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annotate scripts/compute-homography.py @ 1061:671426ce0f3e

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author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 11 Jul 2018 17:31:26 -0400
parents cc5cb04b04b0
children 7b4d732f82b3
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933670761a57 updated code to python 3 (tests pass and scripts run, but non-executed parts of code are probably still not correct)
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1 #! /usr/bin/env python3
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3 import sys, argparse
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4
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5 import matplotlib.pyplot as plt
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6 import numpy as np
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7 import cv2
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8
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9 from trafficintelligence import cvutils, utils, storage
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11 # TODO add option to use RANSAC or other robust homography estimation method?
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13 parser = argparse.ArgumentParser(description='The program computes the homography matrix from at least 4 non-colinear point correspondences inputed in the same order in a video frame and a aerial photo/ground map, or from the list of corresponding points in the two planes.', epilog = '''The point correspondence file contains at least 4 non-colinear point coordinates
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14 with the following format:
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15 - the first two lines are the x and y coordinates in the projected space (usually world space)
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16 - the last two lines are the x and y coordinates in the origin space (usually image space)
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17
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18 If providing video and world images, with a number of points to input
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19 and a ration to convert pixels to world distance unit (eg meters per pixel),
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20 the images will be shown in turn and the user should click
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21 in the same order the corresponding points in world and image spaces.''', formatter_class=argparse.RawDescriptionHelpFormatter)
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23 parser.add_argument('-p', dest = 'pointCorrespondencesFilename', help = 'name of the text file containing the point correspondences')
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24 parser.add_argument('--tsai', dest = 'tsaiCameraFilename', help = 'name of the text file containing the camera parameter following the pinhole camera model (Lund format)') # caution, this is Aliaksei's format
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25 parser.add_argument('-i', dest = 'videoFrameFilename', help = 'filename of the video frame')
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26 parser.add_argument('-w', dest = 'worldFilename', help = 'filename of the aerial photo/ground map')
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27 parser.add_argument('-n', dest = 'nPoints', help = 'number of corresponding points to input', default = 4, type = int)
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28 parser.add_argument('-u', dest = 'unitsPerPixel', help = 'number of units per pixel', default = 1., type = float)
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29 parser.add_argument('-o', dest = 'homographyFilename', help = 'filename of the homography matrix', default = 'homography.txt')
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30 parser.add_argument('--display', dest = 'displayPoints', help = 'display original and projected points on both images', action = 'store_true')
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31 parser.add_argument('--intrinsic', dest = 'intrinsicCameraMatrixFilename', help = 'name of the intrinsic camera file')
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32 parser.add_argument('--distortion-coefficients', dest = 'distortionCoefficients', help = 'distortion coefficients', nargs = '*', type = float)
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33 parser.add_argument('--undistorted-multiplication', dest = 'undistortedImageMultiplication', help = 'undistorted image multiplication', type = float, default = 1.)
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34 parser.add_argument('--undistort', dest = 'undistort', help = 'undistort the video (because features have been extracted that way', action = 'store_true')
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35 parser.add_argument('--save', dest = 'saveImages', help = 'save the undistorted video frame (display option must be chosen)', action = 'store_true')
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37 args = parser.parse_args()
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39 homography = np.array([])
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40 if args.pointCorrespondencesFilename is not None:
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41 worldPts, videoPts = cvutils.loadPointCorrespondences(args.pointCorrespondencesFilename)
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42 homography, mask = cv2.findHomography(videoPts, worldPts) # method=0, ransacReprojThreshold=3
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43 elif args.tsaiCameraFilename is not None: # hack using PDTV
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44 from pdtv import TsaiCamera
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45 cameraData = storage.loadPinholeCameraModel(args.tsaiCameraFilename)
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46 camera = TsaiCamera(Cx=cameraData['Cx'], Cy=cameraData['Cy'], Sx=cameraData['Sx'], Tx=cameraData['Tx'], Ty=cameraData['Ty'], Tz=cameraData['Tz'], dx=cameraData['dx'], dy=cameraData['dy'], f=cameraData['f'], k=cameraData['k'], r1=cameraData['r1'], r2=cameraData['r2'], r3=cameraData['r3'], r4=cameraData['r4'], r5=cameraData['r5'], r6=cameraData['r6'], r7=cameraData['r7'], r8=cameraData['r8'], r9=cameraData['r9'])
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47 homography = cvutils.computeHomographyFromPDTV(camera)
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48 elif args.videoFrameFilename is not None and args.worldFilename is not None:
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49 worldImg = plt.imread(args.worldFilename)
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50 videoImg = plt.imread(args.videoFrameFilename)
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51 if args.undistort:
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52 [map1, map2], newCameraMatrix = cvutils.computeUndistortMaps(videoImg.shape[1], videoImg.shape[0], args.undistortedImageMultiplication, np.loadtxt(args.intrinsicCameraMatrixFilename), args.distortionCoefficients)
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53 videoImg = cv2.remap(videoImg, map1, map2, interpolation=cv2.INTER_LINEAR)
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54 print('Click on {} points in the video frame'.format(args.nPoints))
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55 plt.ion()
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56 plt.figure()
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57 plt.imshow(videoImg)
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58 plt.tight_layout()
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59 videoPts = np.array(plt.ginput(args.nPoints, timeout=3000))
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60 if args.undistort:
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61 videoPts = cvutils.newCameraProject(videoPts.T, np.linalg.inv(newCameraMatrix)).T
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62 print('Click on {} points in the world image'.format(args.nPoints))
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63 plt.figure()
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64 plt.imshow(worldImg)
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65 plt.tight_layout()
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66 worldPts = args.unitsPerPixel*np.array(plt.ginput(args.nPoints, timeout=3000))
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67 plt.close('all')
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68 homography, mask = cv2.findHomography(videoPts, worldPts)
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69 # save the points in file
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70 f = open('point-correspondences.txt', 'a')
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71 np.savetxt(f, worldPts.T)
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72 np.savetxt(f, videoPts.T)
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73 f.close()
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74
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75 if homography.size>0:
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76 np.savetxt(args.homographyFilename,homography)
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77
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78 if args.displayPoints and args.videoFrameFilename is not None and args.worldFilename is not None and homography.size>0 and args.tsaiCameraFilename is None:
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79 worldImg = cv2.imread(args.worldFilename)
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80 videoImg = cv2.imread(args.videoFrameFilename)
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81 if args.undistort:
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82 [map1, map2], newCameraMatrix = cvutils.computeUndistortMaps(videoImg.shape[1], videoImg.shape[0], args.undistortedImageMultiplication, np.loadtxt(args.intrinsicCameraMatrixFilename), args.distortionCoefficients)
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83 videoImg = cv2.remap(videoImg, map1, map2, interpolation=cv2.INTER_LINEAR)
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84 if args.saveImages:
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85 cv2.imwrite(utils.removeExtension(args.videoFrameFilename)+'-undistorted.png', videoImg)
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86 invHomography = np.linalg.inv(homography)
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87 projectedWorldPts = cvutils.homographyProject(worldPts.T, invHomography).T
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88 projectedVideoPts = cvutils.homographyProject(videoPts.T, homography).T
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89 if args.undistort:
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90 projectedWorldPts = cvutils.newCameraProject(projectedWorldPts.T, newCameraMatrix).T
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91 videoPts = cvutils.newCameraProject(videoPts.T, newCameraMatrix).T
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92 for i in range(worldPts.shape[0]):
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93 # world image
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94 cv2.circle(worldImg,tuple(np.int32(np.round(worldPts[i]/args.unitsPerPixel))),2,cvutils.cvBlue['default'])
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95 cv2.circle(worldImg,tuple(np.int32(np.round(projectedVideoPts[i]/args.unitsPerPixel))),2,cvutils.cvRed['default'])
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96 cv2.putText(worldImg, str(i+1), tuple(np.int32(np.round(worldPts[i]/args.unitsPerPixel))+5), cv2.FONT_HERSHEY_PLAIN, 2., cvutils.cvBlue['default'], 2)
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97 # video image
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98 cv2.circle(videoImg,tuple(np.int32(np.round(videoPts[i]))),2,cvutils.cvBlue['default'])
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99 cv2.circle(videoImg,tuple(np.int32(np.round(projectedWorldPts[i]))),2,cvutils.cvRed['default'])
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100 cv2.putText(videoImg, str(i+1), tuple(np.int32(np.round(videoPts[i])+5)), cv2.FONT_HERSHEY_PLAIN, 2., cvutils.cvBlue['default'], 2)
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101 cv2.imshow('video frame',videoImg)
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102 cv2.imshow('world image',worldImg)
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103 cv2.waitKey()
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104 cv2.destroyAllWindows()