--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/scripts/nomad/site-parameters-optimization.py	Tue Jun 21 17:06:06 2022 -0400
@@ -0,0 +1,117 @@
+#! /usr/bin/env python3
+import os
+import sys
+import glob
+from trafficintelligence import storage, moving
+import subprocess
+import numpy as np
+
+
+def loadParametersStartProcess(filename):
+    # load initial parameters from x.txt
+    f = open(filename, 'r+')
+    l = f.readline()
+    x = [s for s in l.strip().split(" ")]
+    f.close()
+    
+    # create para-value list
+    para = paraValueList(x)
+    
+    # run process including trackingfeature, groupfeature, load groundtruth, compute mota
+    print(process(para, intersections, optimizeGroupingOnly))
+
+def paraValueList(x):
+    #create para-value list
+    #list of the 8 parameters and their values
+    pn = 8
+    p = pn*[None]
+    p[0] = '--feature-quality'             #]0.-0.4]
+    p[1] = '--min-feature-distanceklt'     #]0.-6]
+    p[2] = '--window-size'                 #[1-10]integer
+    p[3] = '--min-tracking-error'          #[0.01-0.3]
+    p[4] = '--min-feature-time'            #[2-100]integer
+    p[5] = '--mm-connection-distance'      #[0.5-100]
+    p[6] = '--mm-segmentation-distance'    #[1-100] ~mm-connection-distance / 2.5
+    p[7] = '--min-nfeatures-group'         #[2-4]
+    
+    para = []
+    for n in range(pn):
+        para = para + [p[n],x[n]]
+    
+    return para
+
+def process(para, intersections, optimizeGroupingOnly):
+    Mota = []
+    gtDatabaseaAbsPaths = []
+    configFileAbsPaths = []
+
+    cwd = os.getcwd()
+    # move to the location of the intersection
+    for intersectionPath in intersections:
+        intersectionAbsPath = os.path.abspath(intersectionPath)
+        os.chdir(intersectionAbsPath)
+        # iterate through all the subdirectories to find ground truth sqlite files
+        gtDatabaseaAbsPaths.extend([os.path.abspath(intersectionAbsPath + '/' + file) for file in glob.glob('**/*_gt.sqlite', recursive=True)])
+        configFileAbsPaths.append(os.path.abspath(intersectionAbsPath + '/' + glob.glob('*.cfg', recursive=True)[0]))
+        os.chdir(cwd)
+    for gtDatabaseAbsPath, configFileAbsPath in zip(gtDatabaseaAbsPaths, configFileAbsPaths):
+        gtDatabaseBasename = gtDatabaseAbsPath[:-10]
+        videoFilename = gtDatabaseBasename + ".MP4"
+        databaseFilename = gtDatabaseBasename + ".sqlite"
+        gtDatabaseDirname = os.path.dirname(gtDatabaseAbsPath)
+        homographyFilename = gtDatabaseDirname + "/homography.txt"
+        maskFilename = gtDatabaseDirname + "/mask.png"
+        # Skip feature tracking if the user specified to optimize only grouping parameters
+        if not optimizeGroupingOnly:
+            # Track features
+            trackingFeature(para, configFileAbsPath, videoFilename, databaseFilename, homographyFilename, maskFilename)
+        # Group features
+        groupFeature(para, configFileAbsPath, videoFilename, databaseFilename, homographyFilename, maskFilename)
+        #load trajectory
+        objects = storage.loadTrajectoriesFromSqlite(databaseFilename, 'object')
+        #load ground truth
+        annotations = storage.loadTrajectoriesFromSqlite(gtDatabaseAbsPath, 'object')
+        # Appending negative mota because nomad minimizes the output
+        Mota.append(-computeMota(annotations, objects, Mota))
+    
+    # Change to the previous directory
+    os.chdir(cwd)
+
+    return np.mean(Mota)
+
+def trackingFeature(para, config, video, db, homo, mask):
+    # remove previous tracking
+    if os.path.exists(db):
+        os.remove(db)
+    # trackingfeature command parameters
+    tf = ['feature-based-tracking', config, '--tf', '--video-filename', video, '--database-filename', db, '--homography-filename', homo, '--mask-filename', mask]
+    # run in command line and print directly
+    subprocess.check_output(tf + para[0:10])
+
+def groupFeature(para, config, video, db, homo, mask):
+    #remove previous grouping
+    storage.deleteFromSqlite(db, 'object')
+    #groupfeature command parameters
+    gf = ['feature-based-tracking', config, '--gf', '--video-filename', video, '--database-filename', db, '--homography-filename', homo, '--mask-filename', mask]
+    #run in command line and print directly
+    subprocess.check_output(gf + para[8:16])  # ['--min-feature-time', 'x', '--mm-connection-distance', 'x', '--mm-segmentation-distance', 'x', '--min-nfeatures-group', 'x']
+
+def computeMota(annotations, objects, Mota):
+    matchingDistance = 500
+    firstInstant = 0
+    lastInstant = 50000
+    return moving.computeClearMOT(annotations, objects, matchingDistance, firstInstant, lastInstant)[1]
+
+
+if __name__ == "__main__":
+    # Load args that were given with select-arguments.py
+    with open('arguments.txt', 'r') as f:
+        args = f.read().split('\n')
+        intersections = args[0]
+        optimizeGroupingOnly = args[1]
+        # Convert string representation of list into list
+        intersections = eval(intersections)
+
+    loadParametersStartProcess(sys.argv[1])
+    sys.exit(0)
+