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:
Purpose
Inputs
Outputs
Parameters
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:
Type
Name
Reality Data type
Description
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:
Purpose
Inputs
Outputs
Parameters
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:
Type
Name
Reality Data type
Description
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:
Purpose
Inputs
Outputs
Parameters
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:
Type
Name
Reality Data type
Description
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:
Purpose
Inputs
Outputs
Parameters
(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:
Type
Name
Reality Data type
Description
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:
Purpose
Inputs
Outputs
Parameters
*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:
Type
Name
Reality Data type
Description
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
Was this page helpful?