! [camera-intrinsics-from-Blender] | ||
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| //! [extract-rotation] | ||
| Range rowRange = new Range(0,3); | ||
| Range colRange = new Range(0,3); | ||
| //! [extract-rotation] | ||
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| //! [compute-rotation-displacement] | ||
| //c1Mo * oMc2 | ||
| Mat R1 = new Mat(c1Mo, rowRange, colRange); | ||
| Mat R2 = new Mat(c2Mo, rowRange, colRange); | ||
| Mat R_2to1 = new Mat(); | ||
| Core.gemm(R1, R2.t(), 1, new Mat(), 0, R_2to1 ); | ||
| //! [compute-rotation-displacement] | ||
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| //! [compute-homography] | ||
| Mat tmp = new Mat(), H = new Mat(); | ||
| Core.gemm(cameraMatrix, R_2to1, 1, new Mat(), 0, tmp); | ||
| Core.gemm(tmp, cameraMatrix.inv(), 1, new Mat(), 0, H); | ||
| Scalar s = new Scalar(H.get(2, 2)[0]); | ||
| Core.divide(H, s, H); | ||
| System.out.println(H.dump()); | ||
| //! [compute-homography] | ||
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| //! [stitch] | ||
| Mat img_stitch = new Mat(); | ||
| Imgproc.warpPerspective(img2, img_stitch, H, new Size(img2.cols()*2, img2.rows()) ); | ||
| Mat half = new Mat(); | ||
| half = new Mat(img_stitch, new Rect(0, 0, img1.cols(), img1.rows())); | ||
| img1.copyTo(half); | ||
| //! [stitch] | ||
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| Mat img_compare = new Mat(); | ||
| Mat img_space = Mat.zeros(new Size(50, img1.rows()), CvType.CV_8UC3); | ||
| List<Mat>list = new ArrayList<>(); | ||
| list.add(img1); | ||
| list.add(img_space); | ||
| list.add(img2); | ||
| Core.hconcat(list, img_compare); | ||
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| HighGui.imshow("Compare Images", img_compare); | ||
| HighGui.imshow("Panorama Stitching", img_stitch); | ||
| HighGui.waitKey(0); | ||
| System.exit(0); | ||
| } | ||
| } | ||
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| public class PanoramaStitchingRotatingCamera { | ||
| public static void main(String[] args) { | ||
| System.loadLibrary(Core.NATIVE_LIBRARY_NAME); | ||
| new PanoramaStitchingRotatingCameraRun().basicPanoramaStitching(args); | ||
| } | ||
| } |
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samples/java/tutorial_code/features2D/Homography/PerspectiveCorrection.java
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| import java.util.ArrayList; | ||
| import java.util.List; | ||
| import java.util.Random; | ||
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| import org.opencv.core.*; | ||
| import org.opencv.calib3d.Calib3d; | ||
| import org.opencv.highgui.HighGui; | ||
| import org.opencv.imgcodecs.Imgcodecs; | ||
| import org.opencv.imgproc.Imgproc; | ||
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| class PerspectiveCorrectionRun { | ||
| void perspectiveCorrection (String[] args) { | ||
| String img1Path = args[0], img2Path = args[1]; | ||
| Mat img1 = Imgcodecs.imread(img1Path); | ||
| Mat img2 = Imgcodecs.imread(img2Path); | ||
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| //! [find-corners] | ||
| MatOfPoint2f corners1 = new MatOfPoint2f(), corners2 = new MatOfPoint2f(); | ||
| boolean found1 = Calib3d.findChessboardCorners(img1, new Size(9, 6), corners1 ); | ||
| boolean found2 = Calib3d.findChessboardCorners(img2, new Size(9, 6), corners2 ); | ||
| //! [find-corners] | ||
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| if (!found1 || !found2) { | ||
| System.out.println("Error, cannot find the chessboard corners in both images."); | ||
| System.exit(-1); | ||
| } | ||
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| //! [estimate-homography] | ||
| Mat H = new Mat(); | ||
| H = Calib3d.findHomography(corners1, corners2); | ||
| System.out.println(H.dump()); | ||
| //! [estimate-homography] | ||
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| //! [warp-chessboard] | ||
| Mat img1_warp = new Mat(); | ||
| Imgproc.warpPerspective(img1, img1_warp, H, img1.size()); | ||
| //! [warp-chessboard] | ||
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| Mat img_draw_warp = new Mat(); | ||
| List<Mat> list1 = new ArrayList<>(), list2 = new ArrayList<>() ; | ||
| list1.add(img2); | ||
| list1.add(img1_warp); | ||
| Core.hconcat(list1, img_draw_warp); | ||
| HighGui.imshow("Desired chessboard view / Warped source chessboard view", img_draw_warp); | ||
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| //! [compute-transformed-corners] | ||
| Mat img_draw_matches = new Mat(); | ||
| list2.add(img1); | ||
| list2.add(img2); | ||
| Core.hconcat(list2, img_draw_matches); | ||
| Point []corners1Arr = corners1.toArray(); | ||
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| for (int i = 0 ; i < corners1Arr.length; i++) { | ||
| Mat pt1 = new Mat(3, 1, CvType.CV_64FC1), pt2 = new Mat(); | ||
| pt1.put(0, 0, corners1Arr[i].x, corners1Arr[i].y, 1 ); | ||
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| Core.gemm(H, pt1, 1, new Mat(), 0, pt2); | ||
| double[] data = pt2.get(2, 0); | ||
| Core.divide(pt2, new Scalar(data[0]), pt2); | ||
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| double[] data1 =pt2.get(0, 0); | ||
| double[] data2 = pt2.get(1, 0); | ||
| Point end = new Point((int)(img1.cols()+ data1[0]), (int)data2[0]); | ||
| Imgproc.line(img_draw_matches, corners1Arr[i], end, RandomColor(), 2); | ||
| } | ||
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| HighGui.imshow("Draw matches", img_draw_matches); | ||
| HighGui.waitKey(0); | ||
| //! [compute-transformed-corners] | ||
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| System.exit(0); | ||
| } | ||
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| Scalar RandomColor () { | ||
| Random rng = new Random(); | ||
| int r = rng.nextInt(256); | ||
| int g = rng.nextInt(256); | ||
| int b = rng.nextInt(256); | ||
| return new Scalar(r, g, b); | ||
| } | ||
| } | ||
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| public class PerspectiveCorrection { | ||
| public static void main (String[] args) { | ||
| System.loadLibrary(Core.NATIVE_LIBRARY_NAME); | ||
| new PerspectiveCorrectionRun().perspectiveCorrection(args); | ||
| } | ||
| } |
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samples/python/tutorial_code/features2D/Homography/panorama_stitching_rotating_camera.py
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| #!/usr/bin/env python | ||
| # -*- coding: utf-8 -*- | ||
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| # Python 2/3 compatibility | ||
| from __future__ import print_function | ||
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| import numpy as np | ||
| import cv2 as cv | ||
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| def basicPanoramaStitching(img1Path, img2Path): | ||
| img1 = cv.imread(cv.samples.findFile(img1Path)) | ||
| img2 = cv.imread(cv.samples.findFile(img2Path)) | ||
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| # [camera-pose-from-Blender-at-location-1] | ||
| c1Mo = np.array([[0.9659258723258972, 0.2588190734386444, 0.0, 1.5529145002365112], | ||
| [ 0.08852133899927139, -0.3303661346435547, -0.9396926164627075, -0.10281121730804443], | ||
| [-0.24321036040782928, 0.9076734185218811, -0.342020183801651, 6.130080699920654], | ||
| [0, 0, 0, 1]],dtype=np.float64) | ||
| # [camera-pose-from-Blender-at-location-1] | ||
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| # [camera-pose-from-Blender-at-location-2] | ||
| c2Mo = np.array([[0.9659258723258972, -0.2588190734386444, 0.0, -1.5529145002365112], | ||
| [-0.08852133899927139, -0.3303661346435547, -0.9396926164627075, -0.10281121730804443], | ||
| [0.24321036040782928, 0.9076734185218811, -0.342020183801651, 6.130080699920654], | ||
| [0, 0, 0, 1]],dtype=np.float64) | ||
| # [camera-pose-from-Blender-at-location-2] | ||
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| # [camera-intrinsics-from-Blender] | ||
| cameraMatrix = np.array([[700.0, 0.0, 320.0], [0.0, 700.0, 240.0], [0, 0, 1]], dtype=np.float32) | ||
| # [camera-intrinsics-from-Blender] | ||
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| # [extract-rotation] | ||
| R1 = c1Mo[0:3, 0:3] | ||
| R2 = c2Mo[0:3, 0:3] | ||
| #[extract-rotation] | ||
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| # [compute-rotation-displacement] | ||
| R2 = R2.transpose() | ||
| R_2to1 = np.dot(R1,R2) | ||
| # [compute-rotation-displacement] | ||
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| # [compute-homography] | ||
| H = cameraMatrix.dot(R_2to1).dot(np.linalg.inv(cameraMatrix)) | ||
| H = H / H[2][2] | ||
| # [compute-homography] | ||
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| # [stitch] | ||
| img_stitch = cv.warpPerspective(img2, H, (img2.shape[1]*2, img2.shape[0])) | ||
| img_stitch[0:img1.shape[0], 0:img1.shape[1]] = img1 | ||
| # [stitch] | ||
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| img_space = np.zeros((img1.shape[0],50,3), dtype=np.uint8) | ||
| img_compare = cv.hconcat([img1,img_space, img2]) | ||
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| cv.imshow("Final", img_compare) | ||
| cv.imshow("Panorama", img_stitch) | ||
| cv.waitKey(0) | ||
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| def main(): | ||
| import argparse | ||
| parser = argparse.ArgumentParser(description="Code for homography tutorial. Example 5: basic panorama stitching from a rotating camera.") | ||
| parser.add_argument("-I1","--image1", help = "path to first image", default="Blender_Suzanne1.jpg") | ||
| parser.add_argument("-I2","--image2", help = "path to second image", default="Blender_Suzanne2.jpg") | ||
| args = parser.parse_args() | ||
| print("Panorama Stitching Started") | ||
| basicPanoramaStitching(args.image1, args.image2) | ||
| print("Panorama Stitching Completed Successfully") | ||
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| if __name__ == '__main__': | ||
| main() |
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