Classes | |
class | DataScale |
class | FiducialPicker |
class | ImagePublisher |
class | InterestPointDataset |
class | NarrowTextureFeatureExtractor |
class | PCAIntensities |
class | Recognize3DParam |
class | ScanLabeler |
class | SVM |
class | SVMPCA_ActiveLearner |
Functions | |
def | confusion_matrix |
def | dataset_to_libsvm |
def | draw_dataset |
def | draw_labeled_points |
def | draw_points |
def | find_max_in_density |
def | insert_folder_name |
def | instance_to_image |
def | instances_to_image |
def | inverse_indices |
def | load_data_from_file2 |
def | make_point_exclusion_test_set |
def | preprocess_data_in_dir |
def | preprocess_scan_extract_features |
Variables | |
tuple | current_scan_pred = InterestPointDataset(xs, results, locs2d, locs3d, None) |
tuple | dataset = ut.load_pickle(fname) |
string | dest = 'mode' |
list | dset = locations['data'] |
tuple | fname = raw_input('pick a file name') |
tuple | fp = FiducialPicker(args[0]) |
tuple | fpfh = rospy.ServiceProxy('fpfh', fsrv.FPFHCalc) |
string | help = 'fiducialpicker, preprocess, or label' |
tuple | histogram = np.matrix(res.hist.histograms) |
tuple | img = cv.CloneMat(cdisp['cv']) |
tuple | ip = ImagePublisher('active_learn') |
list | keys = locations['data'] |
tuple | kfe = KinectFeatureExtractor() |
tuple | learner = SVMPCA_ActiveLearner(use_pca=True) |
tuple | locations = ut.load_pickle(opt.locations) |
mode = opt.mode | |
tuple | neg_to_pos_ratio = float(nneg) |
int | NEGATIVE = 0 |
tuple | nneg = np.sum(dataset.outputs == NEGATIVE) |
tuple | npos = np.sum(dataset.outputs == POSITIVE) |
tuple | p = optparse.OptionParser() |
tuple | picked_i = int(raw_input('pick a key to use')) |
tuple | points3d = np.matrix(res.hist.points3d) |
float | POSITIVE = 1.0 |
tuple | req = fsrv.FPFHCalcRequest() |
tuple | res = fpfh(req) |
tuple | results = np.matrix(learner.classify(sdset)) |
tuple | s |
list | seed_dset = keys[i] |
trained = False | |
float | UNLABELED = 2.0 |
string | weight_balance = ' -w0 1 -w1 %.2f' |
def hai_sandbox.recognize_3d.confusion_matrix | ( | true_labels, | |
predicted | |||
) |
Definition at line 44 of file recognize_3d.py.
def hai_sandbox.recognize_3d.dataset_to_libsvm | ( | dataset, | |
filename | |||
) |
Definition at line 125 of file recognize_3d.py.
def hai_sandbox.recognize_3d.draw_dataset | ( | dataset, | |
img, | |||
scale = 1. , |
|||
size = 2 , |
|||
scan_id = None |
|||
) |
Definition at line 153 of file recognize_3d.py.
def hai_sandbox.recognize_3d.draw_labeled_points | ( | image, | |
dataset, | |||
pos_color = [255 , |
|||
neg_color = [0 , |
|||
scale = 1. |
|||
) |
Definition at line 140 of file recognize_3d.py.
def hai_sandbox.recognize_3d.draw_points | ( | img, | |
img_pts, | |||
color, | |||
size = 1 , |
|||
thickness = -1 |
|||
) |
Definition at line 148 of file recognize_3d.py.
def hai_sandbox.recognize_3d.find_max_in_density | ( | locs2d | ) |
Definition at line 700 of file recognize_3d.py.
def hai_sandbox.recognize_3d.insert_folder_name | ( | apath, | |
folder_name | |||
) |
Definition at line 98 of file recognize_3d.py.
def hai_sandbox.recognize_3d.instance_to_image | ( | win_size, | |
instance, | |||
min_val, | |||
max_val | |||
) |
Definition at line 79 of file recognize_3d.py.
def hai_sandbox.recognize_3d.instances_to_image | ( | win_size, | |
instances, | |||
min_val, | |||
max_val | |||
) |
Definition at line 73 of file recognize_3d.py.
def hai_sandbox.recognize_3d.inverse_indices | ( | indices_exclude, | |
num_elements | |||
) |
Definition at line 170 of file recognize_3d.py.
def hai_sandbox.recognize_3d.load_data_from_file2 | ( | fname, | |
rec_param | |||
) |
Definition at line 102 of file recognize_3d.py.
def hai_sandbox.recognize_3d.make_point_exclusion_test_set | ( | training_dataset, | |
all_data_dir, | |||
ext | |||
) |
Definition at line 217 of file recognize_3d.py.
def hai_sandbox.recognize_3d.preprocess_data_in_dir | ( | dirname, | |
ext | |||
) |
Definition at line 205 of file recognize_3d.py.
def hai_sandbox.recognize_3d.preprocess_scan_extract_features | ( | raw_data_fname, | |
ext | |||
) |
Definition at line 176 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::current_scan_pred = InterestPointDataset(xs, results, locs2d, locs3d, None) |
Definition at line 2108 of file recognize_3d.py.
Definition at line 2085 of file recognize_3d.py.
string hai_sandbox::recognize_3d::dest = 'mode' |
Definition at line 1962 of file recognize_3d.py.
Definition at line 2010 of file recognize_3d.py.
list hai_sandbox::recognize_3d::fname = raw_input('pick a file name') |
Definition at line 2009 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::fp = FiducialPicker(args[0]) |
Definition at line 1983 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::fpfh = rospy.ServiceProxy('fpfh', fsrv.FPFHCalc) |
Definition at line 2054 of file recognize_3d.py.
string hai_sandbox::recognize_3d::help = 'fiducialpicker, preprocess, or label' |
Definition at line 1963 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::histogram = np.matrix(res.hist.histograms) |
Definition at line 2069 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::img = cv.CloneMat(cdisp['cv']) |
Definition at line 2111 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::ip = ImagePublisher('active_learn') |
Definition at line 2096 of file recognize_3d.py.
Definition at line 2004 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::kfe = KinectFeatureExtractor() |
Definition at line 2082 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::learner = SVMPCA_ActiveLearner(use_pca=True) |
Definition at line 2094 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::locations = ut.load_pickle(opt.locations) |
Definition at line 2003 of file recognize_3d.py.
Definition at line 1975 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::neg_to_pos_ratio = float(nneg) |
Definition at line 2092 of file recognize_3d.py.
Definition at line 42 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::nneg = np.sum(dataset.outputs == NEGATIVE) |
Definition at line 2086 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::npos = np.sum(dataset.outputs == POSITIVE) |
Definition at line 2087 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::p = optparse.OptionParser() |
Definition at line 1960 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::picked_i = int(raw_input('pick a key to use')) |
Definition at line 2007 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::points3d = np.matrix(res.hist.points3d) |
Definition at line 2070 of file recognize_3d.py.
float hai_sandbox::recognize_3d::POSITIVE = 1.0 |
Definition at line 41 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::req = fsrv.FPFHCalcRequest() |
Definition at line 2059 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::res = fpfh(req) |
Definition at line 2064 of file recognize_3d.py.
tuple hai_sandbox::recognize_3d::results = np.matrix(learner.classify(sdset)) |
Definition at line 2107 of file recognize_3d.py.
00001 ScanLabeler(args[0], ext='_features_df2_dict.pkl', scan_to_train_on=opt.train, 00002 seed_dset=opt.seed, features_to_use=opt.feature)
Definition at line 2020 of file recognize_3d.py.
Definition at line 2008 of file recognize_3d.py.
Definition at line 2095 of file recognize_3d.py.
float hai_sandbox::recognize_3d::UNLABELED = 2.0 |
Definition at line 40 of file recognize_3d.py.
string hai_sandbox::recognize_3d::weight_balance = ' -w0 1 -w1 %.2f' |
Definition at line 2093 of file recognize_3d.py.