Mercurial Hosting > traffic-intelligence
comparison scripts/classify-objects.py @ 962:64259b9885bf
verbose option to print classification information (more to add)
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Mon, 06 Nov 2017 21:25:41 -0500 |
parents | 053484e08947 |
children | e8eabef7857c |
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961:ec1682ed999f | 962:64259b9885bf |
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16 parser.add_argument('-i', dest = 'videoFilename', help = 'name of the video file (overrides the configuration file)') | 16 parser.add_argument('-i', dest = 'videoFilename', help = 'name of the video file (overrides the configuration file)') |
17 parser.add_argument('-n', dest = 'nObjects', help = 'number of objects to classify', type = int, default = None) | 17 parser.add_argument('-n', dest = 'nObjects', help = 'number of objects to classify', 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('--start-frame0', dest = 'startFrame0', help = 'starts with first frame for videos with index problem where frames cannot be reached', action = 'store_true') |
19 parser.add_argument('--plot-speed-distributions', dest = 'plotSpeedDistribution', help = 'simply plots the distributions used for each user type', action = 'store_true') | 19 parser.add_argument('--plot-speed-distributions', dest = 'plotSpeedDistribution', help = 'simply plots the distributions used for each user type', action = 'store_true') |
20 parser.add_argument('--max-speed-distribution-plot', dest = 'maxSpeedDistributionPlot', help = 'if plotting the user distributions, the maximum speed to display (km/h)', type = float, default = 50.) | 20 parser.add_argument('--max-speed-distribution-plot', dest = 'maxSpeedDistributionPlot', help = 'if plotting the user distributions, the maximum speed to display (km/h)', type = float, default = 50.) |
21 parser.add_argument('--verbose', dest = 'verbose', help = 'verbose information', action = 'store_true') | |
21 | 22 |
22 args = parser.parse_args() | 23 args = parser.parse_args() |
23 params, videoFilename, databaseFilename, invHomography, intrinsicCameraMatrix, distortionCoefficients, undistortedImageMultiplication, undistort, firstFrameNum = storage.processVideoArguments(args) | 24 params, videoFilename, databaseFilename, invHomography, intrinsicCameraMatrix, distortionCoefficients, undistortedImageMultiplication, undistort, firstFrameNum = storage.processVideoArguments(args) |
24 classifierParams = storage.ClassifierParameters(params.classifierFilename) | 25 classifierParams = storage.ClassifierParameters(params.classifierFilename) |
25 classifierParams.convertToFrames(params.videoFrameRate, 3.6) # conversion from km/h to m/frame | 26 classifierParams.convertToFrames(params.videoFrameRate, 3.6) # conversion from km/h to m/frame |
109 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = classifierParams.minSpeedEquiprobable, speedProbabilities = speedProbabilities, maxPercentUnknown = classifierParams.maxPercentUnknown) | 110 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = classifierParams.minSpeedEquiprobable, speedProbabilities = speedProbabilities, maxPercentUnknown = classifierParams.maxPercentUnknown) |
110 pastObjects.append(obj) | 111 pastObjects.append(obj) |
111 currentObjects.remove(obj) | 112 currentObjects.remove(obj) |
112 else: | 113 else: |
113 obj.classifyUserTypeHoGSVMAtInstant(img, frameNum, width, height, classifierParams.percentIncreaseCrop, classifierParams.percentIncreaseCrop, classifierParams.minNPixels, classifierParams.hogRescaleSize, classifierParams.hogNOrientations, classifierParams.hogNPixelsPerCell, classifierParams.hogNCellsPerBlock, classifierParams.hogBlockNorm) | 114 obj.classifyUserTypeHoGSVMAtInstant(img, frameNum, width, height, classifierParams.percentIncreaseCrop, classifierParams.percentIncreaseCrop, classifierParams.minNPixels, classifierParams.hogRescaleSize, classifierParams.hogNOrientations, classifierParams.hogNPixelsPerCell, classifierParams.hogNCellsPerBlock, classifierParams.hogBlockNorm) |
115 if args.verbose: | |
116 print('obj {}@{}: {}'.format(obj.getNum(), frameNum, moving.userTypeNames[obj.userTypes[frameNum]])) | |
114 frameNum += 1 | 117 frameNum += 1 |
115 | 118 |
116 for obj in currentObjects: | 119 for obj in currentObjects: |
117 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = classifierParams.minSpeedEquiprobable, speedProbabilities = speedProbabilities, maxPercentUnknown = classifierParams.maxPercentUnknown) | 120 obj.classifyUserTypeHoGSVM(minSpeedEquiprobable = classifierParams.minSpeedEquiprobable, speedProbabilities = speedProbabilities, maxPercentUnknown = classifierParams.maxPercentUnknown) |
118 pastObjects.append(obj) | 121 pastObjects.append(obj) |