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comparison python/calibration-translation.py @ 158:2d7c6d767a39

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corrected and improved calibration-translation.py
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Fri, 09 Sep 2011 19:23:11 -0400
parents 3aab19947a34
children 115f7f90286d
comparison
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157:3aab19947a34 158:2d7c6d767a39
11 import cvutils 11 import cvutils
12 12
13 # development for the data collected and stabilized by Paul in Summer 2011 13 # development for the data collected and stabilized by Paul in Summer 2011
14 # todo test other features 14 # todo test other features
15 15
16 options = utils.parseCLIOptions('Program to re-calibrate an initial calibration based on point correspondences by adjusting the points to slightly different viewpoints, where all the points are still visible\n\nUsage: ', ['ref_video=', 'ref_homography=', 'ref_points='], sys.argv, ['mask_img=']) 16 options = utils.parseCLIOptions('Program to re-calibrate an initial calibration based on point correspondences by adjusting the points to slightly different viewpoints, where all the points are still visible\n\nUsage: ', ['ref_video=', 'ref_points='], sys.argv, ['mask_img='])
17 #, 'ref_homography='
17 18
18 referenceVideoFilename=options['--ref_video']#'1440-1459_Mercalli.avi' 19 referenceVideoFilename=options['--ref_video']#'1440-1459_Mercalli.avi'
19 referenceHomographyFilename=options['--ref_homography']#'1440-1459_Mercalli-homography.txt' 20 #referenceHomographyFilename=options['--ref_homography']#'1440-1459_Mercalli-homography.txt'
20 points = np.loadtxt(options['--ref_points'], dtype=np.float32) # '1440-1459_Mercalli-point-correspondences.txt' 21 points = np.loadtxt(options['--ref_points'], dtype=np.float32) # '1440-1459_Mercalli-point-correspondences.txt'
21 wldPts = points[:2,:].T 22 wldPts = points[:2,:].T
22 imgPts = points[2:,:].T 23 imgPts = points[2:,:].T
23 24
24 def translatePoints(points, t): 25 def translatePoints(points, t):
28 translated[i] += t[i] 29 translated[i] += t[i]
29 return translated 30 return translated
30 31
31 filenames = [f for f in utils.listfiles('.','avi')] # directory to examine should be current directory 32 filenames = [f for f in utils.listfiles('.','avi')] # directory to examine should be current directory
32 33
33 referenceHomography = np.loadtxt(referenceHomographyFilename) 34 #referenceHomography = np.loadtxt(referenceHomographyFilename)
34 referenceVideoIndex = filenames.index(referenceVideoFilename) 35 referenceVideoIndex = filenames.index(referenceVideoFilename)
35 indices = set(range(len(filenames))) 36 indices = set([1, 2, 3, 4, 5, 6, 7, 9, 10, 11])#set(range(len(filenames)))
36 indices.discard(referenceVideoIndex) 37 #indices.discard(referenceVideoIndex)
37 38
38 images = {} 39 images = {}
39 #features = {} 40 #features = {}
40 captures = {} 41 captures = {}
41 42
53 for j,p in enumerate(imgPts): 54 for j,p in enumerate(imgPts):
54 cv2.circle(displayRef, tuple(p), 3, (255,0,0)) 55 cv2.circle(displayRef, tuple(p), 3, (255,0,0))
55 cv2.putText(displayRef, str(j+1), tuple(p), cv2.FONT_HERSHEY_PLAIN, 1, (255,0,0)) 56 cv2.putText(displayRef, str(j+1), tuple(p), cv2.FONT_HERSHEY_PLAIN, 1, (255,0,0))
56 cv2.imshow('Reference',displayRef) 57 cv2.imshow('Reference',displayRef)
57 58
58 key = -1
59 for f in filenames: # get suitable image references for each video 59 for f in filenames: # get suitable image references for each video
60 captures[f] = cv2.VideoCapture(f) 60 captures[f] = cv2.VideoCapture(f)
61 # TODO if frame image already exists, no need to search for it again
62 key = -1
61 while key != cvutils.cvKeyNumbers['y']: 63 while key != cvutils.cvKeyNumbers['y']:
62 (ret, img) = captures[f].read() 64 (ret, img) = captures[f].read()
63 cv2.imshow('Image',img) 65 cv2.imshow('Image',img)
64 print('Can one see the reference points in the image? (y/n)') 66 print('Can one see the reference points in the image? (y/n)')
65 key = cv2.waitKey(0) 67 key = cv2.waitKey(0)
66 68
67 images[f] = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) 69 images[f] = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
68 cv2.imwrite(utils.removeExtension(filenames[i])+'-frame.png') 70 cv2.imwrite(utils.removeExtension(f)+'-frame.png', img)
69 #images[f] = cv2.imread(f, cv2.CV_LOAD_IMAGE_GRAYSCALE) 71 #images[f] = cv2.imread(f, cv2.CV_LOAD_IMAGE_GRAYSCALE)
70 #features[f] = cv2.goodFeaturesToTrack(images[f], 1000, 0.02, 2, useHarrisDetector = True, mask=maskImg) # todo put parameters on the command line ? 72 #features[f] = cv2.goodFeaturesToTrack(images[f], 1000, 0.02, 2, useHarrisDetector = True, mask=maskImg) # todo put parameters on the command line ?
71 # goodFeaturesToTrack(image, maxCorners, qualityLevel, minDistance[, corners[, mask[, blockSize[, useHarrisDetector[, k]]]]]) 73 # goodFeaturesToTrack(image, maxCorners, qualityLevel, minDistance[, corners[, mask[, blockSize[, useHarrisDetector[, k]]]]])
72 # display features 74 # display features
73 if False: 75 if False:
87 displayImg = cv2.cvtColor(images[filenames[i]], cv2.COLOR_GRAY2RGB) #.copy() 89 displayImg = cv2.cvtColor(images[filenames[i]], cv2.COLOR_GRAY2RGB) #.copy()
88 for p in imgPts: 90 for p in imgPts:
89 cv2.circle(displayImg, tuple(p+t[0]), 3, (255,0,0)) 91 cv2.circle(displayImg, tuple(p+t[0]), 3, (255,0,0))
90 cv2.imshow('Image',displayImg) 92 cv2.imshow('Image',displayImg)
91 93
92 while key != cvutils.cvKeyNumbers['y'] and key != cvutils.cvKeyNumbers['n']: 94 while not(key == cvutils.cvKeyNumbers['y'] or key == cvutils.cvKeyNumbers['n']):
93 print('Are the translated points rightly located (y/n)?') 95 print('Are the translated points rightly located (y/n)?')
94 key = cv2.waitKey(0) 96 key = cv2.waitKey(0)
95 if key == cvutils.cvKeyNumbers['y']: # compute homography with translated numbers 97 if key == cvutils.cvKeyNumbers['y']: # compute homography with translated numbers
96 newImgPts = [p+t[0] for p in imgPts] 98 newImgPts = np.array([p+t[0] for p in imgPts])
97 else: 99 else:
98 print('No translation could be found automatically. You will have to manually input world reference points.') 100 print('No translation could be found automatically. You will have to manually input world reference points.')
99 101
100 if t==None or key != cvutils.cvKeyNumbers['y']:# if no translation could computed or it is not satisfactory 102 if t==None or key != cvutils.cvKeyNumbers['y']:# if no translation could computed or it is not satisfactory
101 # image should be right to get points 103 # image should be right to get points
109 newImgPts = np.array([list(p) for p in plt.ginput(n=wldPts.shape[0], timeout=-1)], dtype = np.float32) 111 newImgPts = np.array([list(p) for p in plt.ginput(n=wldPts.shape[0], timeout=-1)], dtype = np.float32)
110 112
111 homography, mask = cv2.findHomography(newImgPts, wldPts) # method=0, ransacReprojThreshold=3 113 homography, mask = cv2.findHomography(newImgPts, wldPts) # method=0, ransacReprojThreshold=3
112 print homography 114 print homography
113 np.savetxt(utils.removeExtension(filenames[i])+'-homography.txt',homography) 115 np.savetxt(utils.removeExtension(filenames[i])+'-homography.txt',homography)
114 np.savetxt(utils.removeExtension(filenames[i])+'-point-correspondences.txt', append(wldPts.T, newImgPts.T, axis=0)) 116 np.savetxt(utils.removeExtension(filenames[i])+'-point-correspondences.txt', np.append(wldPts.T, newImgPts.T, axis=0))
115 117
116 cv2.destroyAllWindows() 118 cv2.destroyAllWindows()