def createAllFeaturesAndTargets():
filepath1 = dru.findPathForFile("AUGv2_trajectories-0830am-0900am.txt")
filepath2 = dru.findPathForFile("trajectories-peachtree.txt")
for testnum in [1, 1.1, 2]:
print("Creating features and targets for testnum:", testnum,
"and filepath:")
print(filepath1)
createFeaturesOnly(filepath1, testnum)
print("Done with testnum:", testnum)
for testnum in [3, 4]:
print("Creating features and targets for testnum:", testnum,
"and filepath:")
print(filepath2)
#manually move features for lankershim (not hard)
createFeaturesOnly(filepath2, testnum)
print("Done with testnum:", testnum)
def newCreateAllFeaturesAndTargets(testtypes,
filename_lank="trajectories-lankershim.txt",
filename_peach="trajectories-peachtree.txt",
save=True,
byIntersection=True):
filepath1 = dru.findPathForFile(filename_lank)
filepath2 = dru.findPathForFile(filename_peach)
if byIntersection:
save_path = os.path.join(c.PATH_TO_RESULTS, "ByIntersection")
else:
save_path = os.path.join(c.PATH_TO_RESULTS, "General")
check_make_paths([save_path])
for testnum in testtypes:
check_make_paths([os.path.join(save_path, testnum)])
allFeatures_normal, allFeatures_LSTM = getAllPossibleFeatures(
filepath1,
filepath2,
lanetype=bool(int(testnum[0])),
history=bool(int(testnum[1])),
histFs=[5, 10, 20, 30],
traffic=bool(int(testnum[2])),
numFramesToFind=20)
if not save: continue
if not byIntersection:
#AppendToEnd(intersectionID, features)
#save new
continue
for intersectionID in allFeatures_LSTM.keys():
#save features
check_make_paths(
[os.path.join(save_path, testnum, str(intersectionID))])
print(allFeatures_LSTM[intersectionID].shape)
np.savetxt(
os.path.join(save_path, testnum, str(intersectionID),
"featuresAndTargets"),
allFeatures_normal[intersectionID])
np.save(
os.path.join(save_path, testnum, str(intersectionID),
"LSTM_Formatted_featuresAndTargets"),
allFeatures_LSTM[intersectionID])
return allFeatures_normal, allFeatures_LSTM
def doGoalStuff(filepath, isCompressed, goalFile, fake=True, vels=False):
print(filepath)
filename = os.path.basename(filepath)
featurepath = dutil.findFeaturePath(filename)
print("constructing driver data...")
driver_data = dd.data(filepath, isCompressed, featurepath)
print("constructing goal dict...")
goal_dict = loadFeatureGoals(featurepath)
#will be a dict that maps dest_num: (avg_x, avg_y), goalNum
#key = (dest, destLane)
#d[key]=(x,y),n -- d[key][0]=(x,y) -- d[key][1] = goalNums
numGoals = len(list(goal_dict.keys())) - 1
print("constructing vidDIct")
if 'format_wrong' in goalFile:
wrongPath = dutil.findPathForFile(goalFile)
outfile = goalFile[0:(len(goalFile) -
len('_format_wrong.txt'))] + '.txt'
outpath = dutil.findPathForFile(outfile)
print("fixing format")
fixFormat(wrongPath, outpath, numGoals, driver_data)
if not vels:
vidDict = readGoalFile(outpath, numGoals, driver_data, False)
else:
vidDict, vidToVels = readGoalAndVelFile(outpath, numGoals,
driver_data, False)
else:
if not vels:
vidDict = readGoalFile(dutil.findPathForFile(goalFile), numGoals,
driver_data, fake)
else:
vidDict, vidToVels = readGoalAndVelFile(
dutil.findPathForFile(goalFile), numGoals, driver_data, fake)
#pick a random vehicle
#vid = driver_data.getRandVid()
#while not vid in vidDict.keys():
# vid = driver_data.getRandVid()
stopAt = 900
vids = [2, 5, 9, 14, 24]
'''stopAt = 899
print(vid)
fidFirst = list(vidDict[vid].keys())[0]
fidLast = 925#list(vidDict[vid].keys())[len(list(vidDict[vid].keys()))-1]
print(fidFirst, fidLast)
fids = [fidLast]
vidsToFids = {vid:fids}
for vid in vidsToFids.keys():'''
#for vid in vids:
for vid in vidDict.keys():
if not driver_data.hasVID(vid):
continue
stopAt = min(driver_data.lastFrameForVID(vid),
list(vidDict[vid].keys())[-1])
frames = []
ActX = []
ActY = []
PredX = []
PredY = []
#for fid in vidsToFids[vid]:
for fid in vidDict[vid].keys():
if not fid in (driver_data.getFrameDict()).keys():
continue
if vid not in (driver_data.getFrameDict())[fid]:
continue
if not vels:
processJustGoals(vid, fid, driver_data, vidDict, goal_dict,
stopAt)
else:
aX, aY, pX, pY = processVelsAndGoals(vid, fid, driver_data,
vidDict, goal_dict,
stopAt, vidToVels)
ActX.append(aX)
ActY.append(aY)
PredX.append(pX)
PredY.append(pY)
frames.append(fid)
plt.figure()
sns.set(style="darkgrid", font='Source Sans Pro')
sns.set_context("talk")
x = frames
XAline, = plt.plot(x, ActX, label='Actual X Vel')
YAline, = plt.plot(x, ActY, label='Actual Y Vel')
XPline, = plt.plot(x, PredX, '--', label='Pred X Vel')
YPline, = plt.plot(x, PredY, '--', label='Pred Y Vel')
title = "Pred and Actual Vel Comparison for Vehicle " + str(vid)
plt.title(title)
plt.legend(loc=0)
fileout = 'TrajComparisonVidX&Y' + str(vid) + '.png'
plt.savefig(plotFolder + fileout)
def main(arguments):
mode = argument_utils.expand_mode(arguments.mode)
if mode == "combine":
print("Combining trajectory files")
peachtree = doStuffForPeachtree()
lankershim = combineLankershimFiles()
return peachtree, lankershim
elif mode == "augment":
print("Augmenting raw trajectoris")
for filename in arguments.filenames:
print("Augmenting file:", filename)
du.augOrigData(dru.findPathForFile(filename))
elif mode == "featurize":
print("Featurizing augmented data")
filename_lank = "AUGv2_trajectories-lankershim.txt"
filename_peach = "AUGv2_trajectories-peachtree.txt"
testtypes = arguments.test_nums.split(",")
print("Test types to featurize for:", testtypes)
if arguments.featurize_type == "s":
print("saving featurzied general data")
newCreateAllFeaturesAndTargets(testtypes,
filename_lank,
filename_peach,
save=True,
byIntersection=False)
elif arguments.featurize_type == "i":
print("saving feautrized data by intersection")
newCreateAllFeaturesAndTargets(testtypes,
filename_lank,
filename_peach,
save=True)
elif arguments.featurize_type == "n":
print("not saving")
newCreateAllFeaturesAndTargets(testtypes,
filename_lank,
filename_peach,
save=False)
else:
print(
"invalid featurization option,", arguments.featurize_type,
"options are s (save general), i (save by intersection), n (dont save - not recommended)"
)
print("Done featurizing")
elif mode == "train":
model_arg = arguments.models
models = argument_utils.model_choices[model_arg]
testtypes = arguments.test_nums.split(",")
str_inters = arguments.test_intersections.split(",")
saving = True # TODO arg?
for test_inters in str_inters:
list_test = [int(i) for i in test_inters]
train_inters = sorted(
list(set([1, 2, 3, 4, 5, 6, 7, 8, 9]) - set(list_test)))
print("test inters:", list_test)
print("train inters:", train_inters)
intersections = ([int(i) for i in test_inters],
[int(i) for i in train_inters])
""" Deprecated
if arguments.mode == "tr":
if not saving:
print("indicated to train without saving, which is useless, will save")
print("training and saving")
saving = True
new_train(models, testtypes, intersections, saving)
elif arguments.mode == "te":
print("testing only")
graphs = input("Save graphs?")
new_test(models, testtypes, intersections, saving, graphs)
elif arguments.mode == "t":
"""
print("training and testing")
graphs = False # TODO arg?
new_train_and_test(models, testtypes, intersections, saving,
graphs)
elif mode == "evaluate":
print("evaluating.")
model_arg = arguments.models
models = argument_utils.model_choices[model_arg]
testtypes = arguments.test_nums.split(",")
teston = arguments.test_intersections
doEvalThings(models, testtypes, teston, arguments)
elif mode == "experimental":
print("doing crazy things probably")
#argv[2] == models (svm or dnn or lstms or nns (dnn and lstms) or all)
#argv[3] == testtypes - "," separated 000,001,010,011,100
#argv[4] == "," separated test intersections, assume train on all except test
#argv[5] == optional - subset, number of training examples - UNUSED
#argv[6] == s (save), 0 (dont save) - UNUSED, save all
model_arg = arguments.models
models = argument_utils.model_choices[model_arg]
testtypes = arguments.test_nums.split(",")
str_inters = arguments.test_intersections.split(",")
saving = True # TODO arg?
for test_inters in str_inters:
list_test = [int(i) for i in test_inters]
train_inters = sorted(
list(set([1, 2, 3, 4, 5, 6, 7, 8, 9]) - set(list_test)))
print("test inters:", list_test)
print("train inters:", train_inters)
intersections = ([int(i) for i in test_inters],
[int(i) for i in train_inters])
new_train_and_test(models,
testtypes,
intersections,
saving,
False,
exper=True)
else:
print(
"invalid argument:", arguments.mode,
"options are a - augment, f - featurize, tr - train, te - test, t - train and test"
)
def combineLankershimFiles(overlapStartFrame=10201, maxVid1=1438):
file1 = 'trajectories-0830am-0845am.txt'
file2 = 'trajectories-0845am-0900am.txt'
return futil.combineTrajFiles(dru.findPathForFile(file1),
dru.findPathForFile(file2))
def run():
filepath = dru.findPathForFile("AUGv2_trajectories-0830am-0900am.txt")
testID = "Test1"
test_folder = c.PATH_TO_RESULTS + str(testID)
doLSTM(filepath, testID, test_folder, numEpochs=2)