def main(argv):
app = basewindow.makeApp()
parser = OptionParser()
parser.add_option("--model",
dest="model_fname",
help="CRF Filename",
metavar="FILE")
parser.add_option("--training", dest="training_fname")
parser.add_option("--testing", dest="testing_fname")
(options, args) = parser.parse_args()
cf = CostFnCrf(options.model_fname)
training = cPickle.load(open(options.training_fname))
testing = cPickle.load(open(options.testing_fname))
describer = Describer(training, cf)
wnd = MainWindow(describer)
wnd.show()
testing_examples = [
ex for ex in testing.observations if ex.sdcs[0].type == "PATH"
]
ex = testing_examples[1]
path_esdc = ex.sdcs[0]
test_grounding = ex.annotation.getGroundings(path_esdc)[0]
wnd.describe(test_grounding)
app.exec_()
def main():
argv = sys.argv
start = time.time()
laser_fname = argv[1]
image_dir = argv[2]
model_fname = argv[3]
region_fname = argv[4]
map_fname = argv[5]
lf = logfile_du(laser_fname, image_dir)
m4du = cPickle.load(open(model_fname, 'r'))
end = time.time()
m4du.initialize()
print "tags"
gtruth_tf = tag_file(region_fname, map_fname)
me = model_evaluator(m4du, gtruth_tf, "d8")
app = basewindow.makeApp()
sentence = '''Go through the double doors and past the
lobby. Go into a lounge with some couches. Enjoy the nice
view. Go past the spiral staircase. Continue towards the
hallway with the cubby holes. But don't go down that
hallway. Instead take a right into the kitchen.'''
sentence = "Go through the double doors and past the lobby."
wnd = MainWindow(me, sentence, "R9", lf)
wnd.setWindowTitle(model_fname)
wnd.show()
retval = app.exec_()
def initialize():
global app
global cfb
if app != None:
return
app = basewindow.makeApp()
state, am = waverly_state_truck()
if cfb and state == cfb.state:
return
tp = nodeSearch.BeamSearch(CostFnCrf.from_mallet(
"%s/tools/crf_training/models/crf_discrete_forklift_1.5.pck" %
SLU_HOME),
useRrt=False)
cfb = costFunctionBrowser.MainWindow([10, 40, 10, 40], tp, show_gui=False)
print 'updating state'
cfb.setState(state)
#parameters
cfb.beamWidthBox.setValue(2)
cfb.seqBeamWidthBox.setValue(10)
cfb.searchDepthBox.setValue(3)
cfb.selectEsdcExtractor()
print 'starting tests'
def main(argv):
print "loading model"
model_fname = argv[1]
#server = Server(None)
m4du = dir_util.load(model_fname)
app = basewindow.makeApp()
wnd = MainWindow(m4du)
wnd.show()
mb_wnd = modelBrowser.MainWindow(m4du)
mb_wnd.setWindowTitle(model_fname)
print "--------------loading server---------------"
server = Server(wnd, mb_wnd)
socket = QSocketNotifier(server.socketFileno, QSocketNotifier.Read)
mb_wnd.connect(socket, SIGNAL("activated(int)"), server.handleRequest)
mb_wnd.startingSlocTable.selectRow(42)
print "done"
mb_wnd.show()
retval = app.exec_()
def main():
app = basewindow.makeApp()
dialog = Dialog()
username = ""
while username == "":
if dialog.exec_() == QDialog.Accepted:
username = dialog.username
assignment = dialog.assignmentDirectory
fullDirectory = "gremclass/%s" % (username)
assignmentDirectory = "%s/%s" % (fullDirectory, assignment)
if not os.path.exists(assignmentDirectory):
if not os.path.exists(fullDirectory):
os.makedirs(fullDirectory)
makeAssignment(assignmentDirectory,
"../data/directions/direction_floor_3/log4_s3.tag",
"../data/directions/direction_floor_3/log4_s3.cmf",
spatialRelationClassifier.engineMap)
wnd = pathAnnotatorWindow.MainWindow(assignmentDirectory)
wnd.show()
retval = app.exec_()
def main():
app = basewindow.makeApp()
rospy.init_node('animator', anonymous=True)
wnd = MainWindow()
wnd.show()
app.exec_()
def main():
app = basewindow.makeApp()
#nd = MainWindow("scratch.assignment/")
wnd = MainWindow("data/floor3.examples/annotations.part3/")
wnd.show()
retval = app.exec_()
def main():
if (len(argv) == 3):
app = basewindow.makeApp()
print "loading"
#mapPartitioner = cPickle.load(open('../data/directions/direction_floor_8/partitions/d8_small.pck'))
mapPartitioner = cPickle.load(
open('../data/directions/direction_floor_8/partitions/d8_small.pck'
))
print "loaded", mapPartitioner
mapPartitioner.skel.map_filename = argv[2]
mapPartitioner.tf.map_filename = argv[2]
polygons = mapPartitioner.tf.as_slimd_polygons()
sloc = (20, 25)
eloc = (21, 38)
X, Y = mapPartitioner.skel.compute_path(sloc, eloc)
points = [(x, y) for x, y in zip(X, Y)]
graphMap(mapPartitioner.skel, points)
#mskel = mapPartitioner.skel
#get path
#wnd = pathDescriberWindow.makeWindow(polygons, [points])
#wnd.show()
print "firstPoint", points[0]
#points = [p for p in zip(X,Y)]
#wnd.generateInstructions(points)
retval = app.exec_()
else:
print "usage:\n\t python skel_shortest_path.py skeleton.pck map.cmf.gz"
def main(argv):
app = basewindow.makeApp()
parser = OptionParser()
parser.add_option("--model-filename",
dest="model_fname",
help="CRF Filename",
metavar="FILE")
parser.add_option("--original-commands",
dest="original_commands_fname",
metavar="FILE")
(options, args) = parser.parse_args()
print "loading model at:", options.model_fname
from sys import argv
wnd = MainWindow(options.model_fname)
print "loading"
wnd.load(argv[1], argv[2], options.original_commands_fname)
print "showing"
wnd.show()
app.exec_()
def main():
app = basewindow.makeApp()
fname = "data/matthias/transcriptions.xls"
wnd = MainWindow(fname)
wnd.openFile("out.xml")
wnd.show()
retval = app.exec_()
def main():
basewindow.batch_mode = True
app = basewindow.makeApp()
wnd = MainWindow()
wnd.load("data/")
wnd.show()
app.exec_()
def main():
tagFile = tag_util.tag_file("../data/directions/direction_floor_3/log4_s3.tag", "../data/directions/direction_floor_3/log4_s3.cmf")
polygons = tagFile.as_slimd_polygons()
app = basewindow.makeApp()
wnd = pathDescriberWindow.makeWindow(polygons, [[(43, 14), (40, 26)]])
wnd.show()
print len(polygons)
retval = app.exec_()
def main():
app = basewindow.makeApp()
wnd = MainWindow()
wnd.setWindowTitle("Spatial Relation Classifier Viewer")
wnd.show()
#wnd.open("data/motion_verbs/follow/follow1.pck")
app.exec_()
def main():
app = basewindow.makeApp()
rospy.init_node('animator_gui', anonymous=True)
wnd = MainWindow()
wnd.show()
print rospy.is_shutdown()
app.exec_()
def main():
app = basewindow.makeApp()
model_fname = sys.argv[1]
region_tagfile = sys.argv[2]
map_fname = sys.argv[3]
m4du = load(model_fname)
wnd = MainWindow(m4du, region_tagfile, map_fname)
wnd.show()
app.exec_()
def main(argv):
import time
start = time.time()
m4du = cPickle.load(open(argv[1], 'r'))
m4du.initialize()
end = time.time()
print "took %.2f seconds" % (end - start)
app = basewindow.makeApp()
wnd = MainWindow(m4du)
wnd.show()
retval = app.exec_()
def main():
from sys import argv
import cPickle
import basewindow
model_file = argv[1]
m4du = cPickle.load(open(model_file, 'r'))
m4du.initialize()
app = basewindow.makeApp()
wnd = MainWindow(m4du)
wnd.setWindowTitle(model_file)
wnd.show()
retval = app.exec_()
def main():
app = basewindow.makeApp()
srEngineMap = dict([(key, spatialRelationClassifier.engineMap[key])
for key in [
"across", "through", "past", "around", "to", "out",
"towards", "away from", "until"
]])
verbEngineMap = dict([(key, spatialRelationClassifier.engineMap[key])
for key in ["turnLeft", "turnRight", "straight"]])
wnd = MainWindow(verbEngineMap, srEngineMap)
wnd.show()
retval = app.exec_()
def main():
app = basewindow.makeApp()
data = []
for session in [
"data/floor3.examples/part1.pck",
"data/floor3.examples/part2.pck",
"data/floor3.examples/part3.pck",
]:
stuff = cPickle.load(open(session))
data.extend(stuff)
wnd = MainWindow(data)
wnd.show()
app.exec_()
def main():
from sys import argv
app = basewindow.makeApp()
map_fname = argv[1]
tag_fname = argv[2]
#tag_fname = "%s/data/directions/direction_hsp/tags/objects.tag" % TKLIB_HOME
#map_fname = "%s/data/directions/direction_hsp/hsp.cmf" % TKLIB_HOME
wnd = MainWindow(tag_fname, map_fname)
wnd.setWindowTitle("Track Browser")
wnd.show()
app.exec_()
def main():
from sys import argv
app = basewindow.makeApp()
map_fn = argv[1]
gtruth_tag_fn = argv[2]
skeleton_fn = argv[3]
tagFile = loadTagFile(argv[2], argv[1])
skeleton = cPickle.load(open(skeleton_fn, 'r'))
wnd = MainWindow(tagFile, skeleton)
wnd.setWindowTitle("Spatial Motion Verbs Pacman")
wnd.show()
#wnd.open("data/motion_verbs/follow/follow1.pck")
app.exec_()
def main(argv):
app = basewindow.makeApp()
from sys import argv
model_fname = argv[1]
dataset_fname = argv[2]
crf = CRFMallet.load(model_fname)
dataset = pickle_util.load(dataset_fname)
wnd = MainWindow()
wnd.load(crf, dataset, title=dataset_fname)
wnd.show()
app.exec_()
def main(args):
app = basewindow.makeApp()
parser = argparse.ArgumentParser()
parser.add_argument("--model-filename",
dest="model_fname",
help="Model Filename",
metavar="FILE")
args = parser.parse_args()
cost_function = CostFnCrf.from_mallet(args.model_fname)
task_planner = nodeSearch.BeamSearch(cost_function)
wnd = MainWindow(task_planner)
wnd.show()
app.exec_()
def main():
from sys import argv
app = basewindow.makeApp()
track_fname = "%s/pytools/video_retrieval/3rdParty/cogmac_slimd2/slimd2/data/worldtracks_2c_hsp_01-01-07_combined.db" % TKLIB_HOME
tag_fname = "%s/data/directions/direction_hsp/tags/objects.tag" % TKLIB_HOME
map_fname = "%s/data/directions/direction_hsp/hsp.cmf" % TKLIB_HOME
wnd = MainWindow(tag_fname, map_fname)
wnd.setWindowTitle("Track Browser")
tracks = read_tracks.readTracks(track_fname)
wnd.load(tracks)
wnd.show()
app.exec_()
def main():
from sys import argv
import cPickle
import basewindow
app = basewindow.makeApp()
map_fn = argv[1]
gtruth_tag_fn = argv[2]
cluster_fn = argv[3]
assignment_fn = argv[4]
tagFile = tag_util.tag_file(gtruth_tag_fn, map_fn)
tagFile.get_map()
tagFile.get_tag_names()
skeleton = cPickle.load(open(cluster_fn, 'r'))
wnd = MainWindow(tagFile, skeleton, isEditable=True)
wnd.show()
humanAssignment = Assignment.load(
"%s/nlp/data/aaai_2010_smv/stefie10/assignment1.1.yaml" % TKLIB_HOME,
tagFile, skeleton)
engine = follow.Engine()
table = trainer_pacman.makeTable(engine, [humanAssignment])
subsetTable = trainer_pacman.makeSubsetExamples(engine, table)
entries = []
for i, ex in enumerate(subsetTable):
print "making entry", i
entry = VerbAssignmentEntry(ex["entry"].value.verb,
ex["entry"].value.command,
tagFile,
skeleton,
situation=ex["situation"].value)
entries.append(entry)
if i > 10:
break
wnd.load(Assignment(entries, tagFile, skeleton))
retval = app.exec_()
def main(argv):
feature_extractors = dict(
(x.__name__, x) for x in [GGGFeatures, EsdcFeatures])
parser = OptionParser()
parser.add_option("--feature-extractor",
dest="feature_extractor",
help="Feature extractor class name")
(options, args) = parser.parse_args()
cls = feature_extractors.get(options.feature_extractor, None)
feature_extractor = cls() if cls != None else None
app = basewindow.makeApp()
wnd = MainWindow(feature_extractor)
corpusFname = argv[1]
wnd.load(corpusFname)
wnd.show()
app.exec_()
def main():
from optparse import OptionParser
app = basewindow.makeApp()
parser = OptionParser()
parser.add_option("--corpus-filename",dest="corpus_fname", metavar="FILE",
action="append")
parser.add_option("--mturk-corpus-filename",dest="mturk_corpus_fname",
metavar="FILE")
parser.add_option("--state-type",dest="state_type",
metavar="FILE")
parser.add_option("--automatically_ground_children", dest="ground_children",
action="store_true", metavar="BOOL",
help="Whenever an ESDC is grounded, ground all children from its figure field to the same object")
(options, args) = parser.parse_args()
wnd = MainWindow(options.mturk_corpus_fname, options.state_type, options.ground_children)
wnd.show()
wnd.load(options.corpus_fname)
app.exec_()
def main(argv):
model_fname = argv[1]
corpus_fname = argv[2]
m4du = dir_util.load(argv[1])
print "tags"
app = basewindow.makeApp()
wnd = MainWindow(m4du, corpus_fname, addFigureToMainWindow=True)
wnd.setWindowTitle(model_fname)
wnd.show()
#wnd.followDirections()
#wnd.load_ranges()
#wnd.draw_viewpoint_paths()
#self.figure.gca().show()
#wnd.plot([4, 12])
app.exec_()
def main(argv):
parser = OptionParser()
parser.add_option("--model-filename",dest="model_fname",
help="CRF Filename", metavar="FILE")
parser.add_option("--rndf-filename",dest="rndf_fname",
help="RNDF Filename", metavar="FILE")
parser.add_option("--skeleton-filename",dest="skel_fname",
help="Skeleton Filename", metavar="FILE")
parser.add_option("--use-rrt",dest="use_rrt",
help="Use RRT?", metavar="FILE")
(options, args) = parser.parse_args()
print "loading model at:", options.model_fname
app = basewindow.makeApp()
wnd = MainWindow(options.rndf_fname, options.skel_fname, options.model_fname)
wnd.show()
app.exec_()
def main(argv):
app = basewindow.makeApp()
from optparse import OptionParser
parser = OptionParser()
parser.add_option("--training_filename",
dest="training_fname",
help="Training Filename",
metavar="FILE")
(options, args) = parser.parse_args()
annotations = annotationIo.load(options.training_fname)
annotation = annotations[0]
state, esdc_to_ggg = annotation_to_ggg_map(annotation)
ggg = esdc_to_ggg[annotation.esdcs[0]]
wnd = MainWindow()
wnd.show()
wnd.load(ggg)
app.exec_()
def main(argv):
print "loading model"
model_file = argv[1]
output_file = argv[2]
m4du = cPickle.load(open(model_file, 'r'))
print "initializing"
m4du.initialize()
print "tags"
#tf = tag_file(argv[2], argv[3])
ofile = cPickle.load(open(output_file, 'r'))
app = basewindow.makeApp()
wnd = MainWindow(m4du, ofile)
wnd.setWindowTitle(
"Model %s, output %s" %
(os.path.basename(model_file), os.path.basename(output_file)))
wnd.browser.setWindowTitle(model_file)
wnd.show()
retval = app.exec_()
def main(argv):
app = basewindow.makeApp()
wnd= MainWindow()
wnd.show()
app.exec_()
