Point Cloud Classification API

Module: mls.classify. This page documents 11 public functions with exact tool IDs, complete parameters, Parameters fields, and examples.

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Functions

classify_classify_by_csf

Classify point cloud by CSF algorithm

  • Exact tool ID:Classify_Classify_by_CSF
  • Recommended call:mls.classify.classify_classify_by_csf(...)
  • Alias:Classify_Classify_by_CSF
  • Required parameters:input_paths, Parameters

Parameters

Parameter Type Required Default Description
input_paths array Yes — Input point cloud file paths
Parameters object Yes — CSF classification parameters

Parameters fields

Field Type Required Default Description
rigidness integer No 1 Grid resolution
gridSize number No 1 Grid size
maxIterations integer No 500 Maximum iterations
gravity number No 0.4 Gravity
classifyThreshold number No 0.5 Classify threshold
doPostprocessing integer No 0 Do postprocessing
toClass integer No 2 Target class

Example

from gvscript import mls

params = mls.classify.classify_classify_by_csf_parameters()
params.rigidness = 1

result = mls.classify.classify_classify_by_csf(
    Parameters=params,
    input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)

classify_classify_by_attribute

Classify point cloud by attribute values

  • Exact tool ID:Classify_Classify_by_Attribute
  • Recommended call:mls.classify.classify_classify_by_attribute(...)
  • Alias:Classify_Classify_by_Attribute
  • Required parameters:input_paths, Parameters

Parameters

Parameter Type Required Default Description
input_paths array Yes — Input point cloud file paths
Parameters object Yes — Attribute classification parameters

Parameters fields

Field Type Required Default Description
attribute integer No 0 0:default, all attributes participate; 1:elevation; 2:intensity; 3:time; 4:angle; 5:return; 6:additional attribute
minValue integer No 0 Minimum of the attribute. When the attribute is 0, this value does not need to be set
maxValue integer No 0 Maximum of the attribute. When the attribute is 0, this value does not need to be set
useSelected integer No 0 Use selected points only
additionAttributeName string No '' Additional attribute name
component integer No 0 Component index
toClass integer No 1 Target class

Example

from gvscript import mls

params = mls.classify.classify_classify_by_attribute_parameters()
params.attribute = 0

result = mls.classify.classify_classify_by_attribute(
    Parameters=params,
    input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)

classify_classify_by_air

Classify air-borne points

  • Exact tool ID:Classify_Classify_by_Air
  • Recommended call:mls.classify.classify_classify_by_air(...)
  • Alias:Classify_Classify_by_Air
  • Required parameters:input_paths, Parameters

Parameters

Parameter Type Required Default Description
input_paths array Yes — Input point cloud file paths
Parameters object Yes — Air point classification parameters

Parameters fields

Field Type Required Default Description
neighborPoints integer No 10 Number of neighboring points
mulStdDeviation number No 5 Standard deviation
useInputPointClouds integer No 0 Use input point clouds
toClass integer No 7 Target class

Example

from gvscript import mls

params = mls.classify.classify_classify_by_air_parameters()
params.neighborPoints = 10

result = mls.classify.classify_classify_by_air(
    Parameters=params,
    input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)

classify_classify_ground_points

Classify ground points

  • Exact tool ID:Classify_Classify_Ground_Points
  • Recommended call:mls.classify.classify_classify_ground_points(...)
  • Alias:Classify_Classify_Ground_Points
  • Required parameters:input_paths, Parameters

Parameters

Parameter Type Required Default Description
input_paths array Yes — Input point cloud file paths
Parameters object Yes — Ground point classification parameters

Parameters fields

Field Type Required Default Description
MaxBldSize integer No 20 Maximum building size
TerrAngle number No 88 Terrain angle
IterAngle number No 8 Iteration angle
IterDistance number No 1.4 Iteration distance
isStopTriang integer No 1 Is stop triangulation
isReduceAngleLength integer No 0 Is reduce angle length
stopTriAng number No 1 Stop triangulation angle
ReduceAngleLength number No 5 Reduce angle length
isOnlyKeyPoints integer No 0 Only key points
ToleranceAbove number No 0.15 Tolerance above
ToleranceBelow number No 0.15 Tolerance below
GridSize number No 20 Grid size
useSelected integer No 0 Use selected points
useInputPointClouds integer No 0 Use input point clouds
showAsAdvancedDlg integer No 1 Show as advanced dialog
GeomorType integer No 2 Geomorphology type
toClass integer No 2 Target class

Example

from gvscript import mls

params = mls.classify.classify_classify_ground_points_parameters()
params.MaxBldSize = 20

result = mls.classify.classify_classify_ground_points(
    Parameters=params,
    input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)

classify_classify_below_surface_points

Classify below surface points

  • Exact tool ID:Classify_Classify_Below_Surface_Points
  • Recommended call:mls.classify.classify_classify_below_surface_points(...)
  • Alias:Classify_Classify_Below_Surface_Points
  • Required parameters:input_paths, Parameters

Parameters

Parameter Type Required Default Description
input_paths array Yes — Input point cloud file paths
Parameters object Yes — Below surface classification parameters

Parameters fields

Field Type Required Default Description
stdDeviation integer No 3 Standard deviation
zTolerance number No 0.1 Z tolerance
toClass integer No 7 Target class

Example

from gvscript import mls

params = mls.classify.classify_classify_below_surface_points_parameters()
params.stdDeviation = 3

result = mls.classify.classify_classify_below_surface_points(
    Parameters=params,
    input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)

classify_classify_by_height_above

Classify points by height above ground

  • Exact tool ID:Classify_Classify_By_Height_Above
  • Recommended call:mls.classify.classify_classify_by_height_above(...)
  • Alias:Classify_Classify_By_Height_Above
  • Required parameters:input_paths, Parameters

Parameters

Parameter Type Required Default Description
input_paths array Yes — Input point cloud file paths
Parameters object Yes — Height above classification parameters

Parameters fields

Field Type Required Default Description
groundClass integer No 2 Ground class ID
minHeight number No 1 Minimum height
maxHeight number No 2 Maximum height
toClass integer No 3 Target class

Example

from gvscript import mls

params = mls.classify.classify_classify_by_height_above_parameters()
params.groundClass = 2

result = mls.classify.classify_classify_by_height_above(
    Parameters=params,
    input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)

classify_classify_low_points

Classify low points

  • Exact tool ID:Classify_Classify_Low_Points
  • Recommended call:mls.classify.classify_classify_low_points(...)
  • Alias:Classify_Classify_Low_Points
  • Required parameters:input_paths, Parameters

Parameters

Parameter Type Required Default Description
input_paths array Yes — Input point cloud file paths
Parameters object Yes — Low points classification parameters

Parameters fields

Field Type Required Default Description
height number No 0.5 Height threshold
radius number No 5 Search radius
pointsNum integer No 1 Number of points threshold
toClass integer No 7 Target class

Example

from gvscript import mls

params = mls.classify.classify_classify_low_points_parameters()
params.height = 0.5

result = mls.classify.classify_classify_low_points(
    Parameters=params,
    input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)

classify_classify_isolated_points

Classify isolated points

  • Exact tool ID:Classify_Classify_Isolated_Points
  • Recommended call:mls.classify.classify_classify_isolated_points(...)
  • Alias:Classify_Classify_Isolated_Points
  • Required parameters:input_paths, Parameters

Parameters

Parameter Type Required Default Description
input_paths array Yes — Input point cloud file paths
Parameters object Yes — Isolated points classification parameters

Parameters fields

Field Type Required Default Description
radius number No 5 Search radius
pointsNum integer No 3 Number of neighboring points threshold
toClass integer No 1 Target class

Example

from gvscript import mls

params = mls.classify.classify_classify_isolated_points_parameters()
params.radius = 5

result = mls.classify.classify_classify_isolated_points(
    Parameters=params,
    input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)

classify_classify_closeby_points

Classify closeby points

  • Exact tool ID:Classify_Classify_Closeby_Points
  • Recommended call:mls.classify.classify_classify_closeby_points(...)
  • Alias:Classify_Classify_Closeby_Points
  • Required parameters:input_paths, Parameters

Parameters

Parameter Type Required Default Description
input_paths array Yes — Input point cloud file paths
Parameters object Yes — Closeby points classification parameters

Parameters fields

Field Type Required Default Description
radius number No 5 Search radius
pointsNum integer No 3 Number of neighboring points threshold
toClass integer No 1 Target class

Example

from gvscript import mls

params = mls.classify.classify_classify_closeby_points_parameters()
params.radius = 5

result = mls.classify.classify_classify_closeby_points(
    Parameters=params,
    input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)

classify_classify_by_min_elevation

Classify by minimum elevation difference

  • Exact tool ID:Classify_Classify_By_Min_Elevation
  • Recommended call:mls.classify.classify_classify_by_min_elevation(...)
  • Alias:Classify_Classify_By_Min_Elevation
  • Required parameters:input_paths, Parameters

Parameters

Parameter Type Required Default Description
input_paths array Yes — Input point cloud file paths
Parameters object Yes — Min elevation classification parameters

Parameters fields

Field Type Required Default Description
radius number No 5 Search radius
minHeight number No 0 Minimum height
maxHeight number No 1 Maximum height
toClass integer No 3 Target class

Example

from gvscript import mls

params = mls.classify.classify_classify_by_min_elevation_parameters()
params.radius = 5

result = mls.classify.classify_classify_by_min_elevation(
    Parameters=params,
    input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)

classify_classify_by_deep_learning

Classify point cloud by deep learning model

  • Exact tool ID:Classify_Classify_By_Deep_Learning
  • Recommended call:mls.classify.classify_classify_by_deep_learning(...)
  • Alias:Classify_Classify_By_Deep_Learning
  • Required parameters:input_paths, Parameters

Parameters

Parameter Type Required Default Description
input_paths array Yes — Input point cloud file paths
Parameters object Yes — Deep learning classification parameters

Parameters fields

Field Type Required Default Description
modelName string No 'GV_Road_MLS' GV_Road_MLS (outdoor, vehicle-mounted), GV_Indoor_HLS (indoor, handheld), GV_Park_HLS (outdoor, handheld), GV_Forest_HLS (forestry, handheld), GV_Garage_HLS (underground parking garage, handheld), GV_Railway (railway)
doPostprocessing string No '0' 0:No need to optimize ground points; 1:optimize ground points
isGPU string No '1' 0:CPU; 1:GPU
id string No '0' ID
isMapping string No '0' Is mapping
batchSize string No '2' Batch size
blockSize string No '200' Block size
bufferSize string No '10' Buffer size

Example

from gvscript import mls

params = mls.classify.classify_classify_by_deep_learning_parameters()
params.modelName = 'GV_Road_MLS'

result = mls.classify.classify_classify_by_deep_learning(
    Parameters=params,
    input_paths=['D:/data/input.LiData'],
)
print(result.ok, result.output, result.message)

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