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recognize_3d.py File Reference
Go to the source code of this file.
Classes
class
hai_sandbox.recognize_3d.DataScale
class
hai_sandbox.recognize_3d.FiducialPicker
class
hai_sandbox.recognize_3d.ImagePublisher
class
hai_sandbox.recognize_3d.InterestPointDataset
class
hai_sandbox.recognize_3d.NarrowTextureFeatureExtractor
class
hai_sandbox.recognize_3d.PCAIntensities
class
hai_sandbox.recognize_3d.Recognize3DParam
class
hai_sandbox.recognize_3d.ScanLabeler
class
hai_sandbox.recognize_3d.SVM
class
hai_sandbox.recognize_3d.SVMPCA_ActiveLearner
Namespaces
namespace
hai_sandbox::recognize_3d
Functions
def
hai_sandbox::recognize_3d.confusion_matrix
def
hai_sandbox::recognize_3d.dataset_to_libsvm
def
hai_sandbox::recognize_3d.draw_dataset
def
hai_sandbox::recognize_3d.draw_labeled_points
def
hai_sandbox::recognize_3d.draw_points
def
hai_sandbox::recognize_3d.find_max_in_density
def
hai_sandbox::recognize_3d.insert_folder_name
def
hai_sandbox::recognize_3d.instance_to_image
def
hai_sandbox::recognize_3d.instances_to_image
def
hai_sandbox::recognize_3d.inverse_indices
def
hai_sandbox::recognize_3d.load_data_from_file2
def
hai_sandbox::recognize_3d.make_point_exclusion_test_set
def
hai_sandbox::recognize_3d.preprocess_data_in_dir
def
hai_sandbox::recognize_3d.preprocess_scan_extract_features
Variables
tuple
hai_sandbox::recognize_3d.current_scan_pred
= InterestPointDataset(xs, results, locs2d, locs3d,
None
)
tuple
hai_sandbox::recognize_3d.dataset
=
ut.load_pickle
(
fname
)
string
hai_sandbox::recognize_3d.dest
= '
mode
'
list
hai_sandbox::recognize_3d.dset
= locations['
data
']
tuple
hai_sandbox::recognize_3d.fname
= raw_input('pick
a
file
name
')
tuple
hai_sandbox::recognize_3d.fp
= FiducialPicker(
args
[0])
tuple
hai_sandbox::recognize_3d.fpfh
= rospy.ServiceProxy('fpfh', fsrv.FPFHCalc)
string
hai_sandbox::recognize_3d.help
= 'fiducialpicker, preprocess, or
label
'
tuple
hai_sandbox::recognize_3d.histogram
= np.matrix(res.hist.histograms)
tuple
hai_sandbox::recognize_3d.img
= cv.CloneMat(cdisp['cv'])
tuple
hai_sandbox::recognize_3d.ip
= ImagePublisher('active_learn')
list
hai_sandbox::recognize_3d.keys
= locations['
data
']
tuple
hai_sandbox::recognize_3d.kfe
= KinectFeatureExtractor()
tuple
hai_sandbox::recognize_3d.learner
= SVMPCA_ActiveLearner(use_pca=
True
)
tuple
hai_sandbox::recognize_3d.locations
=
ut.load_pickle
(opt.locations)
hai_sandbox::recognize_3d.mode
=
opt.mode
tuple
hai_sandbox::recognize_3d.neg_to_pos_ratio
= float(nneg)
int
hai_sandbox::recognize_3d.NEGATIVE
= 0
tuple
hai_sandbox::recognize_3d.nneg
=
np.sum
(
dataset.outputs
== NEGATIVE)
tuple
hai_sandbox::recognize_3d.npos
=
np.sum
(
dataset.outputs
== POSITIVE)
tuple
hai_sandbox::recognize_3d.p
= optparse.OptionParser()
tuple
hai_sandbox::recognize_3d.picked_i
= int(raw_input('pick
a
key
to use'))
tuple
hai_sandbox::recognize_3d.points3d
= np.matrix(res.hist.points3d)
float
hai_sandbox::recognize_3d.POSITIVE
= 1.0
tuple
hai_sandbox::recognize_3d.req
= fsrv.FPFHCalcRequest()
tuple
hai_sandbox::recognize_3d.res
= fpfh(
req
)
tuple
hai_sandbox::recognize_3d.results
= np.matrix(learner.classify(sdset))
tuple
hai_sandbox::recognize_3d.s
list
hai_sandbox::recognize_3d.seed_dset
= keys[
i
]
hai_sandbox::recognize_3d.trained
=
False
float
hai_sandbox::recognize_3d.UNLABELED
= 2.0
string
hai_sandbox::recognize_3d.weight_balance
= ' -w0 1 -w1 %.2f'
hai_sandbox
Author(s): Hai Nguyen
autogenerated on Wed Nov 27 2013 11:46:56