plane_analysis.py File Reference

Go to the source code of this file.

Namespaces
namespace	plane_analysis
Functions
def	plane_analysis.approx_equals
def	plane_analysis.approx_subset
def	plane_analysis.approx_superset
def	plane_analysis.categorize
def	plane_analysis.false_negatives
def	plane_analysis.intersects
Variables
	plane_analysis.a = auto.area
list	plane_analysis.aa = autos[os[2]]
list	plane_analysis.ah = hands[os[1]]
list	plane_analysis.ai = autos[os[2]]
list	plane_analysis.autos = []
tuple	plane_analysis.autototal = sum([x.area for x in autos])
list	plane_analysis.categorized = [categorize(autos, hands, i) for i in range(len(autos))]
string	plane_analysis.coll_namespace = 'run{0}'
string	plane_analysis.db_name = 'semantic_world_model'
tuple	plane_analysis.fns = false_negatives(autos, hands)
list	plane_analysis.fps = [x for x in categorized if x[0] == 5]
tuple	plane_analysis.gcn = gcn_proxy()
tuple	plane_analysis.gcn_proxy
list	plane_analysis.hands = []
tuple	plane_analysis.handtotal = sum([x.area for x in hands])
tuple	plane_analysis.index = int(sys.argv[1])
list	plane_analysis.intersections = [x for x in categorized if x[0] == 4]
float	plane_analysis.it = 0.0
float	plane_analysis.min_area = 0.25
float	plane_analysis.mistake = 0.0
list	plane_analysis.names = []
list	plane_analysis.oversegs = [x for x in categorized if x[0] == 2]
list	plane_analysis.pairs = [(x, y) for (x, y) in zip(hands, names) if x.area >= min_area]
float	plane_analysis.pct = 0.75
tuple	plane_analysis.planes = list(planes_mc.query({}))
tuple	plane_analysis.planes_mc = mr.MessageCollection(db_name, coll_namespace+'_planes', Planes)
	plane_analysis.run_id = None
list	plane_analysis.truepos = [x for x in categorized if x[0] == 1]
list	plane_analysis.undersegs = [x for x in categorized if x[0] == 3]