Mercurial > hg > nsaunier > traffic-intelligence

comparison scripts/nomad/site-parameters-optimization.py @ 1219:8a626226793e

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update where optimization uses either nomad-parameter file depending on optimizing 1 or 2 steps
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Mon, 19 Jun 2023 17:09:56 -0400
parents 606817bc31e8
children 5a207c838323
comparison
equal deleted inserted replaced
1218:1f0b1fc172f8 1219:8a626226793e
5 from trafficintelligence import storage, moving 5 from trafficintelligence import storage, moving
6 import subprocess 6 import subprocess
7 import numpy as np 7 import numpy as np
8 8
9 9
10 def loadParametersStartProcess(filename): 10 def loadParametersStartProcess(filename, intersections):
11 # load initial parameters from x.txt 11 # load initial parameters from x.txt
12 f = open(filename, 'r+') 12 f = open(filename, 'r+')
13 l = f.readline() 13 l = f.readline()
14 x = [s for s in l.strip().split(" ")] 14 x = [s for s in l.strip().split(" ")]
15 f.close() 15 f.close()
16 16
17 # create para-value list 17 # create para-value list
18 para = paraValueList(x) 18 para = paraValueList(x)
19 19
20 # run process including trackingfeature, groupfeature, load groundtruth, compute mota 20 # run process including trackingfeature, groupfeature, load groundtruth, compute mota
21 print(process(para, intersections, optimizeGroupingOnly)) 21 print(process(para, intersections))
22 22
23 def paraValueList(x): 23 def paraValueList(x):
24 #create para-value list 24 #create para-value list
25 #list of the 8 parameters and their values 25 #list of the 8 parameters and their values
26 pn = 8 26 p = 8*[None]
27 p = pn*[None]
28 p[0] = '--feature-quality' #]0.-0.4] 27 p[0] = '--feature-quality' #]0.-0.4]
29 p[1] = '--min-feature-distanceklt' #]0.-6] 28 p[1] = '--min-feature-distanceklt' #]0.-6]
30 p[2] = '--window-size' #[1-10]integer 29 p[2] = '--window-size' #[1-10]integer
31 p[3] = '--min-tracking-error' #[0.01-0.3] 30 p[3] = '--min-tracking-error' #[0.01-0.3]
32 p[4] = '--min-feature-time' #[2-100]integer 31 p[4] = '--min-feature-time' #[2-100]integer
33 p[5] = '--mm-connection-distance' #[0.5-100] 32 p[5] = '--mm-connection-distance' #[0.5-100]
34 p[6] = '--mm-segmentation-distance' #[1-100] ~mm-connection-distance / 2.5 33 p[6] = '--mm-segmentation-distance' #[1-100] ~mm-connection-distance / 2.5
35 p[7] = '--min-nfeatures-group' #[2-4] 34 p[7] = '--min-nfeatures-group' #[2-4]
36 35
37 para = [] 36 para = []
38 for n in range(pn): 37 if len(x) == 4:
39 para = para + [p[n],x[n]] 38 for n in range(4):
39 para = para + [p[4+n],x[n]]
40 else:
41 for n in range(len(x)):
42 para = para + [p[n],x[n]]
40 43
41 return para 44 return para
42 45
43 def process(para, intersections, optimizeGroupingOnly): 46 def process(para, intersections):
44 Mota = [] 47 Mota = []
45 gtDatabaseaAbsPaths = [] 48 gtDatabaseaAbsPaths = []
46 configFileAbsPaths = [] 49 configFileAbsPaths = []
47 50
48 cwd = os.getcwd() 51 cwd = os.getcwd()
56 configFilename = os.path.abspath(intersectionAbsPath + '/' + glob.glob('*.cfg', recursive=True)[0]) 59 configFilename = os.path.abspath(intersectionAbsPath + '/' + glob.glob('*.cfg', recursive=True)[0])
57 configFileAbsPaths.extend([configFilename]*len(newPaths)) 60 configFileAbsPaths.extend([configFilename]*len(newPaths))
58 os.chdir(cwd) 61 os.chdir(cwd)
59 for gtDatabaseAbsPath, configFileAbsPath in zip(gtDatabaseaAbsPaths, configFileAbsPaths): 62 for gtDatabaseAbsPath, configFileAbsPath in zip(gtDatabaseaAbsPaths, configFileAbsPaths):
60 gtDatabaseBasename = gtDatabaseAbsPath[:-10] 63 gtDatabaseBasename = gtDatabaseAbsPath[:-10]
61 videoFilename = gtDatabaseBasename + ".MP4" 64 videoFilename = gtDatabaseBasename + ".avi" # careful, it may be necessary to check video type / extension
65 if not os.path.exists(videoFilename):
66 print('Video file {} does not exist'.format(videoFilename))
62 databaseFilename = gtDatabaseBasename + ".sqlite" 67 databaseFilename = gtDatabaseBasename + ".sqlite"
63 gtDatabaseDirname = os.path.dirname(gtDatabaseAbsPath) 68 gtDatabaseDirname = os.path.dirname(gtDatabaseAbsPath)
64 homographyFilename = gtDatabaseDirname + "/homography.txt" 69 homographyFilename = gtDatabaseDirname + "/homography.txt"
65 maskFilename = gtDatabaseDirname + "/mask.png" 70 maskFilename = gtDatabaseDirname + "/mask.png"
66 # Skip feature tracking if the user specified to optimize only grouping parameters 71 # Skip feature tracking if the user specified to optimize only grouping parameters
67 if not optimizeGroupingOnly: 72 if len(para) > 8:
68 # Track features 73 # Track features
69 trackingFeature(para, configFileAbsPath, videoFilename, databaseFilename, homographyFilename, maskFilename) 74 trackingFeature(para, configFileAbsPath, videoFilename, databaseFilename, homographyFilename, maskFilename)
70 # Group features 75 # Group features
71 groupFeature(para, configFileAbsPath, videoFilename, databaseFilename, homographyFilename, maskFilename) 76 groupFeature(para, configFileAbsPath, videoFilename, databaseFilename, homographyFilename, maskFilename)
72 #load trajectory 77 #load trajectory
89 if os.path.exists(db): 94 if os.path.exists(db):
90 os.remove(db) 95 os.remove(db)
91 # trackingfeature command parameters 96 # trackingfeature command parameters
92 tf = ['feature-based-tracking', config, '--tf', '--video-filename', video, '--database-filename', db, '--homography-filename', homo, '--mask-filename', mask] 97 tf = ['feature-based-tracking', config, '--tf', '--video-filename', video, '--database-filename', db, '--homography-filename', homo, '--mask-filename', mask]
93 # run in command line and print directly 98 # run in command line and print directly
94 subprocess.check_output(tf + para[0:10]) 99 subprocess.check_output(tf + para)
95 100
96 def groupFeature(para, config, video, db, homo, mask): 101 def groupFeature(para, config, video, db, homo, mask):
97 #remove previous grouping 102 #remove previous grouping
98 storage.deleteFromSqlite(db, 'object') 103 storage.deleteFromSqlite(db, 'object')
99 #groupfeature command parameters 104 #groupfeature command parameters
100 gf = ['feature-based-tracking', config, '--gf', '--video-filename', video, '--database-filename', db, '--homography-filename', homo, '--mask-filename', mask] 105 gf = ['feature-based-tracking', config, '--gf', '--video-filename', video, '--database-filename', db, '--homography-filename', homo, '--mask-filename', mask]
101 #run in command line and print directly 106 #run in command line and print directly
102 subprocess.check_output(gf + para[8:16]) # ['--min-feature-time', 'x', '--mm-connection-distance', 'x', '--mm-segmentation-distance', 'x', '--min-nfeatures-group', 'x'] 107 subprocess.check_output(gf + para) # ['--min-feature-time', 'x', '--mm-connection-distance', 'x', '--mm-segmentation-distance', 'x', '--min-nfeatures-group', 'x']
103
104 def computeMota(annotations, objects, Mota):
105 matchingDistance = 5
106 firstInstant = 0
107 lastInstant = 50000
108 return moving.computeClearMOT(annotations, objects, matchingDistance, firstInstant, lastInstant)[1]
109 108
110 109
111 if __name__ == "__main__": 110 if __name__ == "__main__":
112 # Load args that were given with select-arguments.py 111 # Load args that were given with select-arguments.py
113 with open('arguments.txt', 'r') as f: 112 # with open('arguments.txt', 'r') as f:
114 args = f.read().split('\n') 113 # args = f.read().split('\n')
115 intersections = args[0] 114 # intersections = args[0]
116 optimizeGroupingOnly = args[1] 115 # optimizeGroupingOnly = eval(args[1])
117 # Convert string representation of list into list 116 # intersections = eval(intersections)
118 intersections = eval(intersections) 117
118 # Just write the intersections to optimize here
119 intersections = ['../12-laurier']
119 120
120 loadParametersStartProcess(sys.argv[1]) 121 loadParametersStartProcess(sys.argv[1], intersections)
121 sys.exit(0) 122 sys.exit(0)
122