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_()