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annotate scripts/compute-homography.py @ 773:bf4a1790cfac dev

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minor bug and improvements
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Mon, 01 Feb 2016 16:10:26 -0500
parents 0421a5a0072c
children 1fdafa9f6bf4
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1 #! /usr/bin/env python
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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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9 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)
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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 # TODO process camera intrinsic and extrinsic parameters to obtain image to world homography, taking example from Work/src/python/generate-homography.py script
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40 # cameraMat = load(videoFilenamePrefix+'-camera.txt');
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41 # T1 = cameraMat[3:6,:].copy();
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42 # A = cameraMat[0:3,0:3].copy();
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43
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44 # # pay attention, rotation may be the transpose
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45 # # R = T1[:,0:3].T;
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46 # R = T1[:,0:3];
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47 # rT = dot(R, T1[:,3]/1000);
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48 # T = zeros((3,4),'f');
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49 # T[:,0:3] = R[:];
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50 # T[:,3] = rT;
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51
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52 # AT = dot(A,T);
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53
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54 # nPoints = 4;
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55 # worldPoints = cvCreateMat(nPoints, 3, CV_64FC1);
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56 # imagePoints = cvCreateMat(nPoints, 3, CV_64FC1);
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57
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58 # # extract homography from the camera calibration
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59 # worldPoints = cvCreateMat(4, 3, CV_64FC1);
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60 # imagePoints = cvCreateMat(4, 3, CV_64FC1);
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61
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62 # worldPoints[0,:] = [[1, 1, 0]];
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63 # worldPoints[1,:] = [[1, 2, 0]];
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64 # worldPoints[2,:] = [[2, 1, 0]];
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65 # worldPoints[3,:] = [[2, 2, 0]];
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66
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67 # wPoints = [[1,1,2,2],
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68 # [1,2,1,2],
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69 # [0,0,0,0]];
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70 # iPoints = utils.worldToImage(AT, wPoints);
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71
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72 # for i in range(nPoints):
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73 # imagePoints[i,:] = [iPoints[:,i].tolist()];
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74
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75 # H = cvCreateMat(3, 3, CV_64FC1);
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76
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77 # cvFindHomography(imagePoints, worldPoints, H);
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80 homography = np.array([])
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81 if args.pointCorrespondencesFilename is not None:
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82 worldPts, videoPts = cvutils.loadPointCorrespondences(args.pointCorrespondencesFilename)
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83 homography, mask = cv2.findHomography(videoPts, worldPts) # method=0, ransacReprojThreshold=3
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84 elif args.tsaiCameraFilename is not None: # hack using PDTV
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85 from pdtv import TsaiCamera
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86 f = storage.openCheck(args.tsaiCameraFilename, quitting = True)
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87 content = storage.getLines(f)
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88 cameraData = {}
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89 for l in content:
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90 tmp = l.split(':')
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91 cameraData[tmp[0]] = float(tmp[1].strip().replace(',','.'))
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92 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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93 homography = cvutils.computeHomographyFromPDTV(camera)
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94 elif args.videoFrameFilename is not None and args.worldFilename is not None:
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95 worldImg = plt.imread(args.worldFilename)
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96 videoImg = plt.imread(args.videoFrameFilename)
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97 if args.undistort:
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98 [map1, map2] = cvutils.computeUndistortMaps(videoImg.shape[1], videoImg.shape[0], args.undistortedImageMultiplication, np.loadtxt(args.intrinsicCameraMatrixFilename), args.distortionCoefficients)
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99 videoImg = cv2.remap(videoImg, map1, map2, interpolation=cv2.INTER_LINEAR)
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100 print('Click on {0} points in the video frame'.format(args.nPoints))
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101 plt.figure()
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102 plt.imshow(videoImg)
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103 plt.tight_layout()
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104 videoPts = np.array(plt.ginput(args.nPoints, timeout=3000))
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105 print('Click on {0} points in the world image'.format(args.nPoints))
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106 plt.figure()
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107 plt.imshow(worldImg)
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108 plt.tight_layout()
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109 worldPts = args.unitsPerPixel*np.array(plt.ginput(args.nPoints, timeout=3000))
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110 plt.close('all')
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111 homography, mask = cv2.findHomography(videoPts, worldPts)
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112 # save the points in file
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113 f = open('point-correspondences.txt', 'a')
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114 np.savetxt(f, worldPts.T)
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115 np.savetxt(f, videoPts.T)
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116 f.close()
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117
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118 if homography.size>0:
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119 np.savetxt(args.homographyFilename,homography)
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120
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121 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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122 worldImg = cv2.imread(args.worldFilename)
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123 videoImg = cv2.imread(args.videoFrameFilename)
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124 if args.undistort:
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125 [map1, map2] = cvutils.computeUndistortMaps(videoImg.shape[1], videoImg.shape[0], args.undistortedImageMultiplication, np.loadtxt(args.intrinsicCameraMatrixFilename), args.distortionCoefficients)
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126 videoImg = cv2.remap(videoImg, map1, map2, interpolation=cv2.INTER_LINEAR)
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127 if args.saveImages:
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128 cv2.imwrite(utils.removeExtension(args.videoFrameFilename)+'-undistorted.png', videoImg)
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129 invHomography = np.linalg.inv(homography)
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130 projectedWorldPts = cvutils.projectArray(invHomography, worldPts.T).T
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131 projectedVideoPts = cvutils.projectArray(homography, videoPts.T).T
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132 for i in range(worldPts.shape[0]):
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133 # world image
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134 cv2.circle(worldImg,tuple(np.int32(np.round(worldPts[i]/args.unitsPerPixel))),2,cvutils.cvBlue)
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135 cv2.circle(worldImg,tuple(np.int32(np.round(projectedVideoPts[i]/args.unitsPerPixel))),2,cvutils.cvRed)
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136 cv2.putText(worldImg, str(i+1), tuple(np.int32(np.round(worldPts[i]/args.unitsPerPixel))+5), cv2.FONT_HERSHEY_PLAIN, 2., cvutils.cvBlue, 2)
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137 # video image
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138 cv2.circle(videoImg,tuple(np.int32(np.round(videoPts[i]))),2,cvutils.cvBlue)
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139 cv2.circle(videoImg,tuple(np.int32(np.round(projectedWorldPts[i]))),2,cvutils.cvRed)
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140 cv2.putText(videoImg, str(i+1), tuple(np.int32(np.round(videoPts[i])+5)), cv2.FONT_HERSHEY_PLAIN, 2., cvutils.cvBlue, 2)
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141 cv2.imshow('video frame',videoImg)
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142 cv2.imshow('world image',worldImg)
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143 cv2.waitKey()
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144 cv2.destroyAllWindows()