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comparison python/calibration-translation.py @ 160:b0719b3ad3db

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created function to load point correspondences and updates scripts that use it
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Mon, 19 Sep 2011 16:43:28 -0400
parents 115f7f90286d
children 514f6b98cd8c
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159:115f7f90286d 160:b0719b3ad3db
10 import cv2 10 import cv2
11 import utils 11 import utils
12 import cvutils 12 import cvutils
13 13
14 # development for the data collected and stabilized by Paul in Summer 2011 14 # development for the data collected and stabilized by Paul in Summer 2011
15 # todo test other features 15 # todo write help, add options to control the parameters for matching (n points and distance)
16 16
17 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 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='])
18 #, 'ref_homography='
19 18
20 referenceVideoFilename=options['--ref_video']#'1440-1459_Mercalli.avi' 19 referenceVideoFilename=options['--ref_video']
21 #referenceHomographyFilename=options['--ref_homography']#'1440-1459_Mercalli-homography.txt' 20 wldPts, imgPts = cvutils.loadPointCorrespondences(options['--ref_points'])
22 points = np.loadtxt(options['--ref_points'], dtype=np.float32) # '1440-1459_Mercalli-point-correspondences.txt'
23 wldPts = points[:2,:].T
24 imgPts = points[2:,:].T
25 21
26 def translatePoints(points, t): 22 def translatePoints(points, t):
27 'points is Nx2, t is [x,y]' 23 'points is Nx2, t is [x,y]'
28 translated = points.copy() 24 translated = points.copy()
29 for i in xrange(2): 25 for i in xrange(2):
30 translated[i] += t[i] 26 translated[i] += t[i]
31 return translated 27 return translated
32 28
33 filenames = [f for f in utils.listfiles('.','avi')] # directory to examine should be current directory 29 filenames = [f for f in utils.listfiles('.','avi')] # directory to examine should be current directory
34 30
35 #referenceHomography = np.loadtxt(referenceHomographyFilename)
36 referenceVideoIndex = filenames.index(referenceVideoFilename) 31 referenceVideoIndex = filenames.index(referenceVideoFilename)
37 indices = set(range(len(filenames))) 32 indices = set(range(len(filenames)))
38 indices.discard(referenceVideoIndex) 33 indices.discard(referenceVideoIndex)
39 34
40 images = {} 35 images = {}
41 #features = {}
42 captures = {} 36 captures = {}
43 37
44 captures[referenceVideoFilename] = cv2.VideoCapture(referenceVideoFilename) 38 captures[referenceVideoFilename] = cv2.VideoCapture(referenceVideoFilename)
45 (ret, img) = captures[referenceVideoFilename].read() 39 (ret, img) = captures[referenceVideoFilename].read()
46 images[referenceVideoFilename] = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) 40 images[referenceVideoFilename] = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
47 41
42 # load a mask image to compute the translation
48 if '--mask_img' in options.keys(): 43 if '--mask_img' in options.keys():
49 maskImg = cv2.imread('mask.png', cv2.CV_LOAD_IMAGE_GRAYSCALE) # todo add possibility to look in the whole image if not providing mask 44 maskImg = cv2.imread('mask.png', cv2.CV_LOAD_IMAGE_GRAYSCALE) # todo add possibility to look in the whole image if not providing mask
50 else: 45 else:
51 maskImg = np.ones(images[referenceVideoFilename].shape, dtype=np.uint8) 46 maskImg = np.ones(images[referenceVideoFilename].shape, dtype=np.uint8)
52 47
55 for j,p in enumerate(imgPts): 50 for j,p in enumerate(imgPts):
56 cv2.circle(displayRef, tuple(p), 3, (255,0,0)) 51 cv2.circle(displayRef, tuple(p), 3, (255,0,0))
57 cv2.putText(displayRef, str(j+1), tuple(p), cv2.FONT_HERSHEY_PLAIN, 1, (255,0,0)) 52 cv2.putText(displayRef, str(j+1), tuple(p), cv2.FONT_HERSHEY_PLAIN, 1, (255,0,0))
58 cv2.imshow('Reference',displayRef) 53 cv2.imshow('Reference',displayRef)
59 54
60 for f in filenames: # get suitable image references for each video 55 # get suitable image references for each video
56 for f in filenames:
61 captures[f] = cv2.VideoCapture(f) 57 captures[f] = cv2.VideoCapture(f)
62 frameFilename = utils.removeExtension(f)+'-frame.png' # TODO if frame image already exists, no need to search for it again 58 frameFilename = utils.removeExtension(f)+'-frame.png' # TODO if frame image already exists, no need to search for it again
63 if not os.path.exists(frameFilename): 59 if not os.path.exists(frameFilename):
64 key = -1 60 key = -1
65 while key != cvutils.cvKeyNumbers['y']: 61 while key != cvutils.cvKeyNumbers['y']:
82 # cv2.imshow('Reference',display) 78 # cv2.imshow('Reference',display)
83 # cv2.waitKey() 79 # cv2.waitKey()
84 80
85 plt.close('all') 81 plt.close('all')
86 82
83 # validate or input point correspondences and compute homography
87 for i in indices: 84 for i in indices:
88 t = cvutils.computeTranslation(images[filenames[referenceVideoIndex]], images[filenames[i]], referenceFeatures, 100, 10) 85 t = cvutils.computeTranslation(images[filenames[referenceVideoIndex]], images[filenames[i]], referenceFeatures, 100, 10)
89 print filenames[i],t 86 print filenames[i],t
90 key = -1 87 key = -1
91 if t != None: # show translated points and ask if ok 88 if t != None: # show translated points and ask if ok
101 newImgPts = np.array([p+t[0] for p in imgPts]) 98 newImgPts = np.array([p+t[0] for p in imgPts])
102 else: 99 else:
103 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.')
104 101
105 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
106 # image should be right to get points
107 # todo save image
108 print('Select the corresponding points in the same order as in the reference image') 103 print('Select the corresponding points in the same order as in the reference image')
109 plt.figure(1) 104 plt.figure(1)
110 plt.imshow(displayRef) 105 plt.imshow(displayRef)
111 plt.figure(2) 106 plt.figure(2)
112 plt.imshow(img) 107 plt.imshow(img)