Mercurial > hg > nsaunier > traffic-intelligence

comparison scripts/extract-appearance-images.py @ 911:3dd5acfa1899

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corrected potential issues with videos where one cannot reach a give frame from its number
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 28 Jun 2017 16:46:45 -0400
parents cd038493f8c6
children e5970606066f
comparison
equal deleted inserted replaced
910:b58a1061a717 911:3dd5acfa1899
13 parser.add_argument('-i', dest = 'videoFilename', help = 'name of the video file (overrides the configuration file)') 13 parser.add_argument('-i', dest = 'videoFilename', help = 'name of the video file (overrides the configuration file)')
14 parser.add_argument('--gt', dest = 'classificationAnnotationFilename', help = 'name of the file containing the correct classes (user types)', required = True) 14 parser.add_argument('--gt', dest = 'classificationAnnotationFilename', help = 'name of the file containing the correct classes (user types)', required = True)
15 parser.add_argument('--delimiter', dest = 'classificationAnnotationFilenameDelimiter', help = 'delimiter for the fields in the correct classification file', default= ' ') 15 parser.add_argument('--delimiter', dest = 'classificationAnnotationFilenameDelimiter', help = 'delimiter for the fields in the correct classification file', default= ' ')
16 parser.add_argument('-s', dest = 'nFramesStep', help = 'number of frames between each saved patch', default = 50, type = int) 16 parser.add_argument('-s', dest = 'nFramesStep', help = 'number of frames between each saved patch', default = 50, type = int)
17 parser.add_argument('-n', dest = 'nObjects', help = 'number of objects to use to extract patches from', type = int, default = None) 17 parser.add_argument('-n', dest = 'nObjects', help = 'number of objects to use to extract patches from', type = int, default = None)
18 parser.add_argument('--start-frame0', dest = 'startFrame0', help = 'starts with first frame for videos with index problem where frames cannot be reached', action = 'store_true')
18 parser.add_argument('-o', dest = 'overlap', help = 'maximum intersection over union of the features nFramesStep apart to save image', type = float, default = 0.2) 19 parser.add_argument('-o', dest = 'overlap', help = 'maximum intersection over union of the features nFramesStep apart to save image', type = float, default = 0.2)
19 parser.add_argument('--extract-all', dest = 'extractAllObjectImages', help = 'extracts the images for all objects, well classified or not (otherwise, extracts only for the misclassified)', action = 'store_true') 20 parser.add_argument('--extract-all', dest = 'extractAllObjectImages', help = 'extracts the images for all objects, well classified or not (otherwise, extracts only for the misclassified)', action = 'store_true')
20 parser.add_argument('--prefix', dest = 'imagePrefix', help = 'image prefix', default = 'img') 21 parser.add_argument('--prefix', dest = 'imagePrefix', help = 'image prefix', default = 'img')
21 parser.add_argument('--ouput', dest = 'directoryName', help = 'parent directory name for the directories containing the samples for the different road users', default = '.') 22 parser.add_argument('--ouput', dest = 'directoryName', help = 'parent directory name for the directories containing the samples for the different road users', default = '.')
22 parser.add_argument('--compute-speed-distributions', dest = 'computeSpeedDistribution', help = 'computes the distribution of the road users of each type and fits parameters to each', action = 'store_true') 23 parser.add_argument('--compute-speed-distributions', dest = 'computeSpeedDistribution', help = 'computes the distribution of the road users of each type and fits parameters to each', action = 'store_true')
38 objects = storage.loadTrajectoriesFromSqlite(databaseFilename, 'object', annotatedObjectNumbers, withFeatures = True) 39 objects = storage.loadTrajectoriesFromSqlite(databaseFilename, 'object', annotatedObjectNumbers, withFeatures = True)
39 for obj in objects: 40 for obj in objects:
40 if obj.getNum() in annotatedObjectNumbers: 41 if obj.getNum() in annotatedObjectNumbers:
41 obj.setUserType(classificationAnnotations.loc[obj.getNum(), 'road_user_type']) 42 obj.setUserType(classificationAnnotations.loc[obj.getNum(), 'road_user_type'])
42 timeInterval = moving.TimeInterval.unionIntervals([obj.getTimeInterval() for obj in objects]) 43 timeInterval = moving.TimeInterval.unionIntervals([obj.getTimeInterval() for obj in objects])
44 if args.startFrame0:
45 timeInterval.first = 0
43 46
44 for userType in classificationAnnotations['road_user_type'].unique(): 47 for userType in classificationAnnotations['road_user_type'].unique():
45 if not os.path.exists(args.directoryName+os.sep+moving.userTypeNames[userType]): 48 if not os.path.exists(args.directoryName+os.sep+moving.userTypeNames[userType]):
46 os.mkdir(args.directoryName+os.sep+moving.userTypeNames[userType]) 49 os.mkdir(args.directoryName+os.sep+moving.userTypeNames[userType])
47 50
54 height, width = map1.shape 57 height, width = map1.shape
55 58
56 if capture.isOpened(): 59 if capture.isOpened():
57 ret = True 60 ret = True
58 frameNum = timeInterval.first 61 frameNum = timeInterval.first
59 capture.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, frameNum) 62 if not args.startFrame0:
63 capture.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, frameNum)
60 lastFrameNum = timeInterval.last 64 lastFrameNum = timeInterval.last
61 while ret and frameNum <= timeInterval.last: 65 while ret and frameNum <= timeInterval.last:
62 ret, img = capture.read() 66 ret, img = capture.read()
63 distorted = True 67 distorted = True
64 if ret: 68 if ret: