Mercurial > hg > nsaunier > traffic-intelligence

comparison scripts/classify-objects.py @ 684:6d2ece4aed7c dev

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bug forgot to svae objects
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Fri, 05 Jun 2015 13:26:51 +0200
parents f3a0b652b590
children 94b291a5f933
comparison
equal deleted inserted replaced
683:f3a0b652b590 684:6d2ece4aed7c
70 70
71 capture = cv2.VideoCapture(params.videoFilename) 71 capture = cv2.VideoCapture(params.videoFilename)
72 width = int(capture.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH)) 72 width = int(capture.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
73 height = int(capture.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)) 73 height = int(capture.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
74 74
75 pastObjects = []
75 if params.undistort: # setup undistortion 76 if params.undistort: # setup undistortion
76 [map1, map2] = computeUndistortMaps(width, height, undistortedImageMultiplication, intrinsicCameraMatrix, distortionCoefficients) 77 [map1, map2] = computeUndistortMaps(width, height, undistortedImageMultiplication, intrinsicCameraMatrix, distortionCoefficients)
77 if capture.isOpened(): 78 if capture.isOpened():
78 ret = True 79 ret = True
79 frameNum = timeInterval.first 80 frameNum = timeInterval.first
85 if ret: 86 if ret:
86 if frameNum%50 == 0: 87 if frameNum%50 == 0:
87 print('frame number: {}'.format(frameNum)) 88 print('frame number: {}'.format(frameNum))
88 currentObjects = [] 89 currentObjects = []
89 for obj in objects: 90 for obj in objects:
90 if obj.getLastFrameNum() < frameNum: 91 if obj.getLastInstant() < frameNum:
91 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = params.minSpeedEquiprobable, speedProbabilities = speedProbabilities) 92 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = params.minSpeedEquiprobable, speedProbabilities = speedProbabilities)
93 pastObjects.append(obj)
92 else: 94 else:
93 currentObjects.append(obj) 95 currentObjects.append(obj)
94 objects = currentObjects 96 objects = currentObjects
95 if params.undistort: 97 if params.undistort:
96 img = cv2.remap(img, map1, map2, interpolation=cv2.INTER_LINEAR) 98 img = cv2.remap(img, map1, map2, interpolation=cv2.INTER_LINEAR)
101 obj.classifyUserTypeHoGSVMAtInstant(img, frameNum, invHomography, width, height, 0.2, 0.2, 800) # px, py, pixelThreshold 103 obj.classifyUserTypeHoGSVMAtInstant(img, frameNum, invHomography, width, height, 0.2, 0.2, 800) # px, py, pixelThreshold
102 frameNum += 1 104 frameNum += 1
103 105
104 for obj in objects: 106 for obj in objects:
105 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = params.minSpeedEquiprobable, speedProbabilities = speedProbabilities) 107 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = params.minSpeedEquiprobable, speedProbabilities = speedProbabilities)
108 pastObjects.append(obj)
109 print('Saving user types')
110 storage.setRoadUserTypes(params.databaseFilename, pastObjects)