Functions — github.com/aistairc/PinSout

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Functions312 in github.com/aistairc/PinSout

⨍ Functions 312◇ Types & classes 10

↓ 1 callersFunctioneval_one_epoch

ops: dict mapping from string to tf ops

src/sem_seg/model/log_5cls/train.py:232

↓ 1 callersFunctioneval_one_epoch

ops: dict mapping from string to tf ops

src/sem_seg/model/log_6cls/train.py:229

↓ 1 callersMethodfind_side_point

Create the intersection of the bounding box and the plane Creates the intersection of the edges and planes of the top and bottom faces of

src/plane_ransac.py:743

↓ 1 callersMethodgetEnvelopEachSurface

(self, array, components)

src/citygml/PointCloud_To_CityGML.py:451

↓ 1 callersFunctionget_bn_decay

(batch)

src/sem_seg/train.py:117

↓ 1 callersFunctionget_bn_decay

(batch)

src/sem_seg/model/log6/train.py:113

↓ 1 callersFunctionget_bn_decay

(batch)

src/sem_seg/model/log_6cls_test16/train.py:114

↓ 1 callersFunctionget_bn_decay

(batch)

src/sem_seg/model/log6class/train.py:110

↓ 1 callersFunctionget_bn_decay

(batch)

src/sem_seg/model/log13class/train.py:113

↓ 1 callersFunctionget_bn_decay

(batch)

src/sem_seg/model/log_5cls/train.py:113

↓ 1 callersFunctionget_bn_decay

(batch)

src/sem_seg/model/log_6cls/train.py:110

↓ 1 callersMethodget_intersection_line

Finding the intersection points from each plane 1) Finding the intersection points between each planes 2) Sorting the

src/GeneratePointCloud_New.py:291

↓ 1 callersFunctionget_learning_rate

(batch)

src/sem_seg/train.py:106

↓ 1 callersFunctionget_learning_rate

(batch)

src/sem_seg/model/log6/train.py:103

↓ 1 callersFunctionget_learning_rate

(batch)

src/sem_seg/model/log_6cls_test16/train.py:104

↓ 1 callersFunctionget_learning_rate

(batch)

src/sem_seg/model/log6class/train.py:100

↓ 1 callersFunctionget_learning_rate

(batch)

src/sem_seg/model/log13class/train.py:103

↓ 1 callersFunctionget_learning_rate

(batch)

src/sem_seg/model/log_5cls/train.py:103

↓ 1 callersFunctionget_learning_rate

(batch)

src/sem_seg/model/log_6cls/train.py:100

↓ 1 callersMethodget_lineNormal

(self, line_normal)

src/plane_ransac.py:875

↓ 1 callersFunctionget_loss

pred: B,N,13 label: B,N

src/sem_seg/model/log6/model.py:60

↓ 1 callersFunctionget_loss

pred: B,N,13 label: B,N

src/sem_seg/model/log_6cls_test16/model.py:61

↓ 1 callersFunctionget_loss

pred: B,N,13 label: B,N

src/sem_seg/model/log6class/model.py:60

↓ 1 callersFunctionget_loss

pred: B,N,13 label: B,N

src/sem_seg/model/log13class/model.py:60

↓ 1 callersFunctionget_loss

pred: B,N,13 label: B,N

src/sem_seg/model/log_5cls/model.py:60

↓ 1 callersFunctionget_loss

pred: B,N,13 label: B,N

src/sem_seg/model/log_6cls/model.py:60

↓ 1 callersMethodget_plane_list

Planar data extraction from clustered cloud Execute the loop statement until the cloud size is greater than or equal to the clustered

src/GeneratePointCloud_New.py:31

↓ 1 callersFunctionget_pointRate

Making the ratio of points that is included in certain area Args: pointcloud: [x, y, z] point list normal_vector: Equation of pla

src/PointCloudUtils.py:104

↓ 1 callersMethodget_pointRate

(self, pointcloud, normal_vector, point1, point2)

src/plane_ransac.py:1191

↓ 1 callersFunctionget_range

Making the bouning box information Finding the Minimum and Maximum points of X, Y and Z and add the epsilon value Args: p

src/PointCloudUtils.py:315

↓ 1 callersFunctiongrid_subsampling_withoutRGB

PointCloud Voxelization Downsampling using voxelization Args: points: [x, y, z] data list colors: [r, g, b] data list

src/PointCloudUtils.py:335

↓ 1 callersFunctioninsert_batch

(data, label, last_batch=False)

src/sem_seg/gen_indoor3d_h5.py:45

↓ 1 callersMethodmakeRoom

(self)

src/citygml/PointCloud_To_CityGML.py:438

↓ 1 callersMethodmakeSurfaceGeometry

(self)

src/citygml/PointCloud_To_CityGML.py:564

↓ 1 callersMethodmake_line_info

Making the line information from each wall surface Align the intersections of each face and use the floor points to organize the data.

src/graph_cycle_new.py:20

↓ 1 callersMethodmake_room_ceiling

(self)

src/citygml/PointCloud_To_CityGML.py:570

↓ 1 callersMethodmake_room_floor

(self)

src/citygml/PointCloud_To_CityGML.py:598

↓ 1 callersMethodmake_room_info

(self)

src/GeneratePointCloud_New.py:388

↓ 1 callersMethodmake_room_wall

(self)

src/citygml/PointCloud_To_CityGML.py:622

↓ 1 callersMethodmake_side_line

Making side lines of plane Using the bounding box and plane data, create straight lines at both ends of the plane. Args:

src/plane_ransac.py:653

↓ 1 callersFunctionmake_straight

Making the straight information and finding the intersect point Generate straight line data using point_1 and point_2. Finding the in

src/PointCloudUtils.py:468

↓ 1 callersMethodmake_straight2

Making the straight information and finding the intersect point Generate straight line data using point_1 and point_2. Findin

src/plane_ransac.py:703

↓ 1 callersMethodmerged_clustered_wall

Merging the same plane equation data Merging planes that are parallel and within a certain distance Args:

src/GeneratePointCloud_New.py:237

↓ 1 callersFunctionplaceholder_inputs

(batch_size, num_point)

src/sem_seg/model/log6/model.py:12

↓ 1 callersFunctionplaceholder_inputs

(batch_size, num_point)

src/sem_seg/model/log_6cls_test16/model.py:12

↓ 1 callersFunctionplaceholder_inputs

(batch_size, num_point)

src/sem_seg/model/log6class/model.py:12

↓ 1 callersFunctionplaceholder_inputs

(batch_size, num_point)

src/sem_seg/model/log13class/model.py:12

↓ 1 callersFunctionplaceholder_inputs

(batch_size, num_point)

src/sem_seg/model/log_5cls/model.py:12

↓ 1 callersFunctionplaceholder_inputs

(batch_size, num_point)

src/sem_seg/model/log_6cls/model.py:12

↓ 1 callersMethodplane_cluster

Clustering the exported plane data Finding clustered points in the data extracted as planes. Args: cloud_data: Point

src/GeneratePointCloud_New.py:171

↓ 1 callersFunctionply_to_CityGML

Reading the .ply data starting the PinSout Dividing the entire PointCloud data into a certain size. Find the minimum value of each segmented

src/plyTo3Dmodel.py:119

↓ 1 callersFunctionpoint_cloud_three_views

input points Nx3 numpy array (+y is up direction). return an numpy array gray image of size 500x1500.

src/utils/pc_util.py:156

↓ 1 callersFunctionpoint_cloud_three_views_demo

Demo for draw_point_cloud function

src/utils/pc_util.py:171

↓ 1 callersFunctionpoint_cloud_to_volume

input is Nx3 points. output is vsize*vsize*vsize assumes points are in range [-radius, radius]

src/utils/pc_util.py:41

↓ 1 callersFunctionpyplot_draw_point_cloud

points is a Nx3 numpy array

src/utils/pc_util.py:183

↓ 1 callersFunctionread_ply

read XYZ point cloud from filename PLY file

src/utils/pc_util.py:77

↓ 1 callersFunctionroom2blocks_plus

room2block with input filename and RGB preprocessing.

src/sem_seg/indoor3d_util.py:203

↓ 1 callersFunctionroom2blocks_plus_normalized

room2block, with input filename and RGB preprocessing. for each block centralize XYZ, add normalized XYZ as 678 channels

src/sem_seg/indoor3d_util.py:228

↓ 1 callersFunctionroom2samples

Prepare whole room samples. Args: data: N x 6 numpy array, 012 are XYZ in meters, 345 are RGB in [0,1] assumes the data is s

src/sem_seg/indoor3d_util.py:268

↓ 1 callersFunctionroom2samples_plus_normalized

room2sample, with input filename and RGB preprocessing. for each block centralize XYZ, add normalized XYZ as 678 channels

src/sem_seg/indoor3d_util.py:305

↓ 1 callersFunctionsample_data

data is in N x ... we want to keep num_samplexC of them. if N > num_sample, we will randomly keep num_sample of them. if N <

src/sem_seg/indoor3d_util.py:107

↓ 1 callersFunctionsample_data_label

(data, label, num_sample)

src/sem_seg/indoor3d_util.py:125

↓ 1 callersFunctiontrain

()

src/sem_seg/train.py:128

↓ 1 callersFunctiontrain

()

src/sem_seg/model/log6/train.py:123

↓ 1 callersFunctiontrain

()

src/sem_seg/model/log_6cls_test16/train.py:124

↓ 1 callersFunctiontrain

()

src/sem_seg/model/log6class/train.py:120

↓ 1 callersFunctiontrain

()

src/sem_seg/model/log13class/train.py:123

↓ 1 callersFunctiontrain

()

src/sem_seg/model/log_5cls/train.py:123

↓ 1 callersFunctiontrain

()

src/sem_seg/model/log_6cls/train.py:120

↓ 1 callersFunctiontrain_one_epoch

ops: dict mapping from string to tf ops

src/sem_seg/train.py:200

↓ 1 callersFunctiontrain_one_epoch

ops: dict mapping from string to tf ops

src/sem_seg/model/log6/train.py:196

↓ 1 callersFunctiontrain_one_epoch

ops: dict mapping from string to tf ops

src/sem_seg/model/log_6cls_test16/train.py:197

↓ 1 callersFunctiontrain_one_epoch

ops: dict mapping from string to tf ops

src/sem_seg/model/log6class/train.py:193

↓ 1 callersFunctiontrain_one_epoch

ops: dict mapping from string to tf ops

src/sem_seg/model/log13class/train.py:196

↓ 1 callersFunctiontrain_one_epoch

ops: dict mapping from string to tf ops

src/sem_seg/model/log_5cls/train.py:196

↓ 1 callersFunctiontrain_one_epoch

ops: dict mapping from string to tf ops

src/sem_seg/model/log_6cls/train.py:193

↓ 1 callersMethodupdateBuildingEnvelop

(self)

src/citygml/PointCloud_To_CityGML.py:478

↓ 1 callersFunctionvolume_to_point_cloud

vol is occupancy grid (value = 0 or 1) of size vsize*vsize*vsize return Nx3 numpy array.

src/utils/pc_util.py:56

Method__contains__

(self, name)

src/utils/plyfile.py:339

Method__getitem__

(self, name)

src/utils/plyfile.py:342

Method__getitem__

(self, key)

src/utils/plyfile.py:701

Method__gt__

(self, other)

src/plane_ransac.py:1385

Method__init__

(self, surface_list)

src/graph_cycle_new.py:13

Method__init__

(self, distance_threshold, epsilon_value, segmented_wall, segmented_door, segmented_window)

src/GeneratePointCloud_New.py:22

Method__init__

(self, distance_threshold,epsilon_value, segmented_wall, segmented_door=[], segmented_window=[])

src/plane_ransac.py:25

Method__init__

(self, obj, *args)

src/plane_ransac.py:1379

Method__init__

(self, message, element=None, row=None, prop=None)

src/utils/plyfile.py:131

Method__init__

This is not part of the public interface. The preferred methods of obtaining PlyElement instances are PlyData.read (to read from

src/utils/plyfile.py:379

Method__init__

(self, name, val_dtype)

src/utils/plyfile.py:724

Method__init__

(self, name, len_dtype, val_dtype)

src/utils/plyfile.py:827

Method__init__

(self, ceiling_point, floor_point, wall_point, door_point, window_point)

src/citygml/PointCloud_To_CityGML.py:71

Method__iter__

(self)

src/utils/plyfile.py:333

Method__len__

(self)

src/utils/plyfile.py:336

Method__lt__

(self, other)

src/plane_ransac.py:1382

Method__repr__

(self)

src/utils/plyfile.py:148

Method__repr__

(self)

src/utils/plyfile.py:348

Method__repr__

(self)

src/utils/plyfile.py:710

Method__repr__

(self)

src/utils/plyfile.py:815

Method__repr__

(self)

src/utils/plyfile.py:912

Method__setitem__

(self, key, value)

src/utils/plyfile.py:704

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