Pavement Analysis API

Module: mls.pavement. This page documents 5 public functions with exact tool IDs, complete parameters, Parameters fields, and examples.

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Functions

  • onnxdependency_damage_by_cloud — Point cloud-based distress detection - detects 7 geometric distress types (rutting, depression, pothole, bump, upheaval, waves, shoving) using MLS point cloud geometry analysis
  • onnxdependency_damage_by_img — Image-based distress detection - runs deep learning on panoramic/planar images, back-projects 2D results to 3D; detects 6 types (transverse/longitudinal/alligator crack, pothole, patching, raveling)
  • onnxdependency_sample_unit_generator — Generates sample units along the road for PCI calculation; supports Auto mode (curb detection via trajectory)
  • onnxdependency_pci_cal — Computes PCI per ASTM D6433-07 from distress and sample unit data; outputs PCI Section layer
  • onnxdependency_pci_report — Exports a comprehensive HTML report from the Distress and PCI Section layers

onnxdependency_damage_by_cloud

Point cloud-based distress detection - detects 7 geometric distress types (rutting, depression, pothole, bump, upheaval, waves, shoving) using MLS point cloud geometry analysis

  • Exact tool ID:OnnxDependency_Damage_By_Cloud
  • Recommended call:mls.pavement.onnxdependency_damage_by_cloud(...)
  • Alias:OnnxDependency_Damage_By_Cloud
  • Required parameters:input_paths

Parameters

Parameter Type Required Default Description
input_paths array Yes — Point cloud file paths
Parameters object No — Point cloud distress detection parameters

Parameters fields

Field Type Required Default Description
classMask object No {'0': 2} The class of ground points in point cloud file
laneWidth number No 3.7 Lane width in meters. Defines the width of each lane for road range calculation.
leftLaneNum integer No 1 Number of lanes on the left side of the road centerline.
rightLaneNum integer No 1 Number of lanes on the right side of the road centerline.
tolerance number No 0.006 Elevation tolerance in meters. Points exceeding this height/depth threshold from the road surface are considered potential damage.
minArea number No 0.1 Minimum area in m². Damage regions smaller than this are filtered out as noise.

Example

from gvscript import mls

params = mls.pavement.onnxdependency_damage_by_cloud_parameters()
params.classMask = {'0': 2}

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

onnxdependency_damage_by_img

Image-based distress detection - runs deep learning on panoramic/planar images, back-projects 2D results to 3D; detects 6 types (transverse/longitudinal/alligator crack, pothole, patching, raveling)

  • Exact tool ID:OnnxDependency_Damage_By_Img
  • Recommended call:mls.pavement.onnxdependency_damage_by_img(...)
  • Alias:OnnxDependency_Damage_By_Img
  • Required parameters:input_paths

Parameters

Parameter Type Required Default Description
input_paths array Yes — Point cloud file paths
Parameters object No — Image distress detection parameters

Parameters fields

Field Type Required Default Description
classMask object No {'0': 2} The class of ground points in point cloud file
maxDist number No 15.0 Maximum distance in meters. Damage detected farther than this from the camera is filtered out.
distRadius number No 20.0 Projection radius in meters. Controls the distance range for projecting image detection results onto the point cloud.
minArea number No 0.1 Minimum area in m². Damage regions smaller than this are filtered out.
camType integer No 0 Camera type: 0 = panoramic, 1 = planar
imgRanges object No — Planar camera image ID ranges, keyed by camera ID.

Example

from gvscript import mls

params = mls.pavement.onnxdependency_damage_by_img_parameters()
params.classMask = {'0': 2}

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

onnxdependency_sample_unit_generator

Generates sample units along the road for PCI calculation; supports Auto mode (curb detection via trajectory)

  • Exact tool ID:OnnxDependency_Sample_Unit_Generator
  • Recommended call:mls.pavement.onnxdependency_sample_unit_generator(...)
  • Alias:OnnxDependency_Sample_Unit_Generator
  • Required parameters:input_paths

Parameters

Parameter Type Required Default Description
input_paths array Yes — Point cloud file paths
Parameters object No — Sample unit generation parameters

Parameters fields

Field Type Required Default Description
classMask object No {'0': 2} The class of ground points in point cloud file
stdArea number No 255.0 Standard sample unit area in m². Each sample unit will be approximately this size.
minLaneWidth number No 2.5 Minimum lane width in meters (AUTO mode). Used to detect the inner road boundary.
maxLaneWidth number No 3.7 Maximum lane width in meters (AUTO mode). Used to detect the outer road boundary.
trajectory string No '' Trajectory file path (AUTO mode). The trajectory defines the road alignment direction.

Example

from gvscript import mls

params = mls.pavement.onnxdependency_sample_unit_generator_parameters()
params.classMask = {'0': 2}

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

onnxdependency_pci_cal

Computes PCI per ASTM D6433-07 from distress and sample unit data; outputs PCI Section layer

  • Exact tool ID:OnnxDependency_PCI_CAL
  • Recommended call:mls.pavement.onnxdependency_pci_cal(...)
  • Alias:OnnxDependency_PCI_CAL
  • Required parameters: None

Parameters

Parameter Type Required Default Description
Parameters object No — PCI calculation parameters

Parameters fields

Field Type Required Default Description
trajPath string No '' Trajectory file path (used with TRAJ source).
rutting object No {'low': 0.006, 'medium': 0.013, 'high': 0.025} Rutting severity thresholds: { low, medium, high } in meters
depression object No {'low': 0.013, 'medium': 0.025, 'high': 0.05} Depression severity thresholds: { low, medium, high } in meters
potholes_diameter object No {'low': 0.1, 'medium': 0.2, 'high': 0.45} Pothole diameter severity thresholds: { low, medium, high } in meters
potholes_depth object No {'low': 0.013, 'medium': 0.025, 'high': 0.05} Pothole depth severity thresholds: { low, medium, high } in meters
swell object No {'low': 0.0061, 'medium': 0.0183, 'high': 0.0457} Swell severity thresholds: { low, medium, high } in meters
bump object No {'low': 0.0061, 'medium': 0.0183, 'high': 0.0457} Bump severity thresholds: { low, medium, high } in meters
corrugation object No {'low': 0.0061, 'medium': 0.0183, 'high': 0.0457} Corrugation severity thresholds: { low, medium, high } in meters
shoving object No {'low': 0.0061, 'medium': 0.0183, 'high': 0.0457} Shoving severity thresholds: { low, medium, high } in meters

Example

from gvscript import mls

params = mls.pavement.onnxdependency_pci_cal_parameters()
params.trajPath = ''

result = mls.pavement.onnxdependency_pci_cal(
    Parameters=params,
)
print(result.ok, result.output, result.message)

onnxdependency_pci_report

Exports a comprehensive HTML report from the Distress and PCI Section layers

  • Exact tool ID:OnnxDependency_PCI_Report
  • Recommended call:mls.pavement.onnxdependency_pci_report(...)
  • Alias:OnnxDependency_PCI_Report
  • Required parameters: None

Parameters

Parameter Type Required Default Description
Parameters object No — PCI report export parameters

Parameters fields

Field Type Required Default Description
htmlPath string No '' Full output path for the HTML report file. If not specified, a default path is generated automatically.

Example

from gvscript import mls

params = mls.pavement.onnxdependency_pci_report_parameters()
params.htmlPath = ''

result = mls.pavement.onnxdependency_pci_report(
    Parameters=params,
)
print(result.ok, result.output, result.message)

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