Job types - Reality Data Analysis

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Reality Data Analysis

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Reality Analysis job types

Reality Analysis jobs are classified in different types, depending on the detector they use. Here are these job types. For each type, we detail here the different arguments in a more compact way than in the API Reference.

Objects2D

This job uses a photo object detector to detects 2D objects in photos. If photos are oriented, it can turn these 2D objects into 3D objects. In this case, an optional collection of point clouds or meshes might help estimating 3D objects. The following analysis are available:

Detect objects in photos

photos, photoObjectDetector

objects2D

Detect 2D objects in oriented photos and infer 3D objects

photos, photoObjectDetector, pointClouds (opt.), meshes (opt.)

objects3D, objects2D, exportedObjects3DDGN (opt.), exportedObjects3DCesium (opt.), exportedObjects3DGeoJSON (opt.), exportedLocations3DSHP (opt.), exportedLocations3DGeoJSON (opt.)

exportSrs (opt.), minPhotos (opt.),maxDist (opt.), useTiePoints (opt.)

Given 2D objects in oriented photos, infer 3D objects

photos, objects2D, pointClouds (opt.), meshes (opt.)

objects3D, exportedObjects3DDGN (opt.), exportedObjects3DCesium (opt.), exportedObjects3DGeoJSON (opt.), exportedLocations3DSHP (opt.), exportedLocations3DGeoJSON (opt.)

exportSrs (opt.), minPhotos (opt.),maxDist (opt.), useTiePoints (opt.)

where the arguments are:

input

photos

ContextScene

photos to analyze

input/output

objects2D

ContextScene

If output: 2D objects detected by current job. If input: given 2D objects.

input

photoObjectDetector

ContextDetector

photo object detector

input

pointClouds

ContextScene

collection of point clouds

input

meshes

ContextScene

collection of meshes

output

objects3D

ContextScene

detected 3D objects

output

exportedObjects3DDGN

DGN

DGN file export with 3D objects

output

exportedObjects3DCesium

Cesium3DTiles

Cesium 3D Tiles file export with 3D objects

output

exportedObjects3DGeoJSON

GeoJSON

GeoJSON file export with 3D objects

output

exportedLocations3DSHP

SHP

ESRI SHP file export with locations of the 3D objects

output

exportedLocations3DGeoJSON

GeoJSON

GeoJSON file export with locations of the 3D objects

parameter

exportSrs

string

SRS used by exports

parameter

minPhotos

int

minimum number of 2D objects to generate a 3D object

parameter

maxDist

float

maximum distance between photos and 3D objects

parameter

useTiePoints

boolean

improve detection using tie points in orientedPhotos (advanced)

Segmentation2D

This job uses a photo segmentation detector to classify pixels in photos. If photos are oriented, it can project this classification onto a mesh or a point cloud, detecting 3D lines and 3D polygon The following analysis are available:

Segmentation of photos

photos, photoSegmentationDetector

segmentation2D, segmentedPhotos

Segment oriented photos and project segmentation on a collection of meshes or point clouds and detect 3D lines and 3D polygons

photos, photoSegmentationDetector, pointClouds/meshes

segmentation2D, segmentedPhotos, lines3D(opt.), exportedLines3DDGN (opt.), exportedLines3DCesium (opt.), exportedLines3DGeoJSON (opt.), polygons3D (opt.), exportedPolygons3DDGN (opt.), exportedPolygons3DCesium (opt.), exportedPolygons3DGeoJSON (opt.)

minPhotos (opt.), exportSrs (opt.), removeSmallComponents (opt.),computeLineWidth (opt.)

Given a 2D segmentation of oriented photos, project segmentation on a collection of meshes or point clouds and detect 3D lines and 3D polygons

photos, segmentation2D, pointClouds/meshes

lines3D(opt.), exportedLines3DDGN (opt.), exportedLines3DCesium (opt.), exportedLines3DGeoJSON (opt.), polygons3D (opt.), exportedPolygons3DDGN (opt.), exportedPolygons3DCesium (opt.), exportedPolygons3DGeoJSON (opt.)

minPhotos (opt.), exportSrs (opt.), removeSmallComponents (opt.),computeLineWidth (opt.)

where the arguments are:

input

photos

ContextScene

photos to analyze

input

photoSegmentationDetector

ContextDetector

photo segmentation detector to apply

input

pointClouds

ContextScene

collection of point clouds

input

meshes

ContextScene

collection of meshes

input/output

segmentation2D

ContextScene

2D segmentation

output

segmentedPhotos

CCImageCollection

segmented photos (used by segmentation2D)

output

lines3D

ContextScene

detected 3D lines

output

exportedLines3DDGN

DGN

DGN file export with 3D lines

output

exportedLines3DCesium

Cesium3DTiles

Cesium 3D Tiles file export with 3D lines

output

exportedLines3DGeoJSON

GeoJSON

GeoJSON file export with 3D lines

output

polygons3D

ContextScene

detected 3D polygons

output

exportedPolygons3DDGN

DGN

DGN file export with 3D polygons

output

exportedPolygons3DCesium

Cesium3DTiles

Cesium 3D Tiles file export with 3D polygons

output

exportedPolygons3DGeoJSON

GeoJSON

GeoJSON file export with 3D polygons

parameter

minPhotos

int

minimum number of 2D detection to generate a 3D detection

parameter

exportSrs

string

SRS used by exports

parameter

removeSmallComponents

float

remove 3D lines with total length smaller than this value

parameter

computeLineWidth

boolean

estimation 3D line width at each vertex

SegmentationOrthophoto

This job uses an orthophoto segmentation detector to classify pixels in an orthophoto. Depending on the detector, it can detect 2D lines and 2D polygons. The following analysis are available:

Segmentation of orthophoto

orthophoto, orthophotoSegmentationDetector

segmentation2D, segmentedPhotos, polygons2D (opt.), exportedPolygons2DSHP (opt. and only if polygons2D is set), exportedPolygons2DGeoJSON (opt. and only if polygons2D is set), lines2D (opt.), exportedLines2DDGN (opt. and only if lines2D is set), exportedLines2DSHP (opt. and only if lines2D is set), exportedLines2DGeoJSON (opt. and only if lines2D is set)

where the arguments are:

input

orthophoto

ContextScene

orthophoto to analyze

input

orthophotoSegmentationDetector

ContextDetector

orthophoto segmentation detector to apply

output

segmentation2D

ContextScene

2D segmentation

output

segmentedPhotos

CCImageCollection

segmented photos (used by segmentation2D)

output

polygons2D

ContextScene

detected 2D polygons

output

exportedPolygons2DSHP

SHP

2D polygons exported to ESRI shapefile

output

exportedPolygons2DGeoJSON

GeoJSON

2D polygons exported to GeoJSON

output

lines2D

ContextScene

detected 2D lines

output

exportedLines2DDGN

DGN

2D lines exported to DGN file

output

exportedLines2DSHP

SHP

2D lines exported to ESRI shapefile

output

exportedLines2DGeoJSON

GeoJSON

2D lines exported to GeoJSON

Segmentation3D

This job uses a point cloud segmentation detector to classify each point of a point cloud. Variants are available:

it may start from a mesh.
the 3D segmentation may be used to infer 3D objects, 3D lines and 3D polygons.

Finally, the following analysis are available:

(1) Segment a collection of point clouds

pointClouds, pointCloudSegmentationDetector, clipPolygon (opt.)

segmentation3D, segmentedPointCloud, exportedSegmentation3DLAS (opt.), exportedSegmentation3DLAZ (opt.), exportedSegmentation3DPOD (opt.), exportedSegmentation3DPLY (opt.)

saveConfidence (opt.),exportSrs (opt.)

(2) Segment a collection of meshes

meshes, pointCloudSegmentationDetector, clipPolygon (opt.)

same as (1)

saveConfidence (opt.),exportSrs (opt.)

(3) Segment a collection of point clouds or meshes and infer 3D objects, 3D lines and 3D polygons()

same as (1) or (2)

same as (1) or (2) + objects3D (opt.), exportedObjects3DDGN (opt.), exportedObjects3DCesium (opt.), exportedObjects3DGeoJSON (opt.), exportedLocations3DSHP (opt.), exportedLocations3DGeoJSON (opt.), lines3D (opt.), exportedLines3DDGN (opt.), exportedLines3DCesium (opt.), exportedLines3DGeoJSON (opt.), polygons3D (opt.), exportedPolygons3DDGN (opt.), exportedPolygons3DCesium (opt.), exportedPolygons3DGeoJSON (opt.)

removeSmallComponents (opt.), computeLineWidth(opt.), saveConfidence (opt.), exportSrs (opt.), removeSmallComponents (opt.),computeLineWidth (opt.)

(4) Same as any above but starts from a previous 3D segmentation

same as above with segmentation3D instead of pointClouds, meshes and pointCloudSegmentationDetector

same as above except segmentation3D and segmentedPointCloud

same as (3)

where the arguments are:

input

pointClouds

ContextScene

collection of point clouds

input

meshes

ContextScene

collection of meshes

input

pointCloudSegmentationDetector

ContextDetector

point cloud segmentation detector

input

clipPolygon (*)

Unstructured

clipping polygon to limit the analysis to a given region

output/input

segmentation3D

ContextScene

If output: 3D segmentation computed by current job. If input: given 3D segmentation.

output

segmentedPointCloud

OPC

3D segmentation as an OPC file (used by segmentation3D).

output

exportedSegmentation3DPOD

PointCloud

3D segmentation exported as a POD file.

output

exportedSegmentation3DLAS

LAS

3D segmentation exported as a LAS file.

output

exportedSegmentation3DLAZ

LAZ

3D segmentation exported as a LAZ file.

output

exportedSegmentation3DPLY

PLY

3D segmentation exported as a PLY file.

output

objects3D

ContextScene

3D objects inferred from 3D segmentation

output

exportedObjects3DDGN

DGN

DGN file export with 3D objects

output

exportedObjects3DCesium

Cesium3DTiles

Cesium 3D Tiles file export with 3D objects

output

exportedObjects3DGeoJSON

GeoJSON

GeoJSON file export with 3D objects

output

exportedLocations3DSHP

SHP

ESRI SHP file export with locations of the 3D objects

output

exportedLocations3DGeoJSON

GeoJSON

GeoJSON file export with locations of the 3D objects

output

lines3D

ContextScene

detected 3D lines

output

exportedLines3DDGN

DGN

DGN file export with 3D lines

output

exportedLines3DCesium

Cesium3DTiles

Cesium 3D Tiles file export with 3D lines

output

exportedLines3DGeoJSON

GeoJSON

GeoJSON file export with 3D lines

output

polygons3D

ContextScene

detected 3D polygons

output

exportedPolygons3DDGN

DGN

DGN file export with 3D polygons

output

exportedPolygons3DCesium

Cesium3DTiles

Cesium 3D Tiles file export with 3D polygons

output

exportedPolygons3DGeoJSON

GeoJSON

GeoJSON file export with 3D polygons

parameter

removeSmallComponents

float

remove 3D lines with total length smaller than this value

parameter

computeLineWidth

boolean

estimation 3D line width at each vertex

parameter

saveConfidence (*)

boolean

save confidence in 3D segmentation

parameter

exportSRS

string

SRS used by exports.

ChangeDetection

This job detects changes between two collections of point clouds or meshes3D. It uses distance or changes of color between the two collections. The output is a set of 3D objects capturing the regions with changes. This jobs does not use Machine Learning yet.

The following analysis are available:

*Detect changes between two collections of point clouds

pointClouds1, pointClouds2

objects3D, exportedLocations3DSHP (opt.), exportedLocations3DGeoJSON (opt.)

exportSrs (opt.), colorThresholdLow (opt.),colorThresholdHigh (opt.), distThresholdLow (opt.),distThresholdHigh (opt.), minPoints (opt.)

*Detect changes between two collections of meshes

meshes1, meshes2

objects3D, exportedLocations3DSHP (opt.), exportedLocations3DGeoJSON (opt.)

resolution, exportSrs (opt.), colorThresholdLow (opt.),colorThresholdHigh (opt.), distThresholdLow (opt.),distThresholdHigh (opt.), minPoints (opt.)

where the arguments are:

input

pointClouds1

ContextScene

first collection of point clouds

input

pointClouds2

ContextScene

second collection of point clouds

input

meshes1

ContextScene

first collection of meshes

input

meshes2

ContextScene

second collection of meshes

output

objects3D

ContextScene

regions with changes

output

exportedLocations3DSHP

SHP

ESRI SHP file export with locations of regions with changes

output

exportedLocations3DGeoJSON

GeoJSON

GeoJSON file export with locations of regions with changes

parameter

resolution

float

target point cloud resolution when starting from meshes

parameter

exportSrs

string

SRS used by exports

parameter

colorThresholdLow

float

low threshold to detect color changes (hysteresis detection)

parameter

colorThresholdHigh

float

high threshold to detect color changes (hysteresis detection)

parameter

distThresholdLow

float

low threshold to detect spatial changes (hysteresis detection)

parameter

distThresholdHigh

float

high threshold to detect spatial changes (hysteresis detection)

parameter

minPoints

int

minimum number of points in a region to be considered as a change