Metashape Python Reference
Release 2.0.2
Agisoft LLC
Jun 05, 2023

CONTENTS
1 Overview 3
2 Application Modules 5
3 Python API Change Log 215
Python Module Index 249
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Copyright (c) 2023 Agisoft LLC.
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2 CONTENTS
CHAPTER
ONE
OVERVIEW
1.1 Introduction to Python scripting in Metashape Professional
This API is in development and will be extended in the future Metashape releases.
Note: Python scripting is supported only in Metashape Professional edition.
Metashape Professional uses Python 3.8 as a scripting engine.
Python commands and scripts can be executed in Metashape in one of the following ways:

From Metashape “Console” pane using it as standard Python console.
From the “Tools” menu using “Run script. . . ” command.
From command line using “-r” argument and passing the path to the script as an argument.
The following Metashape funtionality can be accessed from Python scripts:
Open/save/create Metashape projects.
Add/remove chunks, cameras, markers.
Add/modify camera calibrations, ground control data, assign geographic projections and coordinates.
Perform processing steps (align photos, build dense cloud, build mesh, texture, decimate model,
etc. . . ).
Export processing results (models, textures, orthophotos, DEMs).
Access data of generated models, point clouds, images.
Start and control network processing tasks.
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CHAPTER
TWO
APPLICATION MODULES
Metashape module provides access to the core processing functionality, including support for inspection and manipulation with project data.
The main component of the module is a Document class, which represents a Metashape project. Multiple Document
instances can be created simultaneously if needed. Besides that a currently opened project in the application can be
accessed using Metashape.app.document property.
The following example performs main processing steps on existing project and saves back the results:

import Metashape
doc = Metashape.app.document
doc.open(« project.psz »)
chunk = doc.chunk
chunk.matchPhotos(downscale=1, generic_preselection=True, reference_
˓→preselection=False)
chunk.alignCameras()
chunk.buildDepthMaps(downscale=4, filter_mode=Metashape.AggressiveFiltering)
chunk.buildModel(source_data=Metashape.DepthMapsData, surface_type=Metashape.
˓→Arbitrary, interpolation=Metashape.EnabledInterpolation)
chunk.buildUV(mapping_mode=Metashape.GenericMapping)
chunk.buildTexture(blending_mode=Metashape.MosaicBlending, texture_size=4096)
doc.save()
class Metashape.Antenna
GPS antenna position relative to camera.
copy()
Return a copy of the object.
Returns A copy of the object.
Return type Antenna
fixed
Fix antenna flag.
Type bool
location
Antenna coordinates.
Type Vector
location_acc
Antenna location accuracy.
Type Vector
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location_covariance
Antenna location covariance.
Type Matrix
location_ref
Antenna location reference.
Type Vector
rotation
Antenna rotation angles.
Type Vector
rotation_acc
Antenna rotation accuracy.
Type Vector
rotation_covariance
Antenna rotation covariance.
Type Matrix
rotation_ref
Antenna rotation reference.
Type Vector
class Metashape.Application
Application class provides access to several global application attributes, such as document currently loaded in
the user interface, software version and GPU device configuration. It also contains helper routines to prompt the
user to input various types of parameters, like displaying a file selection dialog or coordinate system selection
dialog among others.
An instance of Application object can be accessed using Metashape.app attribute, so there is usually no need to
create additional instances in the user code.
The following example prompts the user to select a new coordinate system, applies it to the ative chunk and saves
the project under the user selected file name:
import Metashape
doc = Metashape.app.document
crs = Metashape.app.getCoordinateSystem(« Select Coordinate System », doc.chunk.
˓→crs)
doc.chunk.crs = crs
path = Metashape.app.getSaveFileName(« Save Project As »)
try:
… doc.save(path)
… except RuntimeError:
… Metashape.app.messageBox(« Can’t save project »)
class ConsolePane
ConsolePane class provides access to the console pane
clear()
Clear console pane.
contents
Console pane contents.
Type string
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class ModelView
ModelView class provides access to the model view
class ModelViewMode
Model view mode in [ModelViewShaded, ModelViewSolid, ModelViewWireframe, ModelViewConfidence, ModelViewTextured]
class PointCloudViewMode
Point cloud view mode in [PointCloudViewSolid, PointCloudViewColor, PointCloudViewClassification, PointCloudViewIntensity, PointCloudViewElevation, PointCloudViewConfidence, PointCloudViewReturnNumber, PointCloudViewScanAngle, PointCloudViewSourceId]
class TiePointsViewMode
Tie points view mode in [TiePointsViewColor, TiePointsViewVariance]
class TiledModelViewMode
Tiled model view mode in [TiledModelViewTextured, TiledModelViewSolid, TiledModelViewWireframe]
captureView([width ][, height][, transparent][, hide_items])
Capture image from model view.
Parameters

width (int) – Image width.

height (int) – Image height.

transparent (bool) – Sets transparent background.

hide_items (bool) – Hides all items.
Returns Captured image.
Return type Image
model_view_mode
Model view mode.
Type ModelViewMode
point_cloud_view_mode
Point cloud view mode.
Type PointCloudViewMode
texture_view_mode
Texture view mode.
Type TextureViewMode
tie_points_view_mode
Tie points view mode.
Type TiePointsViewMode
tiled_model_view_mode
Tiled model view mode.
Type TiledModelViewMode
view_mode
View mode.
Type DataSource
viewpoint
Viewpoint in the model view.
Type Viewpoint
class OrthoView
OrthoView class provides access to the ortho view
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captureView([width ][, height][, transparent][, hide_items])
Capture image from ortho view.
Parameters

width (int) – Image width.

height (int) – Image height.

transparent (bool) – Sets transparent background.

hide_items (bool) – Hides all items.
Returns Captured image.
Return type Image
view_mode
View mode.
Type DataSource
class PhotosPane
PhotosPane class provides access to the photos pane
resetFilter()
Reset photos pane filter.
setFilter(items)
Set photos pane filter.
Parameters items (list of Camera or Marker) – filter to apply.
class Settings
PySettings()
Application settings
language
User interface language.
Type string
load()
Load settings from disk.
log_enable
Enable writing log to file.
Type bool
log_path
Log file path.
Type string
network_enable
Network processing enabled flag.
Type bool
network_host
Network server host name.
Type string
network_path
Network data root path.
Type string
network_port
Network server control port.
Type int
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project_absolute_paths
Store absolute image paths in project files.
Type bool
project_compression
Project compression level.
Type int
save()
Save settings on disk.
setValue(key, value)
Set settings value. :arg key: Key. :type key: string :arg value: Value. :type value: object
value(key)
Return settings value. :arg key: Key. :type key: string :return: Settings value. :rtype: object
activated
Metashape activation status.
Type bool
addMenuItem(label, func[, shortcut][, icon ])
Create a new menu entry.
Parameters

label (string) – Menu item label.

func (function) – Function to be called.

shortcut (string) – Keyboard shortcut.

icon (string) – Icon.
addMenuSeparator(label)
Add menu separator.
Parameters label (string) – Menu label.
console_pane
Console pane.
Type ConsolePane
cpu_enable
Use CPU when GPU is active.
Type bool
document
Main application document object.
Type Document
enumGPUDevices()
Enumerate installed GPU devices.
Returns A list of devices.
Return type list
getBool(label= »)
Prompt user for the boolean value.
Parameters label (string) – Optional text label for the dialog.
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Returns Boolean value selected by the user.
Return type bool
getCoordinateSystem([label][, value ])
Prompt user for coordinate system.
Parameters

label (string) – Optional text label for the dialog.

value (CoordinateSystem) – Default value.
Returns Selected coordinate system. If the dialog was cancelled, None is returned.
Return type CoordinateSystem
getExistingDirectory([hint][, dir])
Prompt user for the existing folder.
Parameters

hint (string) – Optional text label for the dialog.

dir (string) – Optional default folder.
Returns Path to the folder selected. If the input was cancelled, empty string is returned.
Return type string
getFloat(label= », value=0)
Prompt user for the floating point value.
Parameters

label (string) – Optional text label for the dialog.

value (float) – Default value.
Returns Floating point value entered by the user.
Return type float
getInt(label= », value=0)
Prompt user for the integer value.
Parameters

label (string) – Optional text label for the dialog.

value (int) – Default value.
Returns Integer value entered by the user.
Return type int
getOpenFileName([hint][, dir][, filter])
Prompt user for the existing file.
Parameters

hint (string) – Optional text label for the dialog.

dir (string) – Optional default folder.

filter (string) – Optional file filter, e.g. “Text file (.txt)” or “.txt”. Multiple filters are
separated with “;;”.
Returns Path to the file selected. If the input was cancelled, empty string is returned.
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Return type string
getOpenFileNames([hint][, dir][, filter])
Prompt user for one or more existing files.
Parameters

hint (string) – Optional text label for the dialog.

dir (string) – Optional default folder.

filter (string) – Optional file filter, e.g. “Text file (.txt)” or “.txt”. Multiple filters are
separated with “;;”.
Returns List of file paths selected by the user. If the input was cancelled, empty list is returned.
Return type list
getSaveFileName([hint][, dir][, filter])
Prompt user for the file. The file does not have to exist.
Parameters

hint (string) – Optional text label for the dialog.

dir (string) – Optional default folder.

filter (string) – Optional file filter, e.g. “Text file (.txt)” or “.txt”. Multiple filters are
separated with “;;”.
Returns Path to the file selected. If the input was cancelled, empty string is returned.
Return type string
getString(label= », value= »)
Prompt user for the string value.
Parameters

label (string) – Optional text label for the dialog.

value (string) – Default value.
Returns String entered by the user.
Return type string
gpu_mask
GPU device bit mask: 1 – use device, 0 – do not use (i.e. value 5 enables device number 0 and 2).
Type int
messageBox(message)
Display message box to the user.
Parameters message (string) – Text message to be displayed.
model_view
Model view.
Type ModelView
ortho_view
Ortho view.
Type OrthoView
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photos_pane
Photos pane.
Type PhotosPane
quit()
Exit application.
releaseFreeMemory()
Call malloc_trim on Linux (does nothing on other OS).
removeMenuItem(label)
Remove menu entry with given label (if exists). If there are multiple entries with given label – all of them
will be removed.
Parameters label (string) – Menu item label.
settings
Application settings.
Type Settings
title
Application name.
Type string
update()
Update user interface during long operations.
version
Metashape version.
Type string
class Metashape.AttachedGeometry
Attached geometry data.
GeometryCollection(geometries)
Create a GeometryCollection geometry.
Parameters geometries (list of Geometry) – Child geometries.
Returns A GeometryCollection geometry.
Return type Geometry
LineString(coordinates)
Create a LineString geometry.
Parameters coordinates (list of int) – List of vertex coordinates.
Returns A LineString geometry.
Return type Geometry
MultiLineString(geometries)
Create a MultiLineString geometry.
Parameters geometries (list of Geometry) – Child line strings.
Returns A point geometry.
Return type Geometry
MultiPoint(geometries)
Create a MultiPoint geometry.
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Parameters geometries (list of Geometry) – Child points.
Returns A point geometry.
Return type Geometry
MultiPolygon(geometries)
Create a MultiPolygon geometry.
Parameters geometries (list of Geometry) – Child polygons.
Returns A point geometry.
Return type Geometry
Point(key)
Create a Point geometry.
Parameters key (int) – Point marker key.
Returns A point geometry.
Return type Geometry
Polygon(exterior_ring[, interior_rings])
Create a Polygon geometry.
Parameters

exterior_ring (list of int) – Point coordinates.

interior_rings (list of int`) – Point coordinates.
Returns A Polygon geometry.
Return type Geometry
coordinates
List of vertex keys.
Type int
geometries
List of child geometries.
Type Geometry
type
Geometry type.
Type Geometry.Type
class Metashape.BBox
Axis aligned bounding box
copy()
Return a copy of the object.
Returns A copy of the object.
Return type BBox
max
Maximum bounding box extent.
Type Vector
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min
Minimum bounding box extent.
Type Vector
size
Bounding box dimension.
Type int
class Metashape.BlendingMode
Blending mode in [AverageBlending, MosaicBlending, MinBlending, MaxBlending, DisabledBlending]
class Metashape.Calibration
Calibration object contains camera calibration information including image size, focal length, principal point
coordinates and distortion coefficients.
b1
Affinity.
Type float
b2
Non-orthogonality.
Type float
copy()
Return a copy of the object.
Returns A copy of the object.
Return type Calibration
covariance_matrix
Covariance matrix.
Type Matrix
covariance_params
Covariance matrix parameters.
Type list of string
cx
Principal point X coordinate.
Type float
cy
Principal point Y coordinate.
Type float
error(point, proj)
Return projection error.
Parameters

point (Vector) – Coordinates of the point to be projected.

proj (Vector) – Pixel coordinates of the point.
Returns 2D projection error.
Return type Vector
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f
Focal length.
Type float
height
Image height.
Type int
k1
Radial distortion coefficient K1.
Type float
k2
Radial distortion coefficient K2.
Type float
k3
Radial distortion coefficient K3.
Type float
k4
Radial distortion coefficient K4.
Type float
load(path, format=CalibrationFormatXML)
Loads calibration from file.
Parameters

path (string) – path to calibration file

format (CalibrationFormat) – Calibration format.
p1
Decentering distortion coefficient P1.
Type float
p2
Decentering distortion coefficiant P2.
Type float
p3
Decentering distortion coefficient P3.
Type float
p4
Decentering distortion coefficiant P4.
Type float
project(point)
Return projected pixel coordinates of the point.
Parameters point (Vector) – Coordinates of the point to be projected.
Returns 2D projected point coordinates.
Return type Vector
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rpc
RPC model.
Type RPCModel
save(path, format=CalibrationFormatXML[, label][, pixel_size ][, focal_length ], cx = 0, cy = 0)
Saves calibration to file.
Parameters

path (string) – path to calibration file

format (CalibrationFormat) – Calibration format.

label (string) – Calibration label used in Australis, CalibCam and CalCam formats.

pixel_size (Vector) – Pixel size in mm used to convert normalized calibration coefficients to Australis and CalibCam coefficients.

focal_length (float) – Focal length (Grid calibration format only).

cx (float) – X principal point coordinate (Grid calibration format only).

cy (float) – Y principal point coordinate (Grid calibration format only).
type
Camera model.
Type Sensor.Type
unproject(point)
Return direction corresponding to the image point.
Parameters point (Vector) – Pixel coordinates of the point.
Returns 3D vector in the camera coordinate system.
Return type Vector
width
Image width.
Type int
class Metashape.CalibrationFormat
Calibration format in [CalibrationFormatXML, CalibrationFormatAustralis, CalibrationFormatAustralisV7,
CalibrationFormatPhotoModeler, CalibrationFormatCalibCam, CalibrationFormatCalCam, CalibrationFormatInpho, CalibrationFormatUSGS, CalibrationFormatPix4D, CalibrationFormatOpenCV, CalibrationFormatPhotomod, CalibrationFormatGrid, CalibrationFormatSTMap]
class Metashape.Camera
Camera instance
import Metashape
chunk = Metashape.app.document.addChunk()
chunk.addPhotos([« IMG_0001.jpg », « IMG_0002.jpg »])
camera = chunk.cameras[0]
camera.photo.meta[« Exif/FocalLength »]
’18’
The following example describes how to create multispectal camera layout:
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import Metashape
doc = Metashape.app.document
chunk = doc.chunk
rgb = [« RGB_0001.JPG », « RGB_0002.JPG », « RGB_0003.JPG »]
nir = [« NIR_0001.JPG », « NIR_0002.JPG », « NIR_0003.JPG »]
images = [[rgb[0], nir[0]], [rgb[1], nir[1]], [[rgb[2], nir[2]]
chunk.addPhotos(images, Metashape.MultiplaneLayout)
class Reference
Camera reference data.
accuracy
Camera location accuracy.
Type Vector
enabled
Location enabled flag.
Type bool
location
Camera coordinates.
Type Vector
location_accuracy
Camera location accuracy.
Type Vector
location_enabled
Location enabled flag.
Type bool
rotation
Camera rotation angles.
Type Vector
rotation_accuracy
Camera rotation accuracy.
Type Vector
rotation_enabled
Rotation enabled flag.
Type bool
class Type
Camera type in [Regular, Keyframe]
calibration
Adjusted camera calibration including photo-invariant parameters.
Type Calibration
center
Camera station coordinates for the photo in the chunk coordinate system.
Type Vector
chunk
Chunk the camera belongs to.
Type Chunk
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enabled
Enables/disables the photo.
Type bool
error(point, proj)
Returns projection error.
Parameters

point (Vector) – Coordinates of the point to be projected.

proj (Vector) – Pixel coordinates of the point.
Returns 2D projection error.
Return type Vector
frames
Camera frames.
Type list of Camera
group
Camera group.
Type CameraGroup
image()
Returns image data.
Returns Image data.
Return type Image
key
Camera identifier.
Type int
label
Camera label.
Type string
layer_index
Camera layer index.
Type int
location_covariance
Camera location covariance.
Type Matrix
mask
Camera mask.
Type Mask
master
Master camera.
Type Camera
meta
Camera meta data.
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Type MetaData
open(path[, layer])
Loads specified image file.
Parameters

path (string) – Path to the image file to be loaded.

layer (int) – Optional layer index in case of multipage files.
orientation
Image orientation (1 – normal, 6 – 90 degree, 3 – 180 degree, 8 – 270 degree).
Type int
photo
Camera photo.
Type Photo
planes
Camera planes.
Type list of Camera
project(point)
Returns coordinates of the point projection on the photo.
Parameters point (Vector) – Coordinates of the point to be projected.
Returns 2D point coordinates.
Return type Vector
reference
Camera reference data.
Type CameraReference
rotation_covariance
Camera rotation covariance.
Type Matrix
selected
Selects/deselects the photo.
Type bool
sensor
Camera sensor.
Type Sensor
shutter
Camera shutter.
Type Shutter
thumbnail
Camera thumbnail.
Type Thumbnail
transform
4×4 matrix describing photo location in the chunk coordinate system.
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Type Matrix
type
Camera type.
Type Camera.Type
unproject(point)
Returns coordinates of the point which will have specified projected coordinates.
Parameters point (Vector) – Projection coordinates.
Returns 3D point coordinates.
Return type Vector
vignetting
Vignetting for each band.
Type list of Vignetting
class Metashape.CameraGroup
CameraGroup objects define groups of multiple cameras. The grouping is established by assignment of a CameraGroup instance to the Camera.group attribute of participating cameras.
The type attribute of CameraGroup instances defines the effect of such grouping on processing results and can
be set to Folder (no effect) or Station (coincident projection centers).
class Type
Camera group type in [Folder, Station]
label
Camera group label.
Type string
selected
Current selection state.
Type bool
type
Camera group type.
Type CameraGroup.Type
class Metashape.CameraTrack
Camera track.
chunk
Chunk the camera track belongs to.
Type Chunk
duration
Animation duration.
Type float
field_of_view
Vertical field of view in degrees.
Type float
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interpolate(time)
Get animation camera transform matrix. :arg time: Animation time point. :type time: float :return: Interpolated camera transformation matrix in chunk coordinate system. :rtype: Matrix
keyframes
Camera track keyframes.
Type list of Camera
label
Animation label.
Type string
load(path[, projection ])
Load camera track from file.
Parameters

path (string) – Path to camera track file

projection (CoordinateSystem) – Camera track coordinate system.
meta
Camera track meta data.
Type MetaData
save(path[, file_format][, drone_name ][, payload_name ][, payload_position ][, max_waypoints][,
projection ])
Save camera track to file.
Parameters

path (string) – Path to camera track file

file_format (string) – File format. “deduce”: – Deduce from extension, “path”: Path,
“earth”: Google Earth KML, “pilot”: DJI Pilot KML, “wpml”: DJI WPML KML, “trinity”: Asctec Trinity CSV, “autopilot”: Asctec Autopilot CSV, “litchi”: Litchi CSV

drone_name (string) – Drone model. “M300 RTK”: – DJI Matrice 300 RTK, “M30”: –
DJI Matrice 30, “M30T”: – DJI Matrice 30T, “M3E”: – DJI Mavic 3E, “M3T”: – DJI Mavic
3T

payload_name (string) – Payload model. “P1 24mm”: – DJI Zenmuse P1 (24 mm lens),
“P1 35mm”: – DJI Zenmuse P1 (35 mm lens), “P1 50mm”: – DJI Zenmuse P1 (50 mm
lens), “H20”: – DJI Zenmuse H20, “H20T”: – DJI Zenmuse H20T, “H20N”: – DJI Zenmuse
H20N, “L1”: – DJI Zenmuse L1, “M30”: – DJI M30, “M30T”: – DJI M30T, “M3E”: – DJI
Mavic 3E Camera, “M3T”: – DJI Mavic 3T Camera

payload_position (string) – Payload position. For M300 RTK drone: “Front left”,
“Front right”, “Top”. For other drones: “Main gimbal”

max_waypoints (int) – Max waypoints per flight

projection (CoordinateSystem) – Camera track coordinate system.
class Metashape.CamerasFormat
Camera orientation format in [CamerasFormatXML, CamerasFormatCHAN, CamerasFormatBoujou, CamerasFormatBundler, CamerasFormatOPK, CamerasFormatPATB, CamerasFormatBINGO, CamerasFormatORIMA, CamerasFormatAeroSys, CamerasFormatInpho, CamerasFormatSummit, CamerasFormatBlocksExchange, CamerasFormatRZML, CamerasFormatVisionMap, CamerasFormatABC, CamerasFormatFBX, CamerasFormatNVM, CamerasFormatMA]
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class Metashape.Chunk
A Chunk object:

provides access to all chunk components (sensors, cameras, camera groups, markers, scale bars)

contains data inherent to individual frames (tie points, model, etc)

implements processing methods (matchPhotos, alignCameras, buildPointCloud, buildModel, etc)

provides access to other chunk attributes (transformation matrix, coordinate system, meta-data, etc..)
New components can be created using corresponding addXXX methods (addSensor, addCamera, addCameraGroup, addMarker, addScalebar, addFrame). Removal of components is supported by a single remove method,
which can accept lists of various component types.
In case of multi-frame chunks the Chunk object contains an additional reference to the particular chunk frame,
initialized to the current frame by default. Various methods that work on a per frame basis (matchPhotos, buildModel, etc) are applied to this particular frame. A frames attribute can be used to obtain a list of Chunk objects
that reference all available frames.
The following example performs image matching and alignment for the active chunk:
import Metashape
chunk = Metashape.app.document.chunk
for frame in chunk.frames:
… frame.matchPhotos(downscale=1)
chunk.alignCameras()
addCamera([sensor])
Add new camera to the chunk.
Parameters sensor (Sensor) – Sensor to be assigned to this camera.
Returns Created camera.
Return type Camera
addCameraGroup()
Add new camera group to the chunk.
Returns Created camera group.
Return type CameraGroup
addCameraTrack()
Add new camera track to the chunk.
Returns Created camera track.
Return type CameraTrack
addDepthMaps()
Add new depth maps set to the chunk.
Returns Created depth maps set.
Return type DepthMaps
addElevation()
Add new elevation model to the chunk.
Returns Created elevation model.
Return type Elevation
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addFrame()
Add new frame to the chunk.
Returns Created frame.
Return type Frame
addFrames([chunk ][, frames], copy_depth_maps=True, copy_point_cloud=True, copy_model=True,
copy_tiled_model=True, copy_elevation=True, copy_orthomosaic=True[, progress])
Add frames from specified chunk.
Parameters

chunk (int) – Chunk to copy frames from.

frames (list of int) – List of frame keys to copy.

copy_depth_maps (bool) – Copy depth maps.

copy_point_cloud (bool) – Copy point cloud.

copy_model (bool) – Copy model.

copy_tiled_model (bool) – Copy tiled model.

copy_elevation (bool) – Copy DEM.

copy_orthomosaic (bool) – Copy orthomosaic.

progress (Callable[[float], None]) – Progress callback.
addMarker([point], visibility=False)
Add new marker to the chunk.
Parameters

point (Vector) – Point to initialize marker projections.

visibility (bool) – Enables visibility check during projection assignment.
Returns Created marker.
Return type Marker
addMarkerGroup()
Add new marker group to the chunk.
Returns Created marker group.
Return type MarkerGroup
addModel()
Add new model to the chunk.
Returns Created model.
Return type Model
addOrthomosaic()
Add new orthomosaic to the chunk.
Returns Created orthomosaic.
Return type Orthomosaic
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addPhotos([filenames][, filegroups], layout=UndefinedLayout[, group ], strip_extensions=True,
load_reference=True, load_xmp_calibration=True, load_xmp_orientation=True,
load_xmp_accuracy=False, load_xmp_antenna=True, load_rpc_txt=False[, progress])
Add a list of photos to the chunk.
Parameters

filenames (list of string) – List of files to add.

filegroups (list of int) – List of file groups.

layout (ImageLayout) – Image layout.

group (int) – Camera group key.

strip_extensions (bool) – Strip file extensions from camera labels.

load_reference (bool) – Load reference coordinates.

load_xmp_calibration (bool) – Load calibration from XMP meta data.

load_xmp_orientation (bool) – Load orientation from XMP meta data.

load_xmp_accuracy (bool) – Load accuracy from XMP meta data.

load_xmp_antenna (bool) – Load GPS/INS offset from XMP meta data.

load_rpc_txt (bool) – Load satellite RPC data from auxiliary TXT files.

progress (Callable[[float], None]) – Progress callback.
addPointCloud()
Add new point cloud to the chunk.
Returns Created point cloud.
Return type PointCloud
addPointCloudGroup()
Add new point cloud group to the chunk.
Returns Created point cloud group.
Return type PointCloudGroup
addScalebar(point1, point2)
Add new scale bar to the chunk.
Parameters

point1 (Marker or Camera) – First endpoint.

point1 – Second endpoint.
Returns Created scale bar.
Return type Scalebar
addScalebarGroup()
Add new scale bar group to the chunk.
Returns Created scale bar group.
Return type ScalebarGroup
addSensor([source ])
Add new sensor to the chunk.
Parameters source (Sensor) – Sensor to copy parameters from.
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Returns Created sensor.
Return type Sensor
addTiledModel()
Add new tiled model to the chunk.
Returns Created tiled model.
Return type TiledModel
alignCameras([cameras][, point_clouds], min_image=2, adaptive_fitting=False, reset_alignment=False,
subdivide_task=True[, progress])
Perform photo alignment for the chunk.
Parameters

cameras (list of int) – List of cameras to align.

point_clouds (list of int) – List of point clouds to align.

min_image (int) – Minimum number of point projections.

adaptive_fitting (bool) – Enable adaptive fitting of distortion coefficients.

reset_alignment (bool) – Reset current alignment.

subdivide_task (bool) – Enable fine-level task subdivision.

progress (Callable[[float], None]) – Progress callback.
analyzeImages([cameras], filter_mask=False[, progress])
Estimate image quality.
Parameters

cameras (list of int) – List of cameras to be analyzed.

filter_mask (bool) – Constrain analyzed image region by mask.

progress (Callable[[float], None]) – Progress callback.
buildContours(source_data=ElevationData, interval=1, min_value=-1e+10, max_value=1e+10,
prevent_intersections=True[, progress])
Build contours for the chunk.
Parameters

source_data (DataSource) – Source data for contour generation.

interval (float) – Contour interval.

min_value (float) – Minimum value of contour range.

max_value (float) – Maximum value of contour range.

prevent_intersections (bool) – Prevent contour intersections.

progress (Callable[[float], None]) – Progress callback.
buildDem(source_data=PointCloudData, interpolation=EnabledInterpolation[, projection ][, region ][,
classes], flip_x=False, flip_y=False, flip_z=False, resolution=0, subdivide_task=True,
workitem_size_tiles=10, max_workgroup_size=100[, progress])
Build elevation model for the chunk.
Parameters

source_data (DataSource) – Selects between point cloud and tie points.
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interpolation (Interpolation) – Interpolation mode.

projection (OrthoProjection) – Output projection.

region (BBox) – Region to be processed.

classes (list of int) – List of point classes to be used for surface extraction.

flip_x (bool) – Flip X axis direction.

flip_y (bool) – Flip Y axis direction.

flip_z (bool) – Flip Z axis direction.

resolution (float) – Output resolution in meters.

subdivide_task (bool) – Enable fine-level task subdivision.

workitem_size_tiles (int) – Number of tiles in a workitem.

max_workgroup_size (int) – Maximum workgroup size.

progress (Callable[[float], None]) – Progress callback.
buildDepthMaps(downscale=4, filter_mode=MildFiltering[, cameras], reuse_depth=False,
max_neighbors=16, subdivide_task=True, workitem_size_cameras=20,
max_workgroup_size=100[, progress])
Generate depth maps for the chunk.
Parameters

downscale (int) – Depth map quality.

filter_mode (FilterMode) – Depth map filtering mode.

cameras (list of int) – List of cameras to process.

reuse_depth (bool) – Enable reuse depth maps option.

max_neighbors (int) – Maximum number of neighbor images to use for depth map generation.

subdivide_task (bool) – Enable fine-level task subdivision.

workitem_size_cameras (int) – Number of cameras in a workitem.

max_workgroup_size (int) – Maximum workgroup size.

progress (Callable[[float], None]) – Progress callback.
buildModel(surface_type=Arbitrary, interpolation=EnabledInterpolation, face_count=HighFaceCount,
face_count_custom=200000, source_data=DepthMapsData[, classes], vertex_colors=True,
vertex_confidence=True, volumetric_masks=False, keep_depth=True, trimming_radius=10[,
cameras], subdivide_task=True, workitem_size_cameras=20, max_workgroup_size=100[,
progress])
Generate model for the chunk frame.
Parameters

surface_type (SurfaceType) – Type of object to be reconstructed.

interpolation (Interpolation) – Interpolation mode.

face_count (FaceCount) – Target face count.

face_count_custom (int) – Custom face count.

source_data (DataSource) – Selects between point cloud, tie points and depth maps.
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classes (list of int) – List of point classes to be used for surface extraction.

vertex_colors (bool) – Enable vertex colors calculation.

vertex_confidence (bool) – Enable vertex confidence calculation.

volumetric_masks (bool) – Enable strict volumetric masking.

keep_depth (bool) – Enable store depth maps option.

trimming_radius (int) – Trimming radius (no trimming if zero).

cameras (list of int) – List of cameras to process.

subdivide_task (bool) – Enable fine-level task subdivision.

workitem_size_cameras (int) – Number of cameras in a workitem.

max_workgroup_size (int) – Maximum workgroup size.

progress (Callable[[float], None]) – Progress callback.
buildOrthomosaic(surface_data=ModelData, blending_mode=MosaicBlending, fill_holes=True,
ghosting_filter=False, cull_faces=False, refine_seamlines=False[, projection ][, region
], resolution=0, resolution_x=0, resolution_y=0, flip_x=False, flip_y=False,
flip_z=False, subdivide_task=True, workitem_size_cameras=20,
workitem_size_tiles=10, max_workgroup_size=100[, progress])
Build orthomosaic for the chunk.
Parameters

surface_data (DataSource) – Orthorectification surface.

blending_mode (BlendingMode) – Orthophoto blending mode.

fill_holes (bool) – Enable hole filling.

ghosting_filter (bool) – Enable ghosting filter.

cull_faces (bool) – Enable back-face culling.

refine_seamlines (bool) – Refine seamlines based on image content.

projection (OrthoProjection) – Output projection.

region (BBox) – Region to be processed.

resolution (float) – Pixel size in meters.

resolution_x (float) – Pixel size in the X dimension in projected units.

resolution_y (float) – Pixel size in the Y dimension in projected units.

flip_x (bool) – Flip X axis direction.

flip_y (bool) – Flip Y axis direction.

flip_z (bool) – Flip Z axis direction.

subdivide_task (bool) – Enable fine-level task subdivision.

workitem_size_cameras (int) – Number of cameras in a workitem.

workitem_size_tiles (int) – Number of tiles in a workitem.

max_workgroup_size (int) – Maximum workgroup size.

progress (Callable[[float], None]) – Progress callback.
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buildPanorama(blending_mode=MosaicBlending, ghosting_filter=False[, rotation ][, region ], width=0,
height=0[, camera_groups][, frames][, progress])
Generate spherical panoramas from camera stations.
Parameters

blending_mode (BlendingMode) – Panorama blending mode.

ghosting_filter (bool) – Enable ghosting filter.

rotation (Matrix) – Panorama 3×3 orientation matrix.

region (BBox) – Region to be generated.

width (int) – Width of output panorama.

height (int) – Height of output panorama.

camera_groups (list of int) – List of camera groups to process.

frames (list of int) – List of frames to process.

progress (Callable[[float], None]) – Progress callback.
buildPointCloud(source_data=DepthMapsData, point_colors=True, point_confidence=False,
keep_depth=True, max_neighbors=100, uniform_sampling=True, points_spacing=0.1[,
asset], subdivide_task=True, workitem_size_cameras=20, max_workgroup_size=100[,
progress])
Generate point cloud for the chunk.
Parameters

source_data (DataSource) – Source data to extract points from.

point_colors (bool) – Enable point colors calculation.

point_confidence (bool) – Enable point confidence calculation.

keep_depth (bool) – Enable store depth maps option.

max_neighbors (int) – Maximum number of neighbor images to use for depth map filtering.

uniform_sampling (bool) – Enable uniform point sampling.

points_spacing (float) – Desired point spacing (m).

asset (int) – Asset to process.

subdivide_task (bool) – Enable fine-level task subdivision.

workitem_size_cameras (int) – Number of cameras in a workitem.

max_workgroup_size (int) – Maximum workgroup size.

progress (Callable[[float], None]) – Progress callback.
buildSeamlines(epsilon=1.5[, progress])
Generate shapes for orthomosaic seamlines.
Parameters

epsilon (float) – Contour simplificaion threshold.

progress (Callable[[float], None]) – Progress callback.
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buildTexture(blending_mode=MosaicBlending, texture_size=8192, fill_holes=True, ghosting_filter=True[,
cameras], texture_type=DiffuseMap[, source_model], transfer_texture=True[, progress])
Generate texture for the chunk.
Parameters

blending_mode (BlendingMode) – Texture blending mode.

texture_size (int) – Texture page size.

fill_holes (bool) – Enable hole filling.

ghosting_filter (bool) – Enable ghosting filter.

cameras (list of int) – A list of cameras to be used for texturing.

texture_type (Model.TextureType) – Texture type.

source_model (int) – Source model.

transfer_texture (bool) – Transfer texture.

progress (Callable[[float], None]) – Progress callback.
buildTiledModel(pixel_size=0, tile_size=256, source_data=DepthMapsData, face_count=20000,
ghosting_filter=False, transfer_texture=False, keep_depth=True, merge=False[,
operand_chunk ][, operand_frame ][, operand_asset][, classes], subdivide_task=True,
workitem_size_cameras=20, max_workgroup_size=100[, progress])
Build tiled model for the chunk.
Parameters

pixel_size (float) – Target model resolution in meters.

tile_size (int) – Size of tiles in pixels.

source_data (DataSource) – Selects between point cloud and mesh.

face_count (int) – Number of faces per megapixel of texture resolution.

ghosting_filter (bool) – Enable ghosting filter.

transfer_texture (bool) – Transfer source model texture to tiled model.

keep_depth (bool) – Enable store depth maps option.

merge (bool) – Merge tiled model flag.

operand_chunk (int) – Operand chunk key.

operand_frame (int) – Operand frame key.

operand_asset (int) – Operand asset key.

classes (list of int) – List of point classes to be used for surface extraction.

subdivide_task (bool) – Enable fine-level task subdivision.

workitem_size_cameras (int) – Number of cameras in a workitem.

max_workgroup_size (int) – Maximum workgroup size.

progress (Callable[[float], None]) – Progress callback.
buildUV(mapping_mode=GenericMapping, page_count=1, texture_size=8192[, camera ][, progress])
Generate uv mapping for the model.
Parameters
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mapping_mode (MappingMode) – Texture mapping mode.

page_count (int) – Number of texture pages to generate.

texture_size (int) – Expected size of texture page at texture generation step.

camera (int) – Camera to be used for texturing in MappingCamera mode.

progress (Callable[[float], None]) – Progress callback.
calculatePointNormals(point_neighbors=28[, point_cloud ][, progress])
Calculate point cloud normals.
Parameters

point_neighbors (int) – Number of point neighbors to use for normal estimation.

point_cloud (int) – Point cloud key to process.

progress (Callable[[float], None]) – Progress callback.
calibrateColors(source_data=ModelData, white_balance=False[, cameras][, progress])
Perform radiometric calibration.
Parameters

source_data (DataSource) – Source data for calibration.

white_balance (bool) – Calibrate white balance.

cameras (list of int) – List of cameras to process.

progress (Callable[[float], None]) – Progress callback.
calibrateReflectance(use_reflectance_panels=True, use_sun_sensor=False[, progress])
Calibrate reflectance factors based on calibration panels and/or sun sensor.
Parameters

use_reflectance_panels (bool) – Use calibrated reflectance panels.

use_sun_sensor (bool) – Apply irradiance sensor measurements.

progress (Callable[[float], None]) – Progress callback.
camera_crs
Coordinate system used for camera reference data.
Type CoordinateSystem
camera_groups
List of camera groups in the chunk.
Type list of CameraGroup
camera_location_accuracy
Expected accuracy of camera coordinates in meters.
Type Vector
camera_rotation_accuracy
Expected accuracy of camera orientation angles in degrees.
Type Vector
camera_track
Camera track.
Type CameraTrack
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camera_tracks
List of camera tracks in the chunk.
Type list of CameraTrack
cameras
List of Regular and Keyframe cameras in the chunk.
Type list of Camera
cir_transform
CIR calibration matrix.
Type CirTransform
colorizeModel(source_data=ImagesData[, progress])
Calculate vertex colors for the model.
Parameters

source_data (DataSource) – Source data to extract colors from.

progress (Callable[[float], None]) – Progress callback.
colorizePointCloud(source_data=ImagesData, workitem_size_cameras=20, max_workgroup_size=100,
subdivide_task=True[, point_cloud ][, progress])
Calculate point colors for the point cloud.
Parameters

source_data (DataSource) – Source data to extract colors from.

workitem_size_cameras (int) – Number of cameras in a workitem.

max_workgroup_size (int) – Maximum workgroup size.

subdivide_task (bool) – Enable fine-level task subdivision.

point_cloud (int) – Point cloud key to colorize.

progress (Callable[[float], None]) – Progress callback.
copy([frames][, items], keypoints=True[, progress])
Make a copy of the chunk.
Parameters

frames (list of Frame) – Optional list of frames to be copied.

items (list of DataSource) – A list of items to copy.

keypoints (bool) – copy key points data.

progress (Callable[[float], None]) – Progress callback.
Returns Copy of the chunk.
Return type Chunk
crs
Coordinate system used for reference data.
Type CoordinateSystem
decimateModel(face_count=200000[, asset], apply_to_selection=False[, progress])
Decimate the model to the specified face count.
Parameters
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face_count (int) – Target face count.

asset (int) – Model to process.

apply_to_selection (bool) – Apply to selection.

progress (Callable[[float], None]) – Progress callback.
depth_maps
Default depth maps set for the current frame.
Type DepthMaps
depth_maps_sets
List of depth maps sets for the current frame.
Type list of DepthMaps
detectFiducials(generate_masks=False, generic_detector=True, right_angle_detector=False,
v_shape_detector=False, fiducials_position_corners=True,
fiducials_position_sides=True[, cameras][, frames][, progress])
Detect fiducial marks on film cameras.
Parameters

generate_masks (bool) – Generate background masks.

generic_detector (bool) – Use generic detector.

right_angle_detector (bool) – Use right angle detector.

v_shape_detector (bool) – Detect V-shape fiducials.

fiducials_position_corners (bool) – Search corners for fiducials.

fiducials_position_sides (bool) – Search sides for fiducials.

cameras (list of int) – List of cameras to process.

frames (list of int) – List of frames to process.

progress (Callable[[float], None]) – Progress callback.
detectMarkers(target_type=CircularTarget12bit, tolerance=50, filter_mask=False, inverted=False,
noparity=False, maximum_residual=5, minimum_size=0, minimum_dist=5[, cameras][,
frames][, progress])
Create markers from coded targets.
Parameters

target_type (TargetType) – Type of targets.

tolerance (int) – Detector tolerance (0 – 100).

filter_mask (bool) – Ignore masked image regions.

inverted (bool) – Detect markers on black background.

noparity (bool) – Disable parity checking.

maximum_residual (float) – Maximum residual for non-coded targets in pixels.

minimum_size (int) – Minimum target radius in pixels to be detected (CrossTarget type
only).

minimum_dist (int) – Minimum distance between targets in pixels (CrossTarget type
only).
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cameras (list of int) – List of cameras to process.

frames (list of int) – List of frames to process.

progress (Callable[[float], None]) – Progress callback.
detectPowerlines(min_altitude=1, n_points_per_line=100, max_quantization_error=0.01,
use_model=True[, progress])
Detect powerlines for the chunk.
Parameters

min_altitude (float) – Minimum altitude for reconstructed powerlines.

n_points_per_line (int) – Maximum number of vertices per detected line.

max_quantization_error (float) – Maximum allowed distance between polyline and
smooth continuous curve.

use_model (bool) – Use model for visibility checks.

progress (Callable[[float], None]) – Progress callback.
elevation
Default elevation model for the current frame.
Type Elevation
elevations
List of elevation models for the current frame.
Type list of Elevation
enabled
Enables/disables the chunk.
Type bool
euler_angles
Euler angles triplet used for rotation reference.
Type EulerAngles
exportCameras(path= », format=CamerasFormatXML[, crs], save_points=True, save_markers=False,
save_invalid_matches=False, use_labels=False, use_initial_calibration=False,
image_orientation=0, chan_rotation_order=RotationOrderXYZ, binary=False,
bundler_save_list=True, bundler_path_list=’list.txt’, bingo_save_image=True,
bingo_save_itera=True, bingo_save_geoin=True, bingo_save_gps=False,
bingo_path_itera=’itera.dat’, bingo_path_image=’image.dat’, bingo_path_geoin=’geoin.dat’,
bingo_path_gps=’gps-imu.dat'[, progress])
Export point cloud and/or camera positions.
Parameters

path (string) – Path to output file.

format (CamerasFormat) – Export format.

crs (CoordinateSystem) – Output coordinate system.

save_points (bool) – Enables/disables export of automatic tie points.

save_markers (bool) – Enables/disables export of manual matching points.

save_invalid_matches (bool) – Enables/disables export of invalid image matches.

use_labels (bool) – Enables/disables label based item identifiers.
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use_initial_calibration (bool) – Transform image coordinates to initial calibration.

image_orientation (int) – Image coordinate system (0 – X right, 1 – X up, 2 – X left, 3

X down).

chan_rotation_order (RotationOrder) – Rotation order (CHAN format only).

binary (bool) – Enables/disables binary encoding for selected format (if applicable).

bundler_save_list (bool) – Enables/disables export of Bundler image list file.

bundler_path_list (string) – Path to Bundler image list file.

bingo_save_image (bool) – Enables/disables export of BINGO IMAGE COORDINATE file.

bingo_save_itera (bool) – Enables/disables export of BINGO ITERA file.

bingo_save_geoin (bool) – Enables/disables export of BINGO GEO INPUT file.

bingo_save_gps (bool) – Enables/disables export of BINGO GPS/IMU data.

bingo_path_itera (string) – Path to BINGO ITERA file.

bingo_path_image (string) – Path to BINGO IMAGE COORDINATE file.

bingo_path_geoin (string) – Path to BINGO GEO INPUT file.

bingo_path_gps (string) – Path to BINGO GPS/IMU file.

progress (Callable[[float], None]) – Progress callback.
exportMarkers(path= »[, crs], binary=False[, progress])
Export markers.
Parameters

path (string) – Path to output file.

crs (CoordinateSystem) – Output coordinate system.

binary (bool) – Enables/disables binary encoding for selected format (if applicable).

progress (Callable[[float], None]) – Progress callback.
exportModel(path= », binary=True, precision=6, texture_format=ImageFormatJPEG, save_texture=True,
save_uv=True, save_normals=True, save_colors=True, save_confidence=False,
save_cameras=True, save_markers=True, save_udim=False, save_alpha=False,
embed_texture=False, strip_extensions=False, raster_transform=RasterTransformNone,
colors_rgb_8bit=True, comment= », save_comment=True, format=ModelFormatNone[, crs][,
shift], clip_to_boundary=True, save_metadata_xml=False[, model][, viewpoint][, progress
])
Export generated model for the chunk.
Parameters

path (string) – Path to output model.

binary (bool) – Enables/disables binary encoding (if supported by format).

precision (int) – Number of digits after the decimal point (for text formats).

texture_format (ImageFormat) – Texture format.

save_texture (bool) – Enables/disables texture export.

save_uv (bool) – Enables/disables uv coordinates export.
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save_normals (bool) – Enables/disables export of vertex normals.

save_colors (bool) – Enables/disables export of vertex colors.

save_confidence (bool) – Enables/disables export of vertex confidence.

save_cameras (bool) – Enables/disables camera export.

save_markers (bool) – Enables/disables marker export.

save_udim (bool) – Enables/disables UDIM texture layout.

save_alpha (bool) – Enables/disables alpha channel export.

embed_texture (bool) – Embeds texture inside the model file (if supported by format).

strip_extensions (bool) – Strips camera label extensions during export.

raster_transform (RasterTransformType) – Raster band transformation.

colors_rgb_8bit (bool) – Convert colors to 8 bit RGB.

comment (string) – Optional comment (if supported by selected format).

save_comment (bool) – Enables/disables comment export.

format (ModelFormat) – Export format.

crs (CoordinateSystem) – Output coordinate system.

shift (Vector) – Optional shift to be applied to vertex coordinates.

clip_to_boundary (bool) – Clip model to boundary shapes.

save_metadata_xml (bool) – Save metadata.xml file.

model (int) – Model key to export.

viewpoint (Viewpoint) – Default view.

progress (Callable[[float], None]) – Progress callback.
exportOrthophotos(path='{filename}.tif'[, cameras], raster_transform=RasterTransformNone[, projection
][, region ], resolution=0, resolution_x=0, resolution_y=0, save_kml=False,
save_world=False, save_alpha=True[, image_compression ], white_background=True,
north_up=True[, progress])
Export orthophotos for the chunk.
Parameters

path (string) – Path to output orthophoto.

cameras (list of int) – List of cameras to process.

raster_transform (RasterTransformType) – Raster band transformation.

projection (OrthoProjection) – Output projection.

region (BBox) – Region to be exported.

resolution (float) – Output resolution in meters.

resolution_x (float) – Pixel size in the X dimension in projected units.

resolution_y (float) – Pixel size in the Y dimension in projected units.

save_kml (bool) – Enable kml file generation.

save_world (bool) – Enable world file generation.
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save_alpha (bool) – Enable alpha channel generation.

image_compression (ImageCompression) – Image compression parameters.

white_background (bool) – Enable white background.

north_up (bool) – Use north-up orientation for export.

progress (Callable[[float], None]) – Progress callback.
exportPointCloud(path= », source_data=PointCloudData[, point_cloud ], binary=True,
save_point_color=True, save_point_normal=True, save_point_intensity=True,
save_point_classification=True, save_point_confidence=True,
save_point_return_number=True, save_point_scan_angle=True,
save_point_source_id=True, save_point_timestamp=True, save_point_index=True,
raster_transform=RasterTransformNone, colors_rgb_8bit=True, comment= »,
save_comment=True, format=PointCloudFormatNone,
image_format=ImageFormatJPEG[, crs][, shift][, region ], clip_to_boundary=True,
block_width=1000, block_height=1000, split_in_blocks=False[, classes],
save_images=False, compression=True, screen_space_error=16, folder_depth=5[,
viewpoint], subdivide_task=True[, progress])
Export point cloud.
Parameters

path (string) – Path to output file.

source_data (DataSource) – Selects between point cloud and tie points. If not specified,
uses point cloud if available.

point_cloud (int) – Point cloud key to export.

binary (bool) – Enables/disables binary encoding for selected format (if applicable).

save_point_color (bool) – Enables/disables export of point color.

save_point_normal (bool) – Enables/disables export of point normal.

save_point_intensity (bool) – Enables/disables export of point intensity.

save_point_classification (bool) – Enables/disables export of point classification.

save_point_confidence (bool) – Enables/disables export of point confidence.

save_point_return_number (bool) – Enables/disables export of point return number.

save_point_scan_angle (bool) – Enables/disables export of point scan angle.

save_point_source_id (bool) – Enables/disables export of point source ID.

save_point_timestamp (bool) – Enables/disables export of point timestamp.

save_point_index (bool) – Enables/disables export of point row and column indices.

raster_transform (RasterTransformType) – Raster band transformation.

colors_rgb_8bit (bool) – Convert colors to 8 bit RGB.

comment (string) – Optional comment (if supported by selected format).

save_comment (bool) – Enable comment export.

format (PointCloudFormat) – Export format.

image_format (ImageFormat) – Image data format.

crs (CoordinateSystem) – Output coordinate system.
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shift (Vector) – Optional shift to be applied to point coordinates.

region (BBox) – Region to be exported.

clip_to_boundary (bool) – Clip point cloud to boundary shapes.

block_width (float) – Block width in meters.

block_height (float) – Block height in meters.

split_in_blocks (bool) – Enable tiled export.

classes (list of int) – List of point classes to be exported.

save_images (bool) – Enable image export.

compression (bool) – Enable compression (Cesium format only).

screen_space_error (float) – Target screen space error (Cesium format only).

folder_depth (int) – Tileset subdivision depth (Cesium format only).

viewpoint (Viewpoint) – Default view.

subdivide_task (bool) – Enable fine-level task subdivision.

progress (Callable[[float], None]) – Progress callback.
exportRaster(path= », format=RasterFormatTiles, image_format=ImageFormatNone,
raster_transform=RasterTransformNone[, projection ][, region ], resolution=0,
resolution_x=0, resolution_y=0, block_width=10000, block_height=10000,
split_in_blocks=False, width=0, height=0[, world_transform ], nodata_value=-32767,
save_kml=False, save_world=False, save_scheme=False, save_alpha=True,
image_description= »[, image_compression ], network_links=True, global_profile=False,
min_zoom_level=-1, max_zoom_level=-1, white_background=True, clip_to_boundary=True,
title=’Orthomosaic’, description=’Generated by Agisoft Metashape’,
source_data=OrthomosaicData, north_up=True, tile_width=256, tile_height=256[, progress
])
Export DEM or orthomosaic to file.
Parameters

path (string) – Path to output orthomosaic.

format (RasterFormat) – Export format.

image_format (ImageFormat) – Tile format.

raster_transform (RasterTransformType) – Raster band transformation.

projection (OrthoProjection) – Output projection.

region (BBox) – Region to be exported.

resolution (float) – Output resolution in meters.

resolution_x (float) – Pixel size in the X dimension in projected units.

resolution_y (float) – Pixel size in the Y dimension in projected units.

block_width (int) – Raster block width in pixels.

block_height (int) – Raster block height in pixels.

split_in_blocks (bool) – Split raster in blocks.

width (int) – Raster width.
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height (int) – Raster height.

world_transform (Matrix) – 2×3 raster-to-world transformation matrix.

nodata_value (float) – No-data value (DEM export only).

save_kml (bool) – Enable kml file generation.

save_world (bool) – Enable world file generation.

save_scheme (bool) – Enable tile scheme files generation.

save_alpha (bool) – Enable alpha channel generation.

image_description (string) – Optional description to be added to image files.

image_compression (ImageCompression) – Image compression parameters.

network_links (bool) – Enable network links generation for KMZ format.

global_profile (bool) – Use global profile (GeoPackage format only).

min_zoom_level (int) – Minimum zoom level (GeoPackage, Google Map Tiles,
MBTiles and World Wind Tiles formats only).

max_zoom_level (int) – Maximum zoom level (GeoPackage, Google Map Tiles,
MBTiles and World Wind Tiles formats only).

white_background (bool) – Enable white background.

clip_to_boundary (bool) – Clip raster to boundary shapes.

title (string) – Export title.

description (string) – Export description.

source_data (DataSource) – Selects between DEM and orthomosaic.

north_up (bool) – Use north-up orientation for export.

tile_width (int) – Tile width in pixels.

tile_height (int) – Tile height in pixels.

progress (Callable[[float], None]) – Progress callback.
exportReference(path= », format=ReferenceFormatNone, items=ReferenceItemsCameras, columns= »,
delimiter=’ ‘, precision=6[, progress])
Export reference data to the specified file.
Parameters

path (string) – Path to the output file.

format (ReferenceFormat) – Export format.

items (ReferenceItems) – Items to export in CSV format.

columns (string) – Column order in csv format (n – label, o – enabled flag, x/y/z – coordinates, X/Y/Z – coordinate accuracy, a/b/c – rotation angles, A/B/C – rotation angle accuracy,
u/v/w – estimated coordinates, U/V/W – coordinate errors, d/e/f – estimated orientation angles, D/E/F – orientation errors, p/q/r – estimated coordinates variance, i/j/k – estimated orientation angles variance, [] – group of multiple values, | – column separator within group).

delimiter (string) – Column delimiter in csv format.

precision (int) – Number of digits after the decimal point (for CSV format).

progress (Callable[[float], None]) – Progress callback.
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exportReport(path= », title= », description= », font_size=12, page_numbers=True,
include_system_info=True[, user_settings][, progress])
Export processing report in PDF format.
Parameters

path (string) – Path to output report.

title (string) – Report title.

description (string) – Report description.

font_size (int) – Font size (pt).

page_numbers (bool) – Enable page numbers.

include_system_info (bool) – Include system information.

user_settings (list of (string, string) tuples) – A list of user defined settings to include on the Processing Parameters page.

progress (Callable[[float], None]) – Progress callback.
exportShapes(path= », save_points=False, save_polylines=False, save_polygons=False[, groups],
format=ShapesFormatNone[, crs][, shift], polygons_as_polylines=False, save_labels=True,
save_attributes=True[, progress])
Export shapes layer to file.
Parameters

path (string) – Path to shape file.

save_points (bool) – Export points.

save_polylines (bool) – Export polylines.

save_polygons (bool) – Export polygons.

groups (list of int) – A list of shape groups to export.

format (ShapesFormat) – Export format.

crs (CoordinateSystem) – Output coordinate system.

shift (Vector) – Optional shift to be applied to vertex coordinates.

polygons_as_polylines (bool) – Save polygons as polylines.

save_labels (bool) – Export labels.

save_attributes (bool) – Export attributes.

progress (Callable[[float], None]) – Progress callback.
exportTexture(path= », texture_type=DiffuseMap, raster_transform=RasterTransformNone,
save_alpha=False[, progress])
Export model texture to file.
Parameters

path (string) – Path to output file.

texture_type (Model.TextureType) – Texture type.

raster_transform (RasterTransformType) – Raster band transformation.

save_alpha (bool) – Enable alpha channel export.

progress (Callable[[float], None]) – Progress callback.
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exportTiledModel(path= », format=TiledModelFormatNone, model_format=ModelFormatCOLLADA,
texture_format=ImageFormatJPEG, raster_transform=RasterTransformNone[,
image_compression ][, crs], clip_to_boundary=True, model_compression=True,
use_rtc_center=False, screen_space_error=16, folder_depth=5[, progress])
Export generated tiled model for the chunk.
Parameters

path (string) – Path to output model.

format (TiledModelFormat) – Export format.

model_format (ModelFormat) – Model format for zip export.

texture_format (ImageFormat) – Texture format.

raster_transform (RasterTransformType) – Raster band transformation.

image_compression (ImageCompression) – Image compression parameters.

crs (CoordinateSystem) – Output coordinate system.

clip_to_boundary (bool) – Clip tiled model to boundary shapes.

model_compression (bool) – Enable mesh compression (Cesium format only).

use_rtc_center (bool) – Use RTC_CENTER offset instead of root tile transform (Cesium format only).

screen_space_error (float) – Target screen space error (Cesium format only).

folder_depth (int) – Tileset subdivision depth (Cesium format only).

progress (Callable[[float], None]) – Progress callback.
filterPointCloud(point_spacing=0[, point_cloud ][, progress])
Reduce point cloud points number.
Parameters

point_spacing (float) – Desired point spacing (m).

point_cloud (int) – Point cloud key to filter.

progress (Callable[[float], None]) – Progress callback.
findCamera(key)
Find camera by its key.
Returns Found camera.
Return type Camera
findCameraGroup(key)
Find camera group by its key.
Returns Found camera group.
Return type CameraGroup
findCameraTrack(key)
Find camera track by its key.
Returns Found camera track.
Return type CameraTrack
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findDepthMaps(key)
Find depth maps by its key.
Returns Found depth maps.
Return type DepthMaps
findElevation(key)
Find elevation model by its key.
Returns Found elevation model.
Return type Elevation
findFrame(key)
Find frame by its key.
Returns Found frame.
Return type Chunk
findMarker(key)
Find marker by its key.
Returns Found marker.
Return type Marker
findMarkerGroup(key)
Find marker group by its key.
Returns Found marker group.
Return type MarkerGroup
findModel(key)
Find model by its key.
Returns Found model.
Return type Model
findOrthomosaic(key)
Find orthomosaic by its key.
Returns Found orthomosaic.
Return type Orthomosaic
findPointCloud(key)
Find point cloud by its key.
Returns Found point cloud.
Return type PointCloud
findPointCloudGroup(key)
Find point cloud group by its key.
Parameters key (int) – Point cloud group key.
Returns Found point cloud group.
Return type PointCloudGroup
findScalebar(key)
Find scalebar by its key.
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Returns Found scalebar.
Return type Scalebar
findScalebarGroup(key)
Find scalebar group by its key.
Returns Found scalebar group.
Return type ScalebarGroup
findSensor(key)
Find sensor by its key.
Returns Found sensor.
Return type Sensor
findTiledModel(key)
Find tiled model by its key.
Returns Found tiled model.
Return type TiledModel
frame
Current frame index.
Type int
frames
List of frames in the chunk.
Type list of Frame
generateMasks(path='{filename}_mask.png’, masking_mode=MaskingModeAlpha,
mask_operation=MaskOperationReplacement, tolerance=10[, cameras],
mask_defocus=False, fix_coverage=True, blur_threshold=3,
depth_threshold=3.40282e+38[, progress])
Generate masks for multiple cameras.
Parameters

path (string) – Mask file name template.

masking_mode (MaskingMode) – Mask generation mode.

mask_operation (MaskOperation) – Mask operation.

tolerance (int) – Background masking tolerance.

cameras (list of int) – Optional list of cameras to be processed.

mask_defocus (bool) – Mask defocus areas.

fix_coverage (bool) – Extend masks to cover whole mesh (only if mask_defocus=True).

blur_threshold (float) – Allowed blur radius on a photo in pix (only if
mask_defocus=True).

depth_threshold (float) – Maximum depth of masked areas in meters (only if
mask_defocus=False).

progress (Callable[[float], None]) – Progress callback.
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generatePrescriptionMap(class_count=4, cell_size=1,
classification_method=JenksNaturalBreaksClassification[,
boundary_shape_group ][, breakpoints][, rates][, progress])
Generate prescription map for orthomosaic.
Parameters

class_count (int) – Number of classes.

cell_size (float) – Step of prescription grid, meters.

classification_method (ClassificationMethod) – Index values classification
method.

boundary_shape_group (int) – Boundary shape group.

breakpoints (list of float) – Classification breakpoints.

rates (list of float) – Fertilizer rate for each class.

progress (Callable[[float], None]) – Progress callback.
image_brightness
Image brightness as percentage.
Type float
image_contrast
Image contrast as percentage.
Type float
importCameras(path= », format=CamerasFormatXML[, crs], image_orientation=0, image_list=’list.txt’,
load_image_list=False[, progress])
Import camera positions.
Parameters

path (string) – Path to the file.

format (CamerasFormat) – File format.

crs (CoordinateSystem) – Ground coordinate system.

image_orientation (int) – Image coordinate system (0 – X right, 1 – X up, 2 – X left, 3

X down).

image_list (string) – Path to image list file (Bundler format only).

load_image_list (bool) – Enable Bundler image list import.

progress (Callable[[float], None]) – Progress callback.
importDepthImages(format=PointCloudFormatNone[, filenames][, color_filenames], image_path= »,
multiplane=False[, progress])
Import images with depth data.
Parameters

format (PointCloudFormat) – Point cloud format.

filenames (list of string) – List of files to import.

color_filenames (list of string) – List of corresponding color files, if present.

image_path (string) – Path template to output files.

multiplane (bool) – Import as a multi-camera system
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progress (Callable[[float], None]) – Progress callback.
importMarkers(path= »[, progress])
Import markers.
Parameters

path (string) – Path to the file.

progress (Callable[[float], None]) – Progress callback.
importModel(path= », format=ModelFormatNone[, crs][, shift], decode_udim=True[, progress])
Import model from file.
Parameters

path (string) – Path to model.

format (ModelFormat) – Model format.

crs (CoordinateSystem) – Model coordinate system.

shift (Vector) – Optional shift to be applied to vertex coordinates.

decode_udim (bool) – Load UDIM texture layout.

progress (Callable[[float], None]) – Progress callback.
importPointCloud(path= », format=PointCloudFormatNone[, crs][, shift], precision=0,
is_laser_scan=False, replace_asset=False, import_images=True,
calculate_normals=True, point_neighbors=28, scanner_at_origin=False,
ignore_scanner_origin=False, ignore_trajectory=False[, trajectory ][, frame_paths][,
progress])
Import point cloud from file.
Parameters

path (string) – Path to point cloud.

format (PointCloudFormat) – Point cloud format.

crs (CoordinateSystem) – Point cloud coordinate system.

shift (Vector) – Optional shift to be applied to point coordinates.

precision (float) – Coordinate precision (m).

is_laser_scan (bool) – Import point clouds as laser scans.

replace_asset (bool) – Replace default asset with imported point cloud.

import_images (bool) – Import images embedded in laser scan.

calculate_normals (bool) – Calculate point normals.

point_neighbors (int) – Number of point neighbors to use for normal estimation.

scanner_at_origin (bool) – Use laser scan origin as scanner position for unstructured
point clouds.

ignore_scanner_origin (bool) – Do not use laser scan origin as scanner position for
structured point clouds.

ignore_trajectory (bool) – Do not attach trajectory to imported point cloud.

trajectory (int) – Trajectory key to attach.
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frame_paths (list of string) – List of point cloud paths to import in each frame of
a multiframe chunk.

progress (Callable[[float], None]) – Progress callback.
importRaster(path= »[, crs], raster_type=ElevationData, nodata_value=-32767,
has_nodata_value=False[, progress])
Import DEM or orthomosaic from file.
Parameters

path (string) – Path to elevation model in GeoTIFF format.

crs (CoordinateSystem) – Default coordinate system if not specified in GeoTIFF file.

raster_type (DataSource) – Type of raster layer to import.

nodata_value (float) – No-data value.

has_nodata_value (bool) – No-data value valid flag.

progress (Callable[[float], None]) – Progress callback.
importReference(path= », format=ReferenceFormatCSV, columns= », delimiter= », group_delimiters=False,
skip_rows=0[, items][, crs], ignore_labels=False, create_markers=False,
threshold=0.1, shutter_lag=0[, progress])
Import reference data from the specified file.
Parameters

path (string) – Path to the file with reference data.

format (ReferenceFormat) – File format.

columns (string) – Column order in csv format (n – label, o – enabled flag, x/y/z – coordinates, X/Y/Z – coordinate accuracy, a/b/c – rotation angles, A/B/C – rotation angle accuracy,
[] – group of multiple values, | – column separator within group).

delimiter (string) – Column delimiter in csv format.

group_delimiters (bool) – Combine consecutive delimiters in csv format.

skip_rows (int) – Number of rows to skip in (csv format only).

items (ReferenceItems) – List of items to load reference for (csv format only).

crs (CoordinateSystem) – Reference data coordinate system (csv format only).

ignore_labels (bool) – Matches reference data based on coordinates alone (csv format
only).

create_markers (bool) – Create markers for missing entries (csv format only).

threshold (float) – Error threshold in meters used when ignore_labels is set (csv format
only).

shutter_lag (float) – Shutter lag in seconds (APM format only).

progress (Callable[[float], None]) – Progress callback.
importShapes(path= », replace=False, boundary_type=NoBoundary, format=ShapesFormatNone,
columns=’nxyzd’, delimiter=’, ‘, group_delimiters=False, skip_rows=0[, crs][, progress])
Import shapes layer from file.
Parameters

path (string) – Path to shape file.
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replace (bool) – Replace current shapes with new data.

boundary_type (Shape.BoundaryType) – Boundary type to be applied to imported
shapes.

format (ShapesFormat) – Shapes format.

columns (string) – Column order in csv format (n – label, x/y/z – coordinates, d – description, [] – group of multiple values, | – column separator within group).

delimiter (string) – Column delimiter in csv format.

group_delimiters (bool) – Combine consequitive delimiters in csv format.

skip_rows (int) – Number of rows to skip in (csv format only).

crs (CoordinateSystem) – Reference data coordinate system (csv format only).

progress (Callable[[float], None]) – Progress callback.
importTiledModel(path= »[, progress])
Import tiled model from file.
Parameters

path (string) – Path to tiled model.

progress (Callable[[float], None]) – Progress callback.
importTrajectory(path= », format=TrajectoryFormatNone, columns=’txyz’, delimiter=’ ‘, skip_rows=0[,
crs][, shift], replace_asset=False[, progress])
Import trajectory from file.
Parameters

path (string) – Trajectory file path.

format (TrajectoryFormat) – Trajectory format.

columns (string) – Column order (t – time, x/y/z – coordinates, space – skip column).

delimiter (string) – CSV delimiter.

skip_rows (int) – Number of rows to skip.

crs (CoordinateSystem) – Point cloud coordinate system.

shift (Vector) – Optional shift to be applied to point coordinates.

replace_asset (bool) – Replace default asset with imported point cloud.

progress (Callable[[float], None]) – Progress callback.
importVideo(path, image_path, frame_step=CustomFrameStep, custom_frame_step=1, time_start=0,
time_end=- 1)
Imports video to active chunk.
Parameters

path (string) – Path to source video.

image_path (string) – Path to directory where to save frames with filename template.
For example: /path/to/dir/frame{filenum}.png.

frame_step (FrameStep) – Frame step type.

custom_frame_step (int) – Every custom_frame_step’th frame will be saved. Used for
frame_step=CustomFrameStep.
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time_start (int) – The starting point for importing video, in milliseconds.

time_end (int) – The endpoint for importing video, in milliseconds.
key
Chunk identifier.
Type int
label
Chunk label.
Type string
loadReferenceExif(load_rotation=False, load_accuracy=False)
Import camera locations from EXIF meta data.
Parameters

load_rotation (bool) – load yaw, pitch and roll orientation angles.

load_accuracy (bool) – load camera location accuracy.
loadReflectancePanelCalibration(path[, cameras])
Load reflectance panel calibration from CSV file.
Parameters

path (string) – Path to calibration file.

cameras (list of Camera) – List of cameras to process.
locateReflectancePanels([progress])
Locate reflectance panels based on QR-codes.
Parameters progress (Callable[[float], None]) – Progress callback.
marker_crs
Coordinate system used for marker reference data.
Type CoordinateSystem
marker_groups
List of marker groups in the chunk.
Type list of MarkerGroup
marker_location_accuracy
Expected accuracy of marker coordinates in meters.
Type Vector
marker_projection_accuracy
Expected accuracy of marker projections in pixels.
Type float
markers
List of Regular, Vertex and Fiducial markers in the chunk.
Type list of Marker
masks
Image masks.
Type Masks
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matchPhotos(downscale=1, generic_preselection=True, reference_preselection=True,
reference_preselection_mode=ReferencePreselectionSource, filter_mask=False,
mask_tiepoints=True, filter_stationary_points=True, keypoint_limit=40000,
keypoint_limit_per_mpx=1000, tiepoint_limit=4000, keep_keypoints=False[, pairs][,
cameras], guided_matching=False, reset_matches=False, subdivide_task=True,
workitem_size_cameras=20, workitem_size_pairs=80, max_workgroup_size=100[, progress
])
Perform image matching for the chunk frame.
Parameters

downscale (int) – Image alignment accuracy.

generic_preselection (bool) – Enable generic preselection.

reference_preselection (bool) – Enable reference preselection.

reference_preselection_mode (ReferencePreselectionMode) – Reference preselection mode.

filter_mask (bool) – Filter points by mask.

mask_tiepoints (bool) – Apply mask filter to tie points.

filter_stationary_points (bool) – Exclude tie points which are stationary across
images.

keypoint_limit (int) – Key point limit.

keypoint_limit_per_mpx (int) – Key point limit per megapixel.

tiepoint_limit (int) – Tie point limit.

keep_keypoints (bool) – Store keypoints in the project.

pairs (list of (int, int) tuples) – User defined list of camera pairs to match.

cameras (list of int) – List of cameras to match.

guided_matching (bool) – Enable guided image matching.

reset_matches (bool) – Reset current matches.

subdivide_task (bool) – Enable fine-level task subdivision.

workitem_size_cameras (int) – Number of cameras in a workitem.

workitem_size_pairs (int) – Number of image pairs in a workitem.

max_workgroup_size (int) – Maximum workgroup size.

progress (Callable[[float], None]) – Progress callback.
meta
Chunk meta data.
Type MetaData
model
Default model for the current frame.
Type Model
models
List of models for the current frame.
Type list of Model
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modified
Modified flag.
Type bool
optimizeCameras(fit_f=True, fit_cx=True, fit_cy=True, fit_b1=False, fit_b2=False, fit_k1=True,
fit_k2=True, fit_k3=True, fit_k4=False, fit_p1=True, fit_p2=True, fit_corrections=False,
adaptive_fitting=False, tiepoint_covariance=False[, progress])
Perform optimization of tie points / camera parameters.
Parameters

fit_f (bool) – Enable optimization of focal length coefficient.

fit_cx (bool) – Enable optimization of X principal point coordinates.

fit_cy (bool) – Enable optimization of Y principal point coordinates.

fit_b1 (bool) – Enable optimization of aspect ratio.

fit_b2 (bool) – Enable optimization of skew coefficient.

fit_k1 (bool) – Enable optimization of k1 radial distortion coefficient.

fit_k2 (bool) – Enable optimization of k2 radial distortion coefficient.

fit_k3 (bool) – Enable optimization of k3 radial distortion coefficient.

fit_k4 (bool) – Enable optimization of k3 radial distortion coefficient.

fit_p1 (bool) – Enable optimization of p1 tangential distortion coefficient.

fit_p2 (bool) – Enable optimization of p2 tangential distortion coefficient.

fit_corrections (bool) – Enable optimization of additional corrections.

adaptive_fitting (bool) – Enable adaptive fitting of distortion coefficients.

tiepoint_covariance (bool) – Estimate tie point covariance matrices.

progress (Callable[[float], None]) – Progress callback.
orthomosaic
Default orthomosaic for the current frame.
Type Orthomosaic
orthomosaics
List of orthomosaics for the current frame.
Type list of Orthomosaic
point_cloud
Default point cloud for the current frame.
Type PointCloud
point_cloud_groups
List of point cloud groups in the chunk.
Type list of PointCloudGroup
point_clouds
List of point clouds for the current frame.
Type list of PointCloud
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primary_channel
Primary channel index (-1 for default).
Type int
publishData(service=ServiceSketchfab, source_data=TiePointsData,
raster_transform=RasterTransformNone, save_point_color=True, save_camera_track=True,
title= », description= », tags= », owner= », token= », username= », password= », account= »,
hostname= », is_draft=False, is_private=False, is_protected=False, tile_size=256,
min_zoom_level=-1, max_zoom_level=-1[, projection ], resolution=0[, point_classes][,
image_compression ][, progress])
Publish generated data online.
Parameters

service (ServiceType) – Service to upload on.

source_data (DataSource) – Asset type to upload.

raster_transform (RasterTransformType) – Raster band transformation.

save_point_color (bool) – Enables/disables export of point colors.

save_camera_track (bool) – Enables/disables export of camera track.

title (string) – Dataset title.

description (string) – Dataset description.

tags (string) – Dataset tags.

owner (string) – Account owner (Cesium and Mapbox services).

token (string) – Account token (Cesium, Mapbox, Picterra, Pointbox and Sketchfab
services).

username (string) – Account username (4DMapper, Melown and Pointscene services).

password (string) – Account password (4DMapper, Melown, Pointscene and Sketchfab
services).

account (string) – Account name (Melown service).

hostname (string) – Service hostname (4DMapper service).

is_draft (bool) – Mark dataset as draft (Sketchfab service).

is_private (bool) – Set dataset access to private (Pointbox and Sketchfab services).

is_protected (bool) – Set dataset access to protected (Pointbox service).

tile_size (int) – Tile size in pixels.

min_zoom_level (int) – Minimum zoom level.

max_zoom_level (int) – Maximum zoom level.

projection (CoordinateSystem) – Output projection.

resolution (float) – Output resolution in meters.

point_classes (list of int) – List of point classes to be exported.

image_compression (ImageCompression) – Image compression parameters.

progress (Callable[[float], None]) – Progress callback.
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raster_transform
Raster transform.
Type RasterTransform
reduceOverlap(overlap=3, use_selection=False[, progress])
Disable redundant cameras.
Parameters

overlap (int) – Target number of cameras observing each point of the surface.

use_selection (bool) – Focus on model selection.

progress (Callable[[float], None]) – Progress callback.
refineMarkers([markers][, progress])
Refine markers based on images content.
Parameters

markers (list of int) – Optional list of markers to be processed.

progress (Callable[[float], None]) – Progress callback.
refineMesh(downscale=4, iterations=10, smoothness=0.5[, cameras][, progress])
Generate model for the chunk frame.
Parameters

downscale (int) – Refinement quality.

iterations (int) – Number of refinement iterations.

smoothness (float) – Smoothing strength. Should be in range [0, 1].

cameras (list of int) – List of cameras to process.

progress (Callable[[float], None]) – Progress callback.
region
Reconstruction volume selection.
Type Region
remove(items)
Remove items from the chunk.
Parameters items (list of Frame, Sensor, CameraGroup, MarkerGroup, ScalebarGroup,
Camera, Marker, Scalebar or CameraTrack) – A list of items to be removed.
removeLighting(color_mode=False, internal_blur=1.5, mesh_noise_suppression=1,
ambient_occlusion_path= », ambient_occlusion_multiplier=1.5[, progress])
Generate model for the chunk frame.
Parameters

color_mode (bool) – Enable multi-color processing mode.

internal_blur (float) – Internal blur. Should be in range [0, 4].

mesh_noise_suppression (float) – Mesh normals noise suppression strength. Should
be in range [0, 4].

ambient_occlusion_path (string) – Path to ambient occlusion texture atlas. Can be
empty.
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ambient_occlusion_multiplier (float) – Ambient occlusion multiplier. Should be
in range [0.25, 4].

progress (Callable[[float], None]) – Progress callback.
renderPreview(width = 2048, height = 2048[, transform ], point_size=1[, progress])
Generate preview image for the chunk.
Parameters

width (int) – Preview image width.

height (int) – Preview image height.

transform (Matrix) – 4×4 viewpoint transformation matrix.

point_size (int) – Point size.

progress (Callable[[float], None]) – Progress callback.
Returns Preview image.
Return type Image
resetRegion()
Reset reconstruction volume selector to default position.
scalebar_accuracy
Expected scale bar accuracy in meters.
Type float
scalebar_groups
List of scale bar groups in the chunk.
Type list of ScalebarGroup
scalebars
List of scale bars in the chunk.
Type list of Scalebar
selected
Selects/deselects the chunk.
Type bool
sensors
List of sensors in the chunk.
Type list of Sensor
shapes
Shapes for the current frame.
Type Shapes
smoothModel(strength=3, apply_to_selection=False, fix_borders=True, preserve_edges=False[, progress])
Smooth mesh using Laplacian smoothing algorithm.
Parameters

strength (float) – Smoothing strength.

apply_to_selection (bool) – Apply to selected faces.

fix_borders (bool) – Fix borders.
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preserve_edges (bool) – Preserve edges.

progress (Callable[[float], None]) – Progress callback.
sortCameras()
Sorts cameras by their labels.
sortMarkers()
Sorts markers by their labels.
sortScalebars()
Sorts scalebars by their labels.
thinTiePoints(point_limit=1000)
Remove excessive tracks from the tie point cloud.
Parameters point_limit (int) – Maximum number of points for each photo.
thumbnails
Image thumbnails.
Type Thumbnails
tie_points
Generated tie point cloud.
Type TiePoints
tiepoint_accuracy
Expected tie point accuracy in pixels.
Type float
tiled_model
Default tiled model for the current frame.
Type TiledModel
tiled_models
List of tiled models for the current frame.
Type list of TiledModel
trackMarkers(first_frame=0, last_frame=0[, progress])
Track marker projections through the frame sequence.
Parameters

first_frame (int) – Starting frame index.

last_frame (int) – Ending frame index.

progress (Callable[[float], None]) – Progress callback.
transform
4×4 matrix specifying chunk location in the world coordinate system.
Type ChunkTransform
transformRaster(data_source=ElevationData[, asset], subtract=False[, operand_chunk ][,
operand_frame ][, operand_asset], width=0, height=0[, world_transform ],
resolution=0, resolution_x=0, resolution_y=0, nodata_value=-32767, north_up=True[,
region ][, projection ][, progress])
Transform DEM or orthomosaic.
Parameters
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data_source (DataSource) – Selects between DEM and orthomosaic.

asset (int) – Asset key to transform.

subtract (bool) – Subtraction flag.

operand_chunk (int) – Operand chunk key.

operand_frame (int) – Operand frame key.

operand_asset (int) – Operand asset key.

width (int) – Raster width.

height (int) – Raster height.

world_transform (Matrix) – 2×3 raster-to-world transformation matrix.

resolution (float) – Output resolution in meters.

resolution_x (float) – Pixel size in the X dimension in projected units.

resolution_y (float) – Pixel size in the Y dimension in projected units.

nodata_value (float) – No-data value (DEM export only).

north_up (bool) – Use north-up orientation for export.

region (BBox) – Region to be processed.

projection (OrthoProjection) – Output projection.

progress (Callable[[float], None]) – Progress callback.
triangulateTiePoints(max_error=10, min_image=2[, progress])
Rebuild tie point cloud for the chunk.
Parameters

max_error (float) – Reprojection error threshold.

min_image (int) – Minimum number of point projections.

progress (Callable[[float], None]) – Progress callback.
updateTransform()
Update chunk transformation based on reference data.
world_crs
Coordinate system used as world coordinate system.
Type CoordinateSystem
class Metashape.ChunkTransform
Transformation between chunk and world coordinates systems.
copy()
Return a copy of the object.
Returns A copy of the object.
Return type ChunkTransform
matrix
Transformation matrix.
Type Matrix
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rotation
Rotation component.
Type Matrix
scale
Scale component.
Type float
translation
Translation component.
Type Vector
class Metashape.CirTransform
CIR calibration matrix.
calibrate()
Calibrate CIR matrix based on orthomosaic histogram.
coeffs
Color matrix.
Type Matrix
copy()
Return a copy of the object.
Returns A copy of the object.
Return type CirTransform
reset()
Reset CIR calibration matrix.
class Metashape.ClassificationMethod
Index values classification method in [EqualIntervalsClassification, JenksNaturalBreaksClassification]
class Metashape.CloudClient
CloudClient class provides access to the Agisoft Cloud processing service and allows to create and manage cloud
projects.
The following example connects to the service and lists available projects:
import Metashape
client = Metashape.CloudClient()
client.username = ‘user’
client.password = ‘password’
client.projectList()
abortProcessing(document)
Cancel processing.
Parameters document (Document) – Project to cancel.
client_id
Client software id (optional).
Type string
client_secret
Client softrwae secret (optional).
Type string
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downloadProject(document[, progress])
Download project from the cloud.
Parameters

document (Document) – Project to download.

progress (Callable[[float], None]) – Progress callback.
getProcessingStatus(document)
Get processing status.
Parameters document (Document) – Project being processed.
Returns Processing status.
Return type dict
getProjectList()
Get list of projects in the cloud.
Returns List of projects.
Return type list
password
Cloud account password.
Type string
processProject(document, tasks)
Start processing in the cloud.
Parameters

document (Document) – Project to process.

tasks (list of NetworkTask) – List of processing tasks to execute.
uploadProject(document[, progress])
Upload project to the cloud.
Parameters

document (Document) – Project to upload.

progress (Callable[[float], None]) – Progress callback.
username
Cloud account username.
Type string
class Metashape.CoordinateSystem
Coordinate reference system (local, geographic or projected).
The following example changes chunk coordinate system to WGS 84 / UTM zone 41N and loads reference data
from file:
import Metashape
chunk = Metashape.app.document.chunk
chunk.crs = Metashape.CoordinateSystem(« EPSG::32641 »)
chunk.importReference(« gcp.txt », Metashape.ReferenceFormatCSV)
chunk.updateTransform()
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addGeoid(path)
Register geoid model.
Parameters path (string) – Path to geoid file.
authority
Authority identifier of the coordinate system.
Type string
copy()
Return a copy of the object.
Returns A copy of the object.
Return type CoordinateSystem
datumTransform(source, target)
Coordinate transformation from source to target coordinate system datum.
Parameters

source (CoordinateSystem) – Source coordinate system.

target (CoordinateSystem) – Target coordinate system.
Returns 4×4 transformation matrix.
Return type Matrix
geoccs
Base geocentric coordinate system.
Type CoordinateSystem
geogcs
Base geographic coordinate system.
Type CoordinateSystem
geoid_height
Fixed geoid height to be used instead of interpolated values.
Type float
init(crs)
Initialize projection based on specified WKT definition or authority identifier.
Parameters crs (string) – WKT definition of coordinate system or authority identifier.
listBuiltinCRS()
Returns a list of builtin coordinate systems.
localframe(point)
Returns 4×4 transformation matrix to LSE coordinates at the given point.
Parameters point (Vector) – Coordinates of the origin in the geocentric coordinates.
Returns Transformation from geocentric coordinates to local coordinates.
Return type Matrix
name
Name of the coordinate system.
Type string
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proj4
Coordinate system definition in PROJ.4 format.
Type string
project(point)
Projects point from geocentric coordinates to projected geographic coordinate system.
Parameters point (Vector) – 3D point in geocentric coordinates.
Returns 3D point in projected coordinates.
Return type Vector
towgs84
TOWGS84 transformation parameters (dx, dy, dz, rx, ry, rz, scale).
Type list of float
transform(point, source, target)
Transform point coordinates between coordinate systems.
Parameters

point (2 or 3 component Vector) – Point coordinates.

source (CoordinateSystem) – Source coordinate system.

target (CoordinateSystem) – Target coordinate system.
Returns Transformed point coordinates.
Return type Vector
transformationMatrix(point, source, target)
Local approximation of coordinate transformation from source to target coordinate system at the given
point.
Parameters

point (3 component Vector) – Point coordinates.

source (CoordinateSystem) – Source coordinate system.

target (CoordinateSystem) – Target coordinate system.
Returns 4×4 transformation matrix.
Return type Matrix
unproject(point)
Unprojects point from projected coordinates to geocentric coordinates.
Parameters point (Vector) – 3D point in projected coordinate system.
Returns 3D point in geocentric coordinates.
Return type Vector
wkt
Coordinate system definition in WKT format.
Type string
wkt2
Coordinate system definition in WKT format, version 2.
Type string
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class Metashape.DataSource
Data source in [TiePointsData, PointCloudData, DepthMapsData, ModelData, TiledModelData, ElevationData,
OrthomosaicData, ImagesData]
class Metashape.DataType
Data type in [DataTypeUndefined, DataType8i, DataType8u, DataType16i, DataType16u, DataType16f,
DataType32i, DataType32u, DataType32f, DataType64i, DataType64u, DataType64f]
class Metashape.DepthMap
Depth map data.
calibration
Depth map calibration.
Type Calibration
copy()
Returns a copy of the depth map.
Returns Copy of the depth map.
Return type DepthMap
getCalibration(level=0)
Returns calibration data.
Parameters level (int) – Level index.
Returns Calibration data.
Return type Calibration
image([level])
Returns image data.
Parameters level (int) – Level index.
Returns Image data.
Return type Image
setCalibration(calibration, level=0)
Parameters

calibration (Calibration) – Calibration data.

level (int) – Level index.
setImage(image, level=0)
Parameters

image (Image) – Image object with depth map data.

level (int) – Level index.
class Metashape.DepthMaps
A set of depth maps generated for a chunk frame.
clear()
Clears depth maps data.
copy()
Create a copy of the depth maps.
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Returns Copy of the depth maps.
Return type DepthMaps
items()
List of items.
key
Depth maps identifier.
Type int
keys()
List of item keys.
label
Depth maps label.
Type string
meta
Depth maps meta data.
Type MetaData
modified
Modified flag.
Type bool
values()
List of item values.
class Metashape.Document
Metashape project.
Contains list of chunks available in the project. Implements processing operations that work with multiple
chunks. Supports saving/loading project files.
The project currently opened in Metashape window can be accessed using Metashape.app.document attribute.
Additional Document objects can be created as needed.
The following example saves active chunk from the opened project in a separate project:
import Metashape
doc = Metashape.app.document
doc.save(path = « project.psz », chunks = [doc.chunk])
addChunk()
Add new chunk to the document.
Returns Created chunk.
Return type Chunk
alignChunks([chunks][, reference ], method=0, fit_scale=True, downscale=1, generic_preselection=False,
filter_mask=False, mask_tiepoints=False, keypoint_limit=40000[, markers][, progress])
Align specified set of chunks.
Parameters

chunks (list of int) – List of chunks to be aligned.

reference (int) – Chunk to be used as a reference.

method (int) – Alignment method (0 – point based, 1 – marker based, 2 – camera based).
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fit_scale (bool) – Fit chunk scale during alignment.

downscale (int) – Alignment accuracy.

generic_preselection (bool) – Enables image pair preselection.

filter_mask (bool) – Filter points by mask.

mask_tiepoints (bool) – Apply mask filter to tie points.

keypoint_limit (int) – Maximum number of points for each photo.

markers (list of int) – List of markers to be used for marker based alignment.

progress (Callable[[float], None]) – Progress callback.
append(document[, chunks][, progress])
Append the specified Document object to the current document.
Parameters

document (Document) – Document object to be appended.

chunks (list of Chunk) – List of chunks to append.

progress (Callable[[float], None]) – Progress callback.
chunk
Active chunk.
Type Chunk
chunks
List of chunks in the document.
Type Chunks
clear()
Clear the contents of the Document object.
copy()
Return a copy of the document.
Returns A copy of the document.
Return type Document
findChunk(key)
Find chunk by its key.
Returns Found chunk.
Return type Chunk
mergeChunks(copy_laser_scans=True, copy_depth_maps=False, copy_point_clouds=False,
copy_models=False, copy_tiled_models=False, copy_elevations=False,
copy_orthomosaics=False, merge_markers=False, merge_tiepoints=False,
merge_assets=False[, chunks][, progress])
Merge specified set of chunks.
Parameters

copy_laser_scans (bool) – Copy laser scans.

copy_depth_maps (bool) – Copy depth maps.

copy_point_clouds (bool) – Copy point clouds.
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copy_models (bool) – Copy models.

copy_tiled_models (bool) – Copy tiled models.

copy_elevations (bool) – Copy DEMs.

copy_orthomosaics (bool) – Copy orthomosaics.

merge_markers (bool) – Merge markers.

merge_tiepoints (bool) – Merge tie points.

merge_assets (bool) – Merge default assets.

chunks (list of int) – List of chunks to process.

progress (Callable[[float], None]) – Progress callback.
meta
Document meta data.
Type MetaData
modified
Modified flag.
Type bool
open(path, read_only=False, ignore_lock=False, archive=True)
Load document from the specified file.
Parameters

path (string) – Path to the file.

read_only (bool) – Open document in read-only mode.

ignore_lock (bool) – Ignore lock state for project modifications.

archive (bool) – Override project format when using non-standard file extension.
path
Path to the document file.
Type string
read_only
Read only status.
Type bool
remove(items)
Remove a set of items from the document.
Parameters items (list of Chunk) – A list of items to be removed.
save([path ][, chunks][, version ], archive=True)
Save document to the specified file.
Parameters

path (string) – Optional path to the file.

chunks (list of Chunk) – List of chunks to be saved.

version (string) – Project version to save.

archive (bool) – Override project format when using non-standard file extension.
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class Metashape.Elevation
Digital elevation model.
altitude(point)
Return elevation value at the specified point.
Parameters point (Vector) – Point coordinates in the elevation coordinate system.
Returns Elevation value.
Return type float
bottom
Y coordinate of the bottom side.
Type float
clear()
Clears elevation model data.
copy()
Create a copy of the elevation model.
Returns Copy of the elevation model.
Return type Elevation
crs
Coordinate system of elevation model.
Type CoordinateSystem
height
Elevation model height.
Type int
key
Elevation model identifier.
Type int
label
Elevation model label.
Type string
left
X coordinate of the left side.
Type float
max
Maximum elevation value.
Type float
meta
Elevation model meta data.
Type MetaData
min
Minimum elevation value.
Type float
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modified
Modified flag.
Type bool
palette
Color palette.
Type dict
projection
Projection of elevation model.
Type OrthoProjection
resolution
DEM resolution in meters.
Type float
right
X coordinate of the right side.
Type float
top
Y coordinate of the top side.
Type float
width
Elevation model width.
Type int
class Metashape.EulerAngles
Euler angles in [EulerAnglesYPR, EulerAnglesOPK, EulerAnglesPOK, EulerAnglesANK]
class Metashape.FaceCount
Face count in [LowFaceCount, MediumFaceCount, HighFaceCount, CustomFaceCount]
class Metashape.FilterMode
Depth filtering mode in [NoFiltering, MildFiltering, ModerateFiltering, AggressiveFiltering]
class Metashape.FrameStep
Frame step size for video import in [CustomFrameStep, SmallFrameStep, MediumFrameStep, LargeFrameStep]
class Metashape.Geometry
Geometry data.
GeometryCollection(geometries)
Create a GeometryCollection geometry.
Parameters geometries (list of Geometry) – Child geometries.
Returns A GeometryCollection geometry.
Return type Geometry
LineString(coordinates)
Create a LineString geometry.
Parameters coordinates (list of Vector) – List of vertex coordinates.
Returns A LineString geometry.
Return type Geometry
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MultiLineString(geometries)
Create a MultiLineString geometry.
Parameters geometries (list of Geometry) – Child line strings.
Returns A point geometry.
Return type Geometry
MultiPoint(geometries)
Create a MultiPoint geometry.
Parameters geometries (list of Geometry) – Child points.
Returns A point geometry.
Return type Geometry
MultiPolygon(geometries)
Create a MultiPolygon geometry.
Parameters geometries (list of Geometry) – Child polygons.
Returns A point geometry.
Return type Geometry
Point(vector)
Create a Point geometry.
Parameters vector (Vector or list of floats) – Point coordinates.
Returns A point geometry.
Return type Geometry
Polygon(exterior_ring[, interior_rings])
Create a Polygon geometry.
Parameters

exterior_ring (list of Vector) – Point coordinates.

interior_rings (list of Vector) – Point coordinates.
Returns A Polygon geometry.
Return type Geometry
class Type
Geometry type in [PointType, LineStringType, PolygonType, MultiPointType, MultiLineStringType, MultiPolygonType, GeometryCollectionType]
coordinates
List of vertex coordinates.
Type Vector
geometries
List of child geometries.
Type Geometry
is_3d
Is 3D flag.
Type bool
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type
Geometry type.
Type Geometry.Type
class Metashape.Image(width, height, channels, datatype=’U8′)
n-channel image
Parameters

width (int) – image width

height (int) – image height

channels (string) – color channel layout, e.g. ‘RGB’, ‘RGBA’, etc.

datatype (string) – pixel data type in [‘U8’, ‘U16’, ‘U32’, ‘F16’, ‘F32’, ‘F64’]
channels
Channel mapping for the image.
Type string
cn
Number of color channels.
Type int
convert(channels[, datatype ])
Convert image to specified data type and channel layout.
Parameters

channels (string) – color channels to be loaded, e.g. ‘RGB’, ‘RGBA’, etc.

datatype (string) – pixel data type in [‘U8’, ‘U16’, ‘U32’, ‘F16’, ‘F32’, ‘F64’]
Returns Converted image.
Return type Image
copy()
Return a copy of the image.
Returns copy of the image
Return type Image
data_type
Data type used to store pixel values.
Type string
fromstring(data, width, height, channels, datatype=’U8′)
Create image from byte array.
Parameters

data (string) – raw image data

width (int) – image width

height (int) – image height

channels (string) – color channel layout, e.g. ‘RGB’, ‘RGBA’, etc.

datatype (string) – pixel data type in [‘U8’, ‘U16’, ‘U32’, ‘F16’, ‘F32’, ‘F64’]
Returns Created image.
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Return type Image
gaussianBlur(radius)
Smooth image with a gaussian filter.
Parameters radius (float) – smoothing radius.
Returns Smoothed image.
Return type Image
height
Image height.
Type int
open(path, layer=0, datatype=’U8′[, channels][, x ][, y ][, w][, h ])
Load image from file.
Parameters

path (string) – path to the image file

layer (int) – image layer in case of multipage file

datatype (string) – pixel data type in [‘U8’, ‘U16’, ‘U32’, ‘F16’, ‘F32’, ‘F64’]

channels (string) – color channels to be loaded, e.g. ‘RGB’, ‘RGBA’, etc.

x (int) – x offset of image region.

y (int) – y offset of image region.

w (int) – width of image region.

h (int) – height of image region.
Returns Loaded image.
Return type Image
resize(width, height)
Resize image to specified dimensions.
Parameters

width (int) – new image width

height (int) – new image height
Returns resized image
Return type Image
save(path[, compression ])
Save image to the file.
Parameters

path (string) – path to the image file

compression (ImageCompression) – compression options
tostring()
Convert image to byte array.
Returns Raw image data.
Return type string
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undistort(calib, center_principal_point=True, square_pixels=True)
Undistort image using provided calibration.
Parameters

calib (Calibration) – lens calibration

center_principal_point (bool) – moves principal point to the image center

square_pixels (bool) – create image with square pixels
Returns undistorted image
Return type Image
uniformNoise(amplitude)
Add uniform noise with specified amplitude.
Parameters amplitude (float) – noise amplitude.
Returns Image with added noise.
Return type Image
warp(calib0, trans0, calib1, trans1)
Warp image by rotating virtual viewpoint.
Parameters

calib0 (Calibration) – initial calibration

trans0 (Matrix) – initial camera orientation as 4×4 matrix

calib1 (Calibration) – final calibration

trans1 (Matrix) – final camera orientation as 4×4 matrix
Returns warped image
Return type Image
width
Image width.
Type int
class Metashape.ImageCompression
Image compression parameters
class TiffCompression
Tiff compression in [TiffCompressionNone, TiffCompressionLZW, TiffCompressionJPEG, TiffCompressionPackbits, TiffCompressionDeflate]
copy()
Return a copy of the object.
Returns A copy of the object.
Return type Viewpoint
jpeg_quality
JPEG quality.
Type int
tiff_big
Enable BigTIFF compression for TIFF files.
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Type bool
tiff_compression
Tiff compression.
Type int
tiff_overviews
Enable image pyramid deneration for TIFF files.
Type bool
tiff_tiled
Export tiled TIFF.
Type bool
class Metashape.ImageFormat
Image format in [ImageFormatNone, ImageFormatJPEG, ImageFormatTIFF, ImageFormatPNG, ImageFormatBMP, ImageFormatEXR, ImageFormatPNM, ImageFormatSGI, ImageFormatCR2, ImageFormatBZ2, ImageFormatSEQ, ImageFormatBIL, ImageFormatASCII, ImageFormatXYZ, ImageFormatARA, ImageFormatTGA, ImageFormatDDS, ImageFormatJP2, ImageFormatWebP, ImageFormatJXL, ImageFormatKTX]
class Metashape.ImageLayout
Image layout in [UndefinedLayout, FlatLayout, MultiframeLayout, MultiplaneLayout]
class Metashape.Interpolation
Interpolation mode in [DisabledInterpolation, EnabledInterpolation, Extrapolated]
class Metashape.License
License information.
activate(license_key)
Activate software online using a license key.
Parameters key (string) – Activation key.
activateOffline(activation_params)
Create a request for offline activation.
Parameters activation_params (string) – The content of .actparam file.
Returns The activation request which should be saved to .actreq file.
Return type string
deactivate()
Deactivate software online.
deactivateOffline()
Create a request for offline deactivation.
Returns The deactivation request which should be saved to .actreq file.
Return type string
install(activation_response)
Install license from the activation response.
Parameters activation_response (string) – The content of .actresp file.
valid
Metashape activation status.
Type bool
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class Metashape.MappingMode
UV mapping mode in [GenericMapping, OrthophotoMapping, AdaptiveOrthophotoMapping, SphericalMapping, CameraMapping]
class Metashape.Marker
Marker instance
class Projection
Marker data().
coord
Point coordinates in pixels.
Type Vector
pinned
Pinned flag.
Type bool
valid
Valid flag.
Type bool
class Projections
Collection of projections specified for the marker
items()
List of items.
keys()
List of item keys.
values()
List of item values.
class Reference
Marker reference data.
accuracy
Marker location accuracy.
Type Vector
enabled
Enabled flag.
Type bool
location
Marker coordinates.
Type Vector
class Type
Marker type in [Regular, Vertex, Fiducial]
chunk
Chunk the marker belongs to.
Type Chunk
enabled
Enables/disables the marker.
Type bool
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frames
Marker frames.
Type list of Marker
group
Marker group.
Type MarkerGroup
key
Marker identifier.
Type int
label
Marker label.
Type string
meta
Marker meta data.
Type MetaData
position
Marker position in the current frame.
Type Vector
position_covariance
Marker position covariance.
Type Matrix
projections
List of marker projections.
Type MarkerProjections
reference
Marker reference data.
Type MarkerReference
selected
Selects/deselects the marker.
Type bool
sensor
Fiducial mark sensor.
Type Sensor
type
Marker type.
Type Marker.Type
class Metashape.MarkerGroup
MarkerGroup objects define groups of multiple markers. The grouping is established by assignment of a MarkerGroup instance to the Marker.group attribute of participating markers.
label
Marker group label.
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Type string
selected
Current selection state.
Type bool
class Metashape.Mask
Mask instance
copy()
Returns a copy of the mask.
Returns Copy of the mask.
Return type Mask
image()
Returns image data.
Returns Image data.
Return type Image
invert()
Create inverted copy of the mask.
Returns Inverted copy of the mask.
Return type Mask
load(path[, layer])
Loads mask from file.
Parameters

path (string) – Path to the image file to be loaded.

layer (int) – Optional layer index in case of multipage files.
setImage(image)
Parameters image (Image) – Image object with mask data.
class Metashape.MaskOperation
Mask operation in [MaskOperationReplacement, MaskOperationUnion, MaskOperationIntersection, MaskOperationDifference]
class Metashape.MaskingMode
Masking mode in [MaskingModeAlpha, MaskingModeFile, MaskingModeBackground, MaskingModeModel]
class Metashape.Masks
A set of masks for a chunk frame.
items()
List of items.
keys()
List of item keys.
meta
Thumbnails meta data.
Type MetaData
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modified
Modified flag.
Type bool
values()
List of item values.
class Metashape.Matrix
m-by-n matrix
import Metashape
m1 = Metashape.Matrix.Diag( (1,2,3,4) )
m3 = Metashape.Matrix( [[1,2,3,4], [1,2,3,4], [1,2,3,4], [1,2,3,4]] )
m2 = m1.inv()
m3 = m1 * m2
x = m3.det()
if x == 1:
… Metashape.app.messageBox(« Diagonal matrix dimensions: » + str(m3.size))
Diag(vector)
Create a diagonal matrix.
Parameters vector (Vector or list of floats) – The vector of diagonal entries.
Returns A diagonal matrix.
Return type Matrix
Rotation(matrix)
Create a rotation matrix.
Parameters matrix (Matrix) – The 3×3 rotation matrix.
Returns 4×4 matrix representing rotation.
Return type Matrix
Scale(scale)
Create a scale matrix.
Parameters scale (Vector) – The scale vector.
Returns A matrix representing scale.
Return type Matrix
Translation(vector)
Create a translation matrix.
Parameters vector (Vector) – The translation vector.
Returns A matrix representing translation.
Return type Matrix
col(index)
Returns column of the matrix.
Returns matrix column.
Return type Vector
copy()
Returns a copy of this matrix.
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Returns an instance of itself
Return type Matrix
det()
Return the determinant of a matrix.
Returns Return a the determinant of a matrix.
Return type float
inv()
Returns an inverted copy of the matrix.
Returns inverted matrix.
Return type Matrix
mulp(point)
Transforms a point in homogeneous coordinates.
Parameters point (Vector) – The point to be transformed.
Returns transformed point.
Return type Vector
mulv(vector)
Transforms vector in homogeneous coordinates.
Parameters vector (Vector) – The vector to be transformed.
Returns transformed vector.
Return type Vector
rotation()
Returns rotation component of the 4×4 matrix.
Returns rotation component
Return type Matrix
row(index)
Returns row of the matrix.
Returns matrix row.
Return type Vector
scale()
Returns scale component of the 4×4 matrix.
Returns scale component
Return type float
size
Matrix dimensions.
Type tuple
svd()
Returns singular value decomposition of the matrix.
Returns u, s, v tuple where a = u * diag(s) * v
Return type Matrix Vector Matrix tuple
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t()
Return a new, transposed matrix.
Returns a transposed matrix
Return type Matrix
translation()
Returns translation component of the 4×4 matrix.
Returns translation component
Return type Vector
zero()
Set all matrix elements to zero.
class Metashape.MetaData(object)
Collection of object properties
copy()
Return a copy of the object.
Returns A copy of the object.
Return type MetaData
items()
List of items.
keys()
List of item keys.
values()
List of item values.
class Metashape.Model
Triangular mesh model instance
class Face
Triangular face of the model
hidden
Face visibility flag.
Type bool
selected
Face selection flag.
Type bool
tex_index
Texture page index.
Type int
tex_vertices
Texture vertex indices.
Type tuple of 3 int
vertices
Vertex indices.
Type tuple of 3 int
class Faces
Collection of model faces
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resize(count)
Resize faces list.
Parameters count (int) – new face count
class Statistics
Mesh statistics
components
Number of connected components.
Type int
degenerate_faces
Number of degenerate faces.
Type int
duplicate_faces
Number of duplicate faces.
Type int
faces
Total number of faces.
Type int
flipped_normals
Number of edges with flipped normals.
Type int
free_vertices
Number of free vertices.
Type int
multiple_edges
Number of edges connecting more than 2 faces.
Type int
open_edges
Number of open edges.
Type int
out_of_range_indices
Number of out of range indices.
Type int
similar_vertices
Number of similar vertices.
Type int
vertices
Total number of vertices.
Type int
zero_faces
Number of zero faces.
Type int
class TexVertex
Texture vertex of the model
coord
Vertex coordinates.
Type tuple of 2 float
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class TexVertices
Collection of model texture vertices
resize(count)
Resize vertex list.
Parameters count (int) – new vertex count
class Texture
Model texture.
image(page=0)
Return texture image.
Parameters page (int) – Texture index for multitextured models.
Returns Texture image.
Return type Image
label
Animation label.
Type string
meta
Camera track meta data.
Type MetaData
model
Model the texture belongs to.
Type Model
setImage(image, page=0)
Initialize texture from image data.
Parameters

image (Image) – Texture image.

page (int) – Texture index for multitextured models.
type
Texture type.
Type Model.TextureType
class TextureType
Texture type in [DiffuseMap, NormalMap, OcclusionMap, DisplacementMap]
class Vertex
Vertex of the model
color
Vertex color.
Type tuple of numbers
confidence
Vertex confidence.
Type float
coord
Vertex coordinates.
Type Vector
class Vertices
Collection of model vertices
resize(count)
Resize vertex list.
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Parameters count (int) – new vertex count
addTexture(type=Model.DiffuseMap)
Add new texture to the model.
Parameters type (Model.TextureType) – Texture type.
Returns Created texture.
Return type Model.Texture
area()
Return area of the model surface.
Returns Model area.
Return type float
bands
List of color bands.
Type list of string
clear()
Clears model data.
closeHoles(level=30, apply_to_selection=False)
Fill holes in the model surface.
Parameters

level (int) – Hole size threshold in percents.

apply_to_selection (bool) – Close holes within selection
copy()
Create a copy of the model.
Returns Copy of the model.
Return type Model
cropSelection()
Crop selected faces and free vertices from the mesh.
data_type
Data type used to store color values.
Type DataType
faces
Collection of mesh faces.
Type MeshFaces
fixTopology()
Remove polygons causing topological problems.
getActiveTexture(type=Model.DiffuseMap)
Return active texture.
Parameters type (Model.TextureType) – Texture type.
Returns Texture image.
Return type Image
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key
Model identifier.
Type int
label
Model label.
Type string
loadTexture(path)
Load texture from the specified file.
Parameters path (string) – Path to the image file.
meta
Model meta data.
Type MetaData
modified
Modified flag.
Type bool
pickPoint(origin, target, endpoints=1)
Return ray intersection with mesh.
Parameters

origin (Vector) – Ray origin.

target (Vector) – Point on the ray.

endpoints (int) – Number of endpoints to check for (0 – line, 1 – ray, 2 – segment).
Returns Coordinates of the intersection point.
Return type Vector
remove(items)
Remove textures from the model.
Parameters items (list of Model.Texture) – A list of textures to be removed.
removeComponents(size)
Remove small connected components.
Parameters size (int) – Threshold on the polygon count of the components to be removed.
removeSelection()
Remove selected faces and free vertices from the mesh.
renderDepth(transform, calibration, cull_faces=True, add_alpha=True)
Render model depth image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

cull_faces (bool) – Enable back-face culling.

add_alpha (bool) – Generate image with alpha channel.
Returns Rendered image.
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Return type Image
renderImage(transform, calibration, cull_faces=True, add_alpha=True,
raster_transform=RasterTransformNone)
Render model image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

cull_faces (bool) – Enable back-face culling.

add_alpha (bool) – Generate image with alpha channel.

raster_transform (RasterTransformType) – Raster band transformation.
Returns Rendered image.
Return type Image
renderMask(transform, calibration, cull_faces=True)
Render model mask image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

cull_faces (bool) – Enable back-face culling.
Returns Rendered image.
Return type Image
renderNormalMap(transform, calibration, cull_faces=True, add_alpha=True)
Render image with model normals for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

cull_faces (bool) – Enable back-face culling.

add_alpha (bool) – Generate image with alpha channel.
Returns Rendered image.
Return type Image
renderPreview(width = 2048, height = 2048[, transform ][, progress])
Generate model preview image.
Parameters

width (int) – Preview image width.

height (int) – Preview image height.

transform (Matrix) – 4×4 viewpoint transformation matrix.

progress (Callable[[float], None]) – Progress callback.
Returns Preview image.
Return type Image
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saveTexture(path)
Save texture to the specified file.
Parameters path (string) – Path to the image file.
setActiveTexture(texture, type=Model.DiffuseMap)
Set active texture.
Parameters

texture (Model.Texture) – Texture to set.

type (Model.TextureType) – Texture type.
statistics([progress])
Return mesh statistics.
Parameters progress (Callable[[float], None]) – Progress callback.
Returns Mesh statistics.
Return type Model.Statistics
tex_vertices
Collection of mesh texture vertices.
Type MeshTexVertices
textures
List of model textures.
Type list of Model.Texture
transform(transform)
Transform vertex coordinates.
Parameters transform (Matrix) – 4×4 transformation matrix.
vertices
Collection of mesh vertices.
Type MeshVertices
volume()
Return volume of the closed model surface.
Returns Model volume.
Return type float
class Metashape.ModelFormat
Model format in [ModelFormatNone, ModelFormatOBJ, ModelFormat3DS, ModelFormatVRML, ModelFormatPLY, ModelFormatCOLLADA, ModelFormatU3D, ModelFormatPDF, ModelFormatDXF, ModelFormatFBX, ModelFormatKMZ, ModelFormatCTM, ModelFormatSTL, ModelFormatDXF_3DF, ModelFormatTLS, ModelFormatABC, ModelFormatOSGB, ModelFormatOSGT, ModelFormatGLTF, ModelFormatX3D,
ModelFormatLandXML]
class Metashape.NetworkClient
NetworkClient class provides access to the network processing server and allows to create and manage tasks.
The following example connects to the server and lists active tasks:
import Metashape
client = Metashape.NetworkClient()
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client.connect(‘127.0.0.1’)
client.batchList()
abortBatch(batch_id)
Abort batch.
Parameters batch_id (int) – Batch id.
abortNode(node_id)
Abort node.
Parameters node_id (int) – Node id.
batchList(revision=0)
Get list of batches.
Parameters revision (int) – First revision to get.
Returns List of batches.
Return type dict
batchStatus(batch_id, revision=0)
Get batch status.
Parameters

batch_id (int) – Batch id.

revision (int) – First revision to get.
Returns Batch status.
Return type dict
connect(host, port=5840)
Connect to the server.
Parameters

host (string) – Server hostname.

port (int) – Communication port.
createBatch(path, tasks[, meta ])
Create new batch.
Parameters

path (string) – Project path relative to root folder.

tasks (list of NetworkTask) – List of processing tasks to execute.

meta (MetaData) – Batch metadata.
Returns Batch id.
Return type int
disconnect()
Disconnect from the server.
dumpBatches([batch_ids])
Dump current state of batches.
Parameters batch_ids (list of int) – List of batch ids to dump.
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Returns Batches data.
Return type string
findBatch(path)
Get batch id based on project path.
Parameters path (string) – Project path relative to root folder.
Returns Batch id.
Return type int
loadBatches(data)
Load batches from dump.
Parameters data (string) – Batches data.
nodeList(revision=0)
Get list of nodes.
Parameters revision (int) – First revision to get.
Returns List of nodes.
Return type dict
nodeStatus(node_id, revision=0)
Get node status.
Parameters

node_id (int) – Node id.

revision (int) – First revision to get.
Returns Node status.
Return type dict
quitNode(node_id)
Quit node.
Parameters node_id (int) – Node id.
serverInfo()
Get server information.
Returns Server information.
Return type dict
serverStatus(revision=0)
Get server status.
Parameters revision (int) – First revision to get.
Returns Server status.
Return type dict
setBatchNodeLimit(batch_id, node_limit)
Set node limit of the batch.
Parameters

batch_id (int) – Batch id.

node_limit (int) – Node limit of the batch (0 – unlimited).
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setBatchPaused(batch_id, paused=True)
Set batch paused state.
Parameters

batch_id (int) – Batch id.

paused (bool) – Paused state.
setBatchPriority(batch_id, priority)
Set batch priority.
Parameters

batch_id (int) – Batch id.

priority (int) – Batch priority (2 – Highest, 1 – High, 0 – Normal, -1 – Low, -2 – Lowest).
setMasterServer([host])
Set or reset master server.
Parameters host (string) – Master server hostname.
setNodeCPUEnable(node_id, cpu_enable)
Set node CPU enable flag.
Parameters

node_id (int) – Node id.

cpu_enable (bool) – CPU enable flag.
setNodeCapability(node_id, capability)
Set node capability.
Parameters

node_id (int) – Node id.

capability (int) – Node capability (1 – CPU, 2 – GPU, 3 – Any).
setNodeGPUMask(node_id, gpu_mask)
Set node GPU mask.
Parameters

node_id (int) – Node id.

gpu_mask (int) – GPU device mask.
setNodePaused(node_id, paused=True)
Set node paused state.
Parameters

node_id (int) – Node id.

paused (bool) – Paused state.
setNodePriority(node_id, priority)
Set node priority.
Parameters

node_id (int) – Node id.

priority (int) – Node priority (2 – Highest, 1 – High, 0 – Normal, -1 – Low, -2 – Lowest).
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class Metashape.NetworkTask
NetworkTask class contains information about network task and its parameters.
The following example creates a new processing task and submits it to the server:
import Metashape
task = Metashape.NetworkTask()
task.name = ‘MatchPhotos’
task.params[‘keypoint_limit’] = 40000
client = Metashape.NetworkClient()
client.connect(‘127.0.0.1’)
batch_id = client.createBatch(‘processing/project.psx’, [task])
client.setBatchPaused(batch_id, false)
chunks
List of chunks.
Type list
encode()
Create a dictionary with task parameters.
frames
List of frames.
Type list
name
Task name.
Type string
params
Task parameters.
Type dict
supports_gpu
GPU support flag.
Type bool
class Metashape.OrthoProjection
Orthographic projection.
class Type
Projection type in [Planar, Cylindrical]
copy()
Return a copy of the object.
Returns A copy of the object.
Return type OrthoProjection
crs
Base coordinate system.
Type CoordinateSystem
matrix
Ortho transformation matrix.
Type Matrix
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radius
Cylindrical projection radius.
Type float
transform(point, source, target)
Transform point coordinates between coordinate systems.
Parameters

point (2 or 3 component Vector) – Point coordinates.

source (OrthoProjection) – Source coordinate system.

target (OrthoProjection) – Target coordinate system.
Returns Transformed point coordinates.
Return type Vector
type
Projection type.
Type OrthoProjection.Type
class Metashape.Orthomosaic
Orthomosaic data.
The following sample assigns to the first shape in the chunk the image from the first camera for the orthomosaic
patch and updates the mosaic:
import Metashape
chunk = Metashape.app.document.chunk
ortho = chunk.orthomosaic
camera = chunk.cameras[0]
shape = chunk.shapes[0]
patch = Metashape.Orthomosaic.Patch()
patch.image_keys = [camera.key]
ortho.patches[shape] = patch
ortho.update()
class Patch
Orthomosaic patch.
copy()
Returns a copy of the patch.
Returns Copy of the patch.
Return type Orthomosaic.Patch
excluded
Excluded flag.
Type bool
image_keys
Image keys.
Type list of int
class Patches
A set of orthomosaic patches.
items()
List of items.
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keys()
List of item keys.
values()
List of item values.
bands
List of color bands.
Type list of string
bottom
Y coordinate of the bottom side.
Type float
clear()
Clears orthomosaic data.
copy()
Create a copy of the orthomosaic.
Returns Copy of the orthomosaic.
Return type Orthomosaic
crs
Coordinate system of orthomosaic.
Type CoordinateSystem
data_type
Data type used to store color values.
Type DataType
height
Orthomosaic height.
Type int
key
Orthomosaic identifier.
Type int
label
Orthomosaic label.
Type string
left
X coordinate of the left side.
Type float
meta
Orthomosaic meta data.
Type MetaData
modified
Modified flag.
Type bool
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patches
Orthomosaic patches.
Type Orthomosaic.Patches
projection
Orthomosaic projection.
Type OrthoProjection
removeOrthophotos()
Remove orthorectified images from orthomosaic.
renderPreview(width = 2048, height = 2048[, progress])
Generate orthomosaic preview image. :arg width: Preview image width. :type width: int :arg height:
Preview image height. :type height: int :arg progress: Progress callback. :type progress: Callable[[float],
None] :return: Preview image. :rtype: Image
reset([progress])
Reset all edits to orthomosaic.
Parameters progress (Callable[[float], None]) – Progress callback.
resolution
Orthomosaic resolution in meters.
Type float
right
X coordinate of the right side.
Type float
top
Y coordinate of the top side.
Type float
update([progress])
Apply edits to orthomosaic.
Parameters progress (Callable[[float], None]) – Progress callback.
width
Orthomosaic width.
Type int
class Metashape.Photo
Photo instance
alpha()
Returns alpha channel data.
Returns Alpha channel data.
Return type Image
copy()
Returns a copy of the photo.
Returns Copy of the photo.
Return type Photo
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image([channels][, datatype ])
Returns image data.
Parameters

datatype (string) – pixel data type in [‘U8’, ‘U16’, ‘U32’, ‘F16’, ‘F32’, ‘F64’]

channels (string) – color channels to be loaded, e.g. ‘RGB’, ‘RGBA’, etc.
Returns Image data.
Return type Image
imageMeta()
Returns image meta data.
Returns Image meta data.
Return type MetaData
layer
Layer index in the image file.
Type int
meta
Frame meta data.
Type MetaData
open(path, layer=0)
Loads specified image file.
Parameters

path (string) – Path to the image file to be loaded.

layer (int) – Layer index in case of multipage files.
path
Path to the image file.
Type string
thumbnail(width=192, height=192)
Creates new thumbnail with specified dimensions.
Returns Thumbnail data.
Return type Thumbnail
class Metashape.PointClass
Point class in [Created, Unclassified, Ground, LowVegetation, MediumVegetation, HighVegetation, Building,
LowPoint, ModelKeyPoint, Water, Rail, RoadSurface, OverlapPoints, WireGuard, WireConductor, TransmissionTower, WireConnector, BridgeDeck, HighNoise, Car, Manmade]
class Metashape.PointCloud
Point cloud data.
assignClass(target=0[, source ][, progress])
Assign class to points.
Parameters

target (PointClass) – Target class.

source (PointClass or list of PointClass) – Classes of points to be replaced.
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progress (Callable[[float], None]) – Progress callback.
assignClassToSelection(target=0[, source ][, progress])
Assign class to selected points.
Parameters

target (PointClass) – Target class.

source (PointClass or list of PointClass) – Classes of points to be replaced.

progress (Callable[[float], None]) – Progress callback.
bands
List of color bands.
Type list of string
classifyGroundPoints(max_angle=15.0, max_distance=1.0, cell_size=50.0, erosion_radius=0.0[,
source_class][, return_number], keep_existing=False[, progress])
Classify points into ground and non ground classes.
Parameters

max_angle (float) – Maximum angle (degrees).

max_distance (float) – Maximum distance (meters).

cell_size (float) – Cell size (meters).

erosion_radius (float) – Erosion radius (meters).

source_class (PointClass) – Class of points to be re-classified.

return_number (int) – Point return number to use (0 – any return, 1 – first return, -1 –
last return).

keep_existing (bool) – Keep existing ground points.

progress (Callable[[float], None]) – Progress callback.
classifyPoints([source ][, target], confidence=0.0[, progress])
Multiclass classification of points.
Parameters

source (PointClass) – Class of points to be re-classified.

target (list of PointClass) – Target point classes for classification.

confidence (float) – Required confidence level from 0.0 to 1.0.

progress (Callable[[float], None]) – Progress callback.
clear()
Clears point cloud data.
compactPoints([progress])
Permanently removes deleted points from point cloud.
Parameters progress (Callable[[float], None]) – Progress callback.
copy()
Create a copy of the point cloud.
Returns Copy of the point cloud.
Return type PointCloud
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cropSelectedPoints([point_classes][, progress])
Crop selected points.
Parameters

point_classes (PointClass or list of PointClass) – Classes of points to be removed.

progress (Callable[[float], None]) – Progress callback.
crs
Reference coordinate system.
Type CoordinateSystem or None
data_type
Data type used to store color values.
Type DataType
group
Point cloud group. :type: :class: PointCloudGroup
is_laser_scan
Use point cloud as laser scan. :type: bool
key
Point cloud identifier.
Type int
label
Point cloud label.
Type string
meta
Point cloud meta data.
Type MetaData
modified
Modified flag.
Type bool
pickPoint(origin, target, endpoints=1)
Returns ray intersection with the point cloud (point on the ray nearest to some point).
Parameters

origin (Vector) – Ray origin.

target (Vector) – Point on the ray.

endpoints (int) – Number of endpoints to check for (0 – line, 1 – ray, 2 – segment).
Returns Coordinates of the intersection point.
Return type Vector
point_count
Number of points in point cloud.
Type int
removePoints(point_classes[, progress])
Remove points.
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Parameters

point_classes (PointClass or list of PointClass) – Classes of points to be removed.

progress (Callable[[float], None]) – Progress callback.
removeSelectedPoints([point_classes][, progress])
Remove selected points.
Parameters

point_classes (PointClass or list of PointClass) – Classes of points to be removed.

progress (Callable[[float], None]) – Progress callback.
renderDepth(transform, calibration, point_size=1, resolution=1, cull_points=False, add_alpha=True)
Render point cloud depth image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

point_size (int) – Point size.

resolution (float) – Level of detail resolution in screen pixels.

cull_points (bool) – Enable normal based culling.

add_alpha (bool) – Generate image with alpha channel.
Returns Rendered image.
Return type Image
renderImage(transform, calibration, point_size=1, resolution=1, cull_points=False, add_alpha=True,
raster_transform=RasterTransformNone)
Render point cloud image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

point_size (int) – Point size.

resolution (float) – Level of detail resolution in screen pixels.

cull_points (bool) – Enable normal based culling.

add_alpha (bool) – Generate image with alpha channel.

raster_transform (RasterTransformType) – Raster band transformation.
Returns Rendered image.
Return type Image
renderMask(transform, calibration, point_size=1, resolution=1, cull_points=False)
Render point cloud mask image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

point_size (int) – Point size.
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resolution (float) – Level of detail resolution in screen pixels.

cull_points (bool) – Enable normal based culling.
Returns Rendered image.
Return type Image
renderNormalMap(transform, calibration, point_size=1, resolution=1, cull_points=False, add_alpha=True)
Render image with point cloud normals for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

point_size (int) – Point size.

resolution (float) – Level of detail resolution in screen pixels.

cull_points (bool) – Enable normal based culling.

add_alpha (bool) – Generate image with alpha channel.
Returns Rendered image.
Return type Image
renderPreview(width = 2048, height = 2048[, transform ], point_size=1[, progress])
Generate point cloud preview image.
Parameters

width (int) – Preview image width.

height (int) – Preview image height.

transform (Matrix) – 4×4 viewpoint transformation matrix.

point_size (int) – Point size.

progress (Callable[[float], None]) – Progress callback.
Returns Preview image.
Return type Image
resetFilters()
Reset filters.
restorePoints([point_classes][, progress])
Restore deleted points.
Parameters

point_classes (PointClass or list of PointClass) – Classes of points to be restored.

progress (Callable[[float], None]) – Progress callback.
selectMaskedPoints(cameras, softness=4[, progress])
Select points based on image masks.
Parameters

cameras (list of Camera) – A list of cameras to use for selection.

softness (float) – Mask edge softness.

progress (Callable[[float], None]) – Progress callback.
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selectPointsByColor(color, tolerance=10, channels=’RGB'[, progress])
Select points based on point colors.
Parameters

color (list of int) – Color to select.

tolerance (int) – Color tolerance.

channels (string) – Combination of color channels to compare in [‘R’, ‘G’, ‘B’, ‘H’, ‘S’,
‘V’].

progress (Callable[[float], None]) – Progress callback.
selectPointsByShapes([shapes][, progress])
Select points based on shapes.
Parameters

shapes (list of Shape) – A list of shapes to use for selection (selected shapes if not specified).

progress (Callable[[float], None]) – Progress callback.
setClassesFilter(point_classes)
Set filter by point classes.
Parameters point_classes (PointClass or list of PointClass) – List of point classes.
setConfidenceFilter(min_confidence, max_confidence)
Set filter by confidence.
Parameters

min_confidence (int) – Minimum confidence value.

max_confidence (int) – Maximum confidence value.
setSelectionFilter()
Set filter by selection.
transform
4×4 point cloud transformation matrix.
Type Matrix
updateStatistics([progress])
Updates point cloud statistics.
Parameters progress (Callable[[float], None]) – Progress callback.
class Metashape.PointCloudFormat
Point cloud format in [PointCloudFormatNone, PointCloudFormatOBJ, PointCloudFormatPLY, PointCloudFormatXYZ, PointCloudFormatLAS, PointCloudFormatExpe, PointCloudFormatU3D, PointCloudFormatPDF,
PointCloudFormatE57, PointCloudFormatOC3, PointCloudFormatPotree, PointCloudFormatLAZ, PointCloudFormatCL3, PointCloudFormatPTS, PointCloudFormatPTX, PointCloudFormatDXF, PointCloudFormatCesium, PointCloudFormatPCD, PointCloudFormatSLPK]
class Metashape.PointCloudGroup
PointCloudGroup objects define groups of multiple laser scans. The grouping is established by assignment of a
PointCloudGroup instance to the PointCloud.group attribute of participating laser scans.
crs
Reference coordinate system.
Type CoordinateSystem or None
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fixed
Fix relative laser scan positions within the group.
Type bool
key
Asset group identifier.
Type int
label
Camera group label.
Type string
meta
Asset group meta data.
Type MetaData
selected
Current selection state.
Type bool
transform
4×4 asset group transformation matrix.
Type Matrix
class Metashape.Preselection
Image pair preselection in [NoPreselection, GenericPreselection, ReferencePreselection]
class Metashape.RPCModel
Rational polynomial model.
copy()
Return a copy of the object.
Returns A copy of the object.
Return type RPCModel
error(point, proj)
Returns projection error.
Parameters

point (Vector) – Coordinates of the point to be projected.

proj (Vector) – Pixel coordinates of the point.
Returns 2D projection error.
Return type Vector
image_offset
Image coordinate offset.
Type Vector
image_scale
Image coordinate scale.
Type Vector
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line_den_coeff
Line denominator.
Type Vector
line_num_coeff
Line numerator.
Type Vector
load(path)
Load RPC model from file.
Parameters path (string) – path to RPC model file
object_offset
Object coordinate offset.
Type Vector
object_scale
Object coordinate scale.
Type Vector
project(point)
Returns projected pixel coordinates of the point.
Parameters point (Vector) – Coordinates of the point to be projected.
Returns 2D projected point coordinates.
Return type Vector
samp_den_coeff
Sample denominator.
Type Vector
samp_num_coeff
Sample numerator.
Type Vector
save(path)
Save RPC model to file.
Parameters path (string) – path to RPC model file
unproject(point)
Returns direction corresponding to the image point.
Parameters point (Vector) – Pixel coordinates of the point.
Returns 3D vector in the camera coordinate system.
Return type Vector
class Metashape.RasterFormat
Raster format in [RasterFormatNone, RasterFormatTiles, RasterFormatKMZ, RasterFormatXYZ, RasterFormatMBTiles, RasterFormatWW, RasterFormatTMS, RasterFormatGeoPackage]
class Metashape.RasterTransform
Raster transform definition.
calibrateRange()
Auto detect range based on orthomosaic histogram.
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copy()
Return a copy of the object.
Returns A copy of the object.
Return type RasterTransform
enabled
Enable flag.
Type bool
false_color
False color channels.
Type list
formula
Raster calculator expression.
Type string
interpolation
Interpolation enable flag.
Type bool
palette
Color palette.
Type dict
range
Palette mapping range.
Type tuple
reset()
Reset raster transform.
class Metashape.RasterTransformType
Raster transformation type in [RasterTransformNone, RasterTransformValue, RasterTransformPalette]
class Metashape.ReferenceFormat
Reference format in [ReferenceFormatNone, ReferenceFormatXML, ReferenceFormatTEL, ReferenceFormatCSV, ReferenceFormatMavinci, ReferenceFormatBramor, ReferenceFormatAPM]
class Metashape.ReferenceItems
Reference items in [ReferenceItemsCameras, ReferenceItemsMarkers, ReferenceItemsScalebars]
class Metashape.ReferencePreselectionMode
Reference preselection mode in [ReferencePreselectionSource, ReferencePreselectionEstimated, ReferencePreselectionSequential]
class Metashape.Region
Region parameters
center
Region center coordinates.
Type Vector
copy()
Return a copy of the object.
Returns A copy of the object.
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Return type Region
rot
Region rotation matrix.
Type Matrix
size
Region size.
Type Vector
class Metashape.RotationOrder
Rotation order in [RotationOrderXYZ, RotationOrderXZY, RotationOrderYXZ, RotationOrderYZX, RotationOrderZXY, RotationOrderZYX]
class Metashape.Scalebar
Scale bar instance
class Reference
Scale bar reference data
accuracy
Scale bar length accuracy.
Type float
distance
Scale bar length.
Type float
enabled
Enabled flag.
Type bool
chunk
Chunk the scalebar belongs to.
Type Chunk
frames
Scale bar frames.
Type list of Scalebar
group
Scale bar group.
Type ScalebarGroup
key
Scale bar identifier.
Type int
label
Scale bar label.
Type string
meta
Scale bar meta data.
Type MetaData
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point0
Start of the scale bar.
Type Marker
point1
End of the scale bar.
Type Marker
reference
Scale bar reference data.
Type ScalebarReference
selected
Selects/deselects the scale bar.
Type bool
class Metashape.ScalebarGroup
ScalebarGroup objects define groups of multiple scale bars. The grouping is established by assignment of a
ScalebarGroup instance to the Scalebar.group attribute of participating scale bars.
label
Scale bar group label.
Type string
selected
Current selection state.
Type bool
class Metashape.Sensor
Sensor instance
class Reference
Sensor reference data.
accuracy
Sensor location accuracy.
Type Vector
enabled
Location enabled flag.
Type bool
location
Sensor coordinates.
Type Vector
location_accuracy
Sensor location accuracy.
Type Vector
location_enabled
Location enabled flag.
Type bool
rotation
Sensor rotation angles.
Type Vector
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rotation_accuracy
Sensor rotation accuracy.
Type Vector
rotation_enabled
Rotation enabled flag.
Type bool
class Type
Sensor type in [Frame, Fisheye, Spherical, Cylindrical, RPC]
antenna
GPS antenna correction.
Type Antenna
bands
List of color bands.
Type list of string
black_level
Black level for each band.
Type list of float
calibrateFiducials(resolution=0.014)
Fit fiducial coordinates to image measurements.
Parameters resolution (float) – Scanning resolution in mm/pix.
calibration
Adjusted calibration of the photo.
Type Calibration
chunk
Chunk the sensor belongs to.
Type Chunk
data_type
Data type used to store color values.
Type DataType
fiducials
Fiducial marks.
Type list of Marker
film_camera
Film camera flag.
Type bool
fixed
Fix calibration flag.
Type bool
fixed_calibration
Fix calibration flag.
Type bool
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fixed_location
Fix location flag.
Type bool
fixed_params
List of fixed calibration parameters.
Type list of string
fixed_rotation
Fix rotation flag.
Type bool
focal_length
Focal length in mm.
Type float
height
Image height.
Type int
key
Sensor identifier.
Type int
label
Sensor label.
Type string
layer_index
Sensor layer index.
Type int
location
Sensor plane location.
Type Vector
location_covariance
Sensor plane location covariance.
Type Matrix
makeMaster()
Make this sensor master in the multi-camera system.
master
Master sensor.
Type Sensor
meta
Sensor meta data.
Type MetaData
normalize_sensitivity
Enable sensitivity normalization.
Type bool
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normalize_to_float
Convert pixel values to floating point after normalization.
Type bool
photo_params
List of image-variant calibration parameters.
Type list of string
pixel_height
Pixel height in mm.
Type float
pixel_size
Pixel size in mm.
Type Vector
pixel_width
Pixel width in mm.
Type float
planes
Sensor planes.
Type list of Sensor
reference
Sensor reference data.
Type SensorReference
rolling_shutter
Enable rolling shutter compensation.
Type Shutter.Model
rotation
Sensor plane rotation.
Type Matrix
rotation_covariance
Sensor plane rotation covariance.
Type Matrix
sensitivity
Sensitivity for each band.
Type list of float
type
Sensor projection model.
Type Sensor.Type
user_calib
Custom calibration used as initial calibration during photo alignment.
Type Calibration
vignetting
Vignetting for each band.
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Type list of Vignetting
width
Image width.
Type int
class Metashape.ServiceType
Service type in [ServiceSketchfab, ServiceMapbox, Service4DMapper, ServicePointscene, ServiceMelown, ServicePointbox, ServicePicterra, ServiceCesium]
class Metashape.Shape
Shape data.
class BoundaryType
Shape boundary type in [NoBoundary, OuterBoundary, InnerBoundary]
class Vertices
Collection of shape vertices
area()
Return area of the shape on DEM.
Returns Shape area.
Return type float
areaFitted()
Return 2D area of the shape projected onto the best fitting plane.
Returns Shape area.
Return type float
attributes
Shape attributes.
Type MetaData
boundary_type
Shape boundary type.
Type Shape.BoundaryType
geometry
Shape geometry.
Type Geometry or AttachedGeometry
group
Shape group.
Type ShapeGroup
is_attached
Attached flag.
Type bool
key
Shape identifier.
Type int
label
Shape label.
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Type string
perimeter2D()
Return perimeter of the shape on DEM.
Returns Shape perimeter.
Return type float
perimeter3D()
Return perimeter of the shape.
Returns Shape perimeter.
Return type float
selected
Selects/deselects the shape.
Type bool
volume(level=’bestfit’)
Return volume of the shape measured on DEM above and below best fit, mean level or custom level plane.
Parameters level (float) – Plane level: ‘bestfit’, ‘mean’ or custom value.
Returns Shape volumes.
Return type dict
class Metashape.ShapeGroup
ShapeGroup objects define groups of multiple shapes. The grouping is established by assignment of a ShapeGroup instance to the Shape.group attribute of participating shapes.
color
Shape group color.
Type tuple of 4 int
enabled
Enable flag.
Type bool
key
Shape group identifier.
Type int
label
Shape group label.
Type string
meta
Shape group meta data.
Type MetaData
selected
Current selection state.
Type bool
show_labels
Shape labels visibility flag.
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Type bool
class Metashape.Shapes
A set of shapes for a chunk frame.
addGroup()
Add new shape group to the set of shapes.
Returns Created shape group.
Return type ShapeGroup
addShape()
Add new shape to the set of shapes.
Returns Created shape.
Return type Shape
crs
Shapes coordinate system.
Type CoordinateSystem
group
Default shape group.
Type ShapeGroup
groups
List of shape groups.
Type list of ShapeGroup
items()
List of items.
meta
Shapes meta data.
Type MetaData
modified
Modified flag.
Type bool
projection
Shapes projection.
Type OrthoProjection
remove(items)
Remove items from the shape layer.
Parameters items (list of Shape or ShapeGroup) – A list of items to be removed.
shapes
List of shapes.
Type list of Shape
updateAltitudes(items[, progress])
Update altitudes for items.
Parameters
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items (list of Shape or ShapeGroup) – A list of items to be updated.

progress (Callable[[float], None]) – Progress callback.
class Metashape.ShapesFormat
Shapes format in [ShapesFormatNone, ShapesFormatSHP, ShapesFormatKML, ShapesFormatDXF, ShapesFormatGeoJSON, ShapesFormatGeoPackage, ShapesFormatCSV]
class Metashape.Shutter
Shutter object contains estimated parameters of the rolling shutter correction model.
class Model
Rolling shutter model in [Disabled, Regularized, Full]
copy()
Return a copy of the object.
Returns A copy of the object.
Return type Shutter
rotation
Rotation matrix of the rolling shutter model.
Type Matrix
translation
Translation vector of the rolling shutter model.
Type Vector
class Metashape.SurfaceType
Surface type in [Arbitrary, HeightField]
class Metashape.Target
Target parameters
code
Target code.
Type int
coord
Target location.
Type Vector
copy()
Return a copy of the object.
Returns A copy of the object.
Return type Target
radius
Target radius.
Type float
class Metashape.TargetType
Target type in [CircularTarget12bit, CircularTarget14bit, CircularTarget16bit, CircularTarget20bit, CircularTarget, CrossTarget]
class Metashape.Tasks
Task classes.
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class AddFrames
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
chunk
Chunk to copy frames from.
Type int
copy_depth_maps
Copy depth maps.
Type bool
copy_elevation
Copy DEM.
Type bool
copy_model
Copy model.
Type bool
copy_orthomosaic
Copy orthomosaic.
Type bool
copy_point_cloud
Copy point cloud.
Type bool
copy_tiled_model
Copy tiled model.
Type bool
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
frames
List of frame keys to copy.
Type list of int
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
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target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class AddPhotos
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
filegroups
List of file groups.
Type list of int
filenames
List of files to add.
Type list of string
group
Camera group key.
Type int
layout
Image layout.
Type ImageLayout
load_reference
Load reference coordinates.
Type bool
load_rpc_txt
Load satellite RPC data from auxiliary TXT files.
Type bool
load_xmp_accuracy
Load accuracy from XMP meta data.
Type bool
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load_xmp_antenna
Load GPS/INS offset from XMP meta data.
Type bool
load_xmp_calibration
Load calibration from XMP meta data.
Type bool
load_xmp_orientation
Load orientation from XMP meta data.
Type bool
name
Task name.
Type string
strip_extensions
Strip file extensions from camera labels.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class AlignCameras
Task class containing processing parameters.
adaptive_fitting
Enable adaptive fitting of distortion coefficients.
Type bool
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to align.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
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encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
min_image
Minimum number of point projections.
Type int
name
Task name.
Type string
point_clouds
List of point clouds to align.
Type list of int
reset_alignment
Reset current alignment.
Type bool
subdivide_task
Enable fine-level task subdivision.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class AlignChunks
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
chunks
List of chunks to be aligned.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
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downscale
Alignment accuracy.
Type int
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
filter_mask
Filter points by mask.
Type bool
fit_scale
Fit chunk scale during alignment.
Type bool
generic_preselection
Enables image pair preselection.
Type bool
keypoint_limit
Maximum number of points for each photo.
Type int
markers
List of markers to be used for marker based alignment.
Type list of int
mask_tiepoints
Apply mask filter to tie points.
Type bool
method
Alignment method (0 – point based, 1 – marker based, 2 – camera based).
Type int
name
Task name.
Type string
reference
Chunk to be used as a reference.
Type int
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
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class AnalyzeImages
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to be analyzed.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
filter_mask
Constrain analyzed image region by mask.
Type bool
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class BuildContours
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
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decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
interval
Contour interval.
Type float
max_value
Maximum value of contour range.
Type float
min_value
Minimum value of contour range.
Type float
name
Task name.
Type string
prevent_intersections
Prevent contour intersections.
Type bool
source_data
Source data for contour generation.
Type DataSource
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class BuildDem
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
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classes
List of point classes to be used for surface extraction.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
flip_x
Flip X axis direction.
Type bool
flip_y
Flip Y axis direction.
Type bool
flip_z
Flip Z axis direction.
Type bool
interpolation
Interpolation mode.
Type Interpolation
max_workgroup_size
Maximum workgroup size.
Type int
name
Task name.
Type string
projection
Output projection.
Type OrthoProjection
region
Region to be processed.
Type BBox
resolution
Output resolution in meters.
Type float
source_data
Selects between point cloud and tie points.
Type DataSource
subdivide_task
Enable fine-level task subdivision.
Type bool
supports_gpu
GPU support flag.
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Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
workitem_size_tiles
Number of tiles in a workitem.
Type int
class BuildDepthMaps
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
downscale
Depth map quality.
Type int
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
filter_mode
Depth map filtering mode.
Type FilterMode
max_neighbors
Maximum number of neighbor images to use for depth map generation.
Type int
max_workgroup_size
Maximum workgroup size.
Type int
name
Task name.
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Type string
reuse_depth
Enable reuse depth maps option.
Type bool
subdivide_task
Enable fine-level task subdivision.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
workitem_size_cameras
Number of cameras in a workitem.
Type int
class BuildModel
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
classes
List of point classes to be used for surface extraction.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
face_count
Target face count.
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Type FaceCount
face_count_custom
Custom face count.
Type int
interpolation
Interpolation mode.
Type Interpolation
keep_depth
Enable store depth maps option.
Type bool
max_workgroup_size
Maximum workgroup size.
Type int
name
Task name.
Type string
source_data
Selects between point cloud, tie points and depth maps.
Type DataSource
subdivide_task
Enable fine-level task subdivision.
Type bool
supports_gpu
GPU support flag.
Type bool
surface_type
Type of object to be reconstructed.
Type SurfaceType
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
trimming_radius
Trimming radius (no trimming if zero).
Type int
vertex_colors
Enable vertex colors calculation.
Type bool
vertex_confidence
Enable vertex confidence calculation.
Type bool
volumetric_masks
Enable strict volumetric masking.
Type bool
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workitem_count
Work item count.
Type int
workitem_size_cameras
Number of cameras in a workitem.
Type int
class BuildOrthomosaic
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
blending_mode
Orthophoto blending mode.
Type BlendingMode
cull_faces
Enable back-face culling.
Type bool
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
fill_holes
Enable hole filling.
Type bool
flip_x
Flip X axis direction.
Type bool
flip_y
Flip Y axis direction.
Type bool
flip_z
Flip Z axis direction.
Type bool
ghosting_filter
Enable ghosting filter.
Type bool
max_workgroup_size
Maximum workgroup size.
Type int
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name
Task name.
Type string
projection
Output projection.
Type OrthoProjection
refine_seamlines
Refine seamlines based on image content.
Type bool
region
Region to be processed.
Type BBox
resolution
Pixel size in meters.
Type float
resolution_x
Pixel size in the X dimension in projected units.
Type float
resolution_y
Pixel size in the Y dimension in projected units.
Type float
subdivide_task
Enable fine-level task subdivision.
Type bool
supports_gpu
GPU support flag.
Type bool
surface_data
Orthorectification surface.
Type DataSource
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
workitem_size_cameras
Number of cameras in a workitem.
Type int
workitem_size_tiles
Number of tiles in a workitem.
Type int
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class BuildPanorama
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
blending_mode
Panorama blending mode.
Type BlendingMode
camera_groups
List of camera groups to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
frames
List of frames to process.
Type list of int
ghosting_filter
Enable ghosting filter.
Type bool
height
Height of output panorama.
Type int
name
Task name.
Type string
region
Region to be generated.
Type BBox
rotation
Panorama 3×3 orientation matrix.
Type Matrix
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
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toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
width
Width of output panorama.
Type int
workitem_count
Work item count.
Type int
class BuildPointCloud
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
asset
Asset to process.
Type int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
keep_depth
Enable store depth maps option.
Type bool
max_neighbors
Maximum number of neighbor images to use for depth map filtering.
Type int
max_workgroup_size
Maximum workgroup size.
Type int
name
Task name.
Type string
point_colors
Enable point colors calculation.
Type bool
point_confidence
Enable point confidence calculation.
Type bool
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points_spacing
Desired point spacing (m).
Type float
source_data
Source data to extract points from.
Type DataSource
subdivide_task
Enable fine-level task subdivision.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
uniform_sampling
Enable uniform point sampling.
Type bool
workitem_count
Work item count.
Type int
workitem_size_cameras
Number of cameras in a workitem.
Type int
class BuildSeamlines
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
epsilon
Contour simplificaion threshold.
Type float
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name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class BuildTexture
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
blending_mode
Texture blending mode.
Type BlendingMode
cameras
A list of cameras to be used for texturing.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
fill_holes
Enable hole filling.
Type bool
ghosting_filter
Enable ghosting filter.
Type bool
name
Task name.
Type string
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source_model
Source model.
Type int
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
texture_size
Texture page size.
Type int
texture_type
Texture type.
Type Model.TextureType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
transfer_texture
Transfer texture.
Type bool
workitem_count
Work item count.
Type int
class BuildTiledModel
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
classes
List of point classes to be used for surface extraction.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
face_count
Number of faces per megapixel of texture resolution.
Type int
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ghosting_filter
Enable ghosting filter.
Type bool
keep_depth
Enable store depth maps option.
Type bool
max_workgroup_size
Maximum workgroup size.
Type int
merge
Merge tiled model flag.
Type bool
name
Task name.
Type string
operand_asset
Operand asset key.
Type int
operand_chunk
Operand chunk key.
Type int
operand_frame
Operand frame key.
Type int
pixel_size
Target model resolution in meters.
Type float
source_data
Selects between point cloud and mesh.
Type DataSource
subdivide_task
Enable fine-level task subdivision.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
tile_size
Size of tiles in pixels.
Type int
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
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transfer_texture
Transfer source model texture to tiled model.
Type bool
workitem_count
Work item count.
Type int
workitem_size_cameras
Number of cameras in a workitem.
Type int
class BuildUV
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
camera
Camera to be used for texturing in MappingCamera mode.
Type int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
mapping_mode
Texture mapping mode.
Type MappingMode
name
Task name.
Type string
page_count
Number of texture pages to generate.
Type int
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
texture_size
Expected size of texture page at texture generation step.
Type int
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toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class CalculatePointNormals
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
point_cloud
Point cloud key to process.
Type int
point_neighbors
Number of point neighbors to use for normal estimation.
Type int
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class CalibrateCamera
Task class containing processing parameters.
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apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
border
Border size to ignore.
Type int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
fit_b1
Enable optimization of aspect ratio.
Type bool
fit_b2
Enable optimization of skew coefficient.
Type bool
fit_cxcy
Enable optimization of principal point coordinates.
Type bool
fit_f
Enable optimization of focal length coefficient.
Type bool
fit_k1
Enable optimization of k1 radial distortion coefficient.
Type bool
fit_k2
Enable optimization of k2 radial distortion coefficient.
Type bool
fit_k3
Enable optimization of k3 radial distortion coefficient.
Type bool
fit_k4
Enable optimization of k4 radial distortion coefficient.
Type bool
fit_p1
Enable optimization of p1 tangential distortion coefficient.
Type bool
fit_p2
Enable optimization of p2 tangential distortion coefficient.
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Type bool
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class CalibrateColors
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
source_data
Source data for calibration.
Type DataSource
supports_gpu
GPU support flag.
Type bool
target
Task target.
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Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
white_balance
Calibrate white balance.
Type bool
workitem_count
Work item count.
Type int
class CalibrateReflectance
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
use_reflectance_panels
Use calibrated reflectance panels.
Type bool
use_sun_sensor
Apply irradiance sensor measurements.
Type bool
workitem_count
Work item count.
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Type int
class ClassifyGroundPoints
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cell_size
Cell size (meters).
Type float
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
erosion_radius
Erosion radius (meters).
Type float
keep_existing
Keep existing ground points.
Type bool
max_angle
Maximum angle (degrees).
Type float
max_distance
Maximum distance (meters).
Type float
name
Task name.
Type string
point_cloud
Point cloud key to classify.
Type int
return_number
Point return number to use (0 – any return, 1 – first return, -1 – last return).
Type int
source_class
Class of points to be re-classified.
Type int
supports_gpu
GPU support flag.
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Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ClassifyPoints
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
confidence
Required confidence level.
Type float
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
point_cloud
Point cloud key to classify.
Type int
source_class
Class of points to be re-classified.
Type int
subdivide_task
Enable fine-level task subdivision.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
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Type Tasks.TargetType
target_classes
Target point classes for classification.
Type list of int
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class CloseHoles
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
apply_to_selection
Close holes within selection.
Type bool
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
level
Hole size threshold in percents.
Type int
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
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Type int
class ColorizeModel
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
source_data
Source data to extract colors from.
Type DataSource
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ColorizePointCloud
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
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decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
max_workgroup_size
Maximum workgroup size.
Type int
name
Task name.
Type string
point_cloud
Point cloud key to colorize.
Type int
source_data
Source data to extract colors from.
Type DataSource
subdivide_task
Enable fine-level task subdivision.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
workitem_size_cameras
Number of cameras in a workitem.
Type int
class CompactPointCloud
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
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decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
point_cloud
Point cloud key to process.
Type int
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ConvertImages
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
color_correction
Apply color correction.
Type bool
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
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image_compression
Image compression parameters.
Type ImageCompression
merge_planes
Merge multispectral images.
Type bool
name
Task name.
Type string
path
Path to output file.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
update_gps_tags
Update GPS tags.
Type bool
use_initial_calibration
Transform to initial calibration.
Type bool
workitem_count
Work item count.
Type int
class DecimateModel
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
apply_to_selection
Apply to selection.
Type bool
asset
Model to process.
Type int
decode(dict)
Initialize task parameters with a dictionary.
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decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
face_count
Target face count.
Type int
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class DetectFiducials
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
fiducials_position_corners
Search corners for fiducials.
Type bool
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fiducials_position_sides
Search sides for fiducials.
Type bool
frames
List of frames to process.
Type list of int
generate_masks
Generate background masks.
Type bool
generic_detector
Use generic detector.
Type bool
name
Task name.
Type string
right_angle_detector
Use right angle detector.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
v_shape_detector
Detect V-shape fiducials.
Type bool
workitem_count
Work item count.
Type int
class DetectMarkers
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
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decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
filter_mask
Ignore masked image regions.
Type bool
frames
List of frames to process.
Type list of int
inverted
Detect markers on black background.
Type bool
maximum_residual
Maximum residual for non-coded targets in pixels.
Type float
minimum_dist
Minimum distance between targets in pixels (CrossTarget type only).
Type int
minimum_size
Minimum target radius in pixels to be detected (CrossTarget type only).
Type int
name
Task name.
Type string
noparity
Disable parity checking.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
target_type
Type of targets.
Type TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
tolerance
Detector tolerance (0 – 100).
Type int
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workitem_count
Work item count.
Type int
class DetectPowerlines
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
max_quantization_error
Maximum allowed distance between polyline and smooth continuous curve.
Type float
min_altitude
Minimum altitude for reconstructed powerlines.
Type float
n_points_per_line
Maximum number of vertices per detected line.
Type int
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
use_model
Use model for visibility checks.
Type bool
workitem_count
Work item count.
Type int
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class DuplicateAsset
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
asset_key
Asset key.
Type int
asset_type
Asset type.
Type DataSource
clip_to_boundary
Clip to boundary shapes.
Type bool
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class DuplicateChunk
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.
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workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
chunk
Chunk to copy.
Type int
copy_depth_maps
Copy depth maps.
Type bool
copy_elevations
Copy DEMs.
Type bool
copy_keypoints
Copy keypoints.
Type bool
copy_models
Copy models.
Type bool
copy_orthomosaics
Copy orthomosaics.
Type bool
copy_point_clouds
Copy point clouds.
Type bool
copy_tiled_models
Copy tiled models.
Type bool
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
frames
List of frame keys to copy.
Type list of int
label
New chunk label.
Type string
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
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target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ExportCameras
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
binary
Enables/disables binary encoding for selected format (if applicable).
Type bool
bingo_path_geoin
Path to BINGO GEO INPUT file.
Type string
bingo_path_gps
Path to BINGO GPS/IMU file.
Type string
bingo_path_image
Path to BINGO IMAGE COORDINATE file.
Type string
bingo_path_itera
Path to BINGO ITERA file.
Type string
bingo_save_geoin
Enables/disables export of BINGO GEO INPUT file.
Type bool
bingo_save_gps
Enables/disables export of BINGO GPS/IMU data.
Type bool
bingo_save_image
Enables/disables export of BINGO IMAGE COORDINATE file.
Type bool
bingo_save_itera
Enables/disables export of BINGO ITERA file.
Type bool
bundler_path_list
Path to Bundler image list file.
Type string
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bundler_save_list
Enables/disables export of Bundler image list file.
Type bool
chan_rotation_order
Rotation order (CHAN format only).
Type RotationOrder
crs
Output coordinate system.
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
format
Export format.
Type CamerasFormat
image_orientation
Image coordinate system (0 – X right, 1 – X up, 2 – X left, 3 – X down).
Type int
name
Task name.
Type string
path
Path to output file.
Type string
save_invalid_matches
Enables/disables export of invalid image matches.
Type bool
save_markers
Enables/disables export of manual matching points.
Type bool
save_points
Enables/disables export of automatic tie points.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
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Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
use_initial_calibration
Transform image coordinates to initial calibration.
Type bool
use_labels
Enables/disables label based item identifiers.
Type bool
workitem_count
Work item count.
Type int
class ExportMarkers
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
binary
Enables/disables binary encoding for selected format (if applicable).
Type bool
crs
Output coordinate system.
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
path
Path to output file.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
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Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ExportMasks
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
path
Path to output file.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ExportModel
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters
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object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
binary
Enables/disables binary encoding (if supported by format).
Type bool
clip_to_boundary
Clip model to boundary shapes.
Type bool
colors_rgb_8bit
Convert colors to 8 bit RGB.
Type bool
comment
Optional comment (if supported by selected format).
Type string
crs
Output coordinate system.
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
embed_texture
Embeds texture inside the model file (if supported by format).
Type bool
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
format
Export format.
Type ModelFormat
model
Model key to export.
Type int
name
Task name.
Type string
path
Path to output model.
Type string
precision
Number of digits after the decimal point (for text formats).
Type int
raster_transform
Raster band transformation.
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Type RasterTransformType
save_alpha
Enables/disables alpha channel export.
Type bool
save_cameras
Enables/disables camera export.
Type bool
save_colors
Enables/disables export of vertex colors.
Type bool
save_comment
Enables/disables comment export.
Type bool
save_confidence
Enables/disables export of vertex confidence.
Type bool
save_markers
Enables/disables marker export.
Type bool
save_metadata_xml
Save metadata.xml file.
Type bool
save_normals
Enables/disables export of vertex normals.
Type bool
save_texture
Enables/disables texture export.
Type bool
save_udim
Enables/disables UDIM texture layout.
Type bool
save_uv
Enables/disables uv coordinates export.
Type bool
shift
Optional shift to be applied to vertex coordinates.
Type Vector
strip_extensions
Strips camera label extensions during export.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
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texture_format
Texture format.
Type ImageFormat
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
viewpoint
Default view.
Type Viewpoint
workitem_count
Work item count.
Type int
class ExportOrthophotos
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
image_compression
Image compression parameters.
Type ImageCompression
name
Task name.
Type string
north_up
Use north-up orientation for export.
Type bool
path
Path to output orthophoto.
Type string
projection
Output projection.
Type OrthoProjection
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raster_transform
Raster band transformation.
Type RasterTransformType
region
Region to be exported.
Type BBox
resolution
Output resolution in meters.
Type float
resolution_x
Pixel size in the X dimension in projected units.
Type float
resolution_y
Pixel size in the Y dimension in projected units.
Type float
save_alpha
Enable alpha channel generation.
Type bool
save_kml
Enable kml file generation.
Type bool
save_world
Enable world file generation.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
white_background
Enable white background.
Type bool
workitem_count
Work item count.
Type int
class ExportPointCloud
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
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binary
Enables/disables binary encoding for selected format (if applicable).
Type bool
block_height
Block height in meters.
Type float
block_width
Block width in meters.
Type float
classes
List of point classes to be exported.
Type list of int
clip_to_boundary
Clip point cloud to boundary shapes.
Type bool
colors_rgb_8bit
Convert colors to 8 bit RGB.
Type bool
comment
Optional comment (if supported by selected format).
Type string
compression
Enable compression (Cesium format only).
Type bool
crs
Output coordinate system.
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
folder_depth
Tileset subdivision depth (Cesium format only).
Type int
format
Export format.
Type PointCloudFormat
image_format
Image data format.
Type ImageFormat
name
Task name.
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Type string
path
Path to output file.
Type string
point_cloud
Point cloud key to export.
Type int
raster_transform
Raster band transformation.
Type RasterTransformType
region
Region to be exported.
Type BBox
save_comment
Enable comment export.
Type bool
save_images
Enable image export.
Type bool
save_point_classification
Enables/disables export of point classification.
Type bool
save_point_color
Enables/disables export of point color.
Type bool
save_point_confidence
Enables/disables export of point confidence.
Type bool
save_point_index
Enables/disables export of point row and column indices.
Type bool
save_point_intensity
Enables/disables export of point intensity.
Type bool
save_point_normal
Enables/disables export of point normal.
Type bool
save_point_return_number
Enables/disables export of point return number.
Type bool
save_point_scan_angle
Enables/disables export of point scan angle.
Type bool
save_point_source_id
Enables/disables export of point source ID.
Type bool
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save_point_timestamp
Enables/disables export of point timestamp.
Type bool
screen_space_error
Target screen space error (Cesium format only).
Type float
shift
Optional shift to be applied to point coordinates.
Type Vector
source_data
Selects between point cloud and tie points. If not specified, uses point cloud if available.
Type DataSource
split_in_blocks
Enable tiled export.
Type bool
subdivide_task
Enable fine-level task subdivision.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
viewpoint
Default view.
Type Viewpoint
workitem_count
Work item count.
Type int
class ExportRaster
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
block_height
Raster block height in pixels.
Type int
block_width
Raster block width in pixels.
Type int
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clip_to_boundary
Clip raster to boundary shapes.
Type bool
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
description
Export description.
Type string
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
format
Export format.
Type RasterFormat
global_profile
Use global profile (GeoPackage format only).
Type bool
height
Raster height.
Type int
image_compression
Image compression parameters.
Type ImageCompression
image_description
Optional description to be added to image files.
Type string
image_format
Tile format.
Type ImageFormat
max_zoom_level
Maximum zoom level (GeoPackage, Google Map Tiles, MBTiles and World Wind Tiles formats only).
Type int
min_zoom_level
Minimum zoom level (GeoPackage, Google Map Tiles, MBTiles and World Wind Tiles formats only).
Type int
name
Task name.
Type string
network_links
Enable network links generation for KMZ format.
Type bool
nodata_value
No-data value (DEM export only).
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Type float
north_up
Use north-up orientation for export.
Type bool
path
Path to output orthomosaic.
Type string
projection
Output projection.
Type OrthoProjection
raster_transform
Raster band transformation.
Type RasterTransformType
region
Region to be exported.
Type BBox
resolution
Output resolution in meters.
Type float
resolution_x
Pixel size in the X dimension in projected units.
Type float
resolution_y
Pixel size in the Y dimension in projected units.
Type float
save_alpha
Enable alpha channel generation.
Type bool
save_kml
Enable kml file generation.
Type bool
save_scheme
Enable tile scheme files generation.
Type bool
save_world
Enable world file generation.
Type bool
source_data
Selects between DEM and orthomosaic.
Type DataSource
split_in_blocks
Split raster in blocks.
Type bool
supports_gpu
GPU support flag.
Type bool
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target
Task target.
Type Tasks.TargetType
tile_height
Tile height in pixels.
Type int
tile_width
Tile width in pixels.
Type int
title
Export title.
Type string
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
white_background
Enable white background.
Type bool
width
Raster width.
Type int
workitem_count
Work item count.
Type int
world_transform
2×3 raster-to-world transformation matrix.
Type Matrix
class ExportReference
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
columns
Column order in csv format (n – label, o – enabled flag, x/y/z – coordinates, X/Y/Z – coordinate accuracy, a/b/c – rotation angles, A/B/C – rotation angle accuracy, u/v/w – estimated coordinates, U/V/W

coordinate errors, d/e/f – estimated orientation angles, D/E/F – orientation errors, p/q/r – estimated
coordinates variance, i/j/k – estimated orientation angles variance, [] – group of multiple values, | –
column separator within group).
Type string
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
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delimiter
Column delimiter in csv format.
Type string
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
format
Export format.
Type ReferenceFormat
items
Items to export in CSV format.
Type ReferenceItems
name
Task name.
Type string
path
Path to the output file.
Type string
precision
Number of digits after the decimal point (for CSV format).
Type int
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ExportReport
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
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description
Report description.
Type string
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
font_size
Font size (pt).
Type int
include_system_info
Include system information.
Type bool
name
Task name.
Type string
page_numbers
Enable page numbers.
Type bool
path
Path to output report.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
title
Report title.
Type string
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
user_settings
A list of user defined settings to include on the Processing Parameters page.
Type list of (string, string) tuples
workitem_count
Work item count.
Type int
class ExportShapes
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.
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workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
crs
Output coordinate system.
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
format
Export format.
Type ShapesFormat
groups
A list of shape groups to export.
Type list of int
name
Task name.
Type string
path
Path to shape file.
Type string
polygons_as_polylines
Save polygons as polylines.
Type bool
save_attributes
Export attributes.
Type bool
save_labels
Export labels.
Type bool
save_points
Export points.
Type bool
save_polygons
Export polygons.
Type bool
save_polylines
Export polylines.
Type bool
shift
Optional shift to be applied to vertex coordinates.
Type Vector
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supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ExportTexture
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
path
Path to output file.
Type string
raster_transform
Raster band transformation.
Type RasterTransformType
save_alpha
Enable alpha channel export.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
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texture_type
Texture type.
Type Model.TextureType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ExportTiledModel
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
clip_to_boundary
Clip tiled model to boundary shapes.
Type bool
crs
Output coordinate system.
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
folder_depth
Tileset subdivision depth (Cesium format only).
Type int
format
Export format.
Type TiledModelFormat
image_compression
Image compression parameters.
Type ImageCompression
model_compression
Enable mesh compression (Cesium format only).
Type bool
model_format
Model format for zip export.
Type ModelFormat
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name
Task name.
Type string
path
Path to output model.
Type string
raster_transform
Raster band transformation.
Type RasterTransformType
screen_space_error
Target screen space error (Cesium format only).
Type float
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
texture_format
Texture format.
Type ImageFormat
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
use_rtc_center
Use RTC_CENTER offset instead of root tile transform (Cesium format only).
Type bool
workitem_count
Work item count.
Type int
class FilterPointCloud
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
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name
Task name.
Type string
point_cloud
Point cloud key to filter.
Type int
point_spacing
Desired point spacing (m).
Type float
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class GenerateMasks
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
blur_threshold
Allowed blur radius on a photo in pix (only if mask_defocus=True).
Type float
cameras
Optional list of cameras to be processed.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
depth_threshold
Maximum depth of masked areas in meters (only if mask_defocus=False).
Type float
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
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fix_coverage
Extend masks to cover whole mesh (only if mask_defocus=True).
Type bool
mask_defocus
Mask defocus areas.
Type bool
mask_operation
Mask operation.
Type MaskOperation
masking_mode
Mask generation mode.
Type MaskingMode
name
Task name.
Type string
path
Mask file name template.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
tolerance
Background masking tolerance.
Type int
workitem_count
Work item count.
Type int
class GeneratePrescriptionMap
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
boundary_shape_group
Boundary shape group.
Type int
breakpoints
Classification breakpoints.
Type list of float
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cell_size
Step of prescription grid, meters.
Type float
class_count
Number of classes.
Type int
classification_method
Index values classification method.
Type ClassificationMethod
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
rates
Fertilizer rate for each class.
Type list of float
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ImportCameras
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
crs
Ground coordinate system.
Type CoordinateSystem
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decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
format
File format.
Type CamerasFormat
image_list
Path to image list file (Bundler format only).
Type string
image_orientation
Image coordinate system (0 – X right, 1 – X up, 2 – X left, 3 – X down).
Type int
load_image_list
Enable Bundler image list import.
Type bool
name
Task name.
Type string
path
Path to the file.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ImportDepthImages
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
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color_filenames
List of corresponding color files, if present.
Type list of string
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
filenames
List of files to import.
Type list of string
format
Point cloud format.
Type PointCloudFormat
image_path
Path template to output files.
Type string
multiplane
Import as a multi-camera system
Type bool
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ImportMarkers
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
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decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
path
Path to the file.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ImportModel
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
crs
Model coordinate system.
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
decode_udim
Load UDIM texture layout.
Type bool
encode()
Create a dictionary with task parameters.
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encodeJSON()
Create a JSON string with task parameters.
format
Model format.
Type ModelFormat
name
Task name.
Type string
path
Path to model.
Type string
shift
Optional shift to be applied to vertex coordinates.
Type Vector
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ImportPointCloud
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
calculate_normals
Calculate point normals.
Type bool
crs
Point cloud coordinate system.
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
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encodeJSON()
Create a JSON string with task parameters.
format
Point cloud format.
Type PointCloudFormat
frame_paths
List of point cloud paths to import in each frame of a multiframe chunk.
Type list of string
ignore_scanner_origin
Do not use laser scan origin as scanner position for structured point clouds.
Type bool
ignore_trajectory
Do not attach trajectory to imported point cloud.
Type bool
import_images
Import images embedded in laser scan.
Type bool
is_laser_scan
Import point clouds as laser scans.
Type bool
name
Task name.
Type string
path
Path to point cloud.
Type string
point_neighbors
Number of point neighbors to use for normal estimation.
Type int
precision
Coordinate precision (m).
Type float
replace_asset
Replace default asset with imported point cloud.
Type bool
scanner_at_origin
Use laser scan origin as scanner position for unstructured point clouds.
Type bool
shift
Optional shift to be applied to point coordinates.
Type Vector
supports_gpu
GPU support flag.
Type bool
target
Task target.
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Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
trajectory
Trajectory key to attach.
Type int
workitem_count
Work item count.
Type int
class ImportRaster
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
crs
Default coordinate system if not specified in GeoTIFF file.
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
has_nodata_value
No-data value valid flag.
Type bool
name
Task name.
Type string
nodata_value
No-data value.
Type float
path
Path to elevation model in GeoTIFF format.
Type string
raster_type
Type of raster layer to import.
Type DataSource
supports_gpu
GPU support flag.
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Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ImportReference
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
columns
Column order in csv format (n – label, o – enabled flag, x/y/z – coordinates, X/Y/Z – coordinate accuracy,
a/b/c – rotation angles, A/B/C – rotation angle accuracy, [] – group of multiple values, | – column
separator within group).
Type string
create_markers
Create markers for missing entries (csv format only).
Type bool
crs
Reference data coordinate system (csv format only).
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
delimiter
Column delimiter in csv format.
Type string
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
format
File format.
Type ReferenceFormat
group_delimiters
Combine consecutive delimiters in csv format.
Type bool
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ignore_labels
Matches reference data based on coordinates alone (csv format only).
Type bool
items
List of items to load reference for (csv format only).
Type ReferenceItems
name
Task name.
Type string
path
Path to the file with reference data.
Type string
shutter_lag
Shutter lag in seconds (APM format only).
Type float
skip_rows
Number of rows to skip in (csv format only).
Type int
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
threshold
Error threshold in meters used when ignore_labels is set (csv format only).
Type float
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ImportShapes
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
boundary_type
Boundary type to be applied to imported shapes.
Type Shape.BoundaryType
columns
Column order in csv format (n – label, x/y/z – coordinates, d – description, [] – group of multiple values,
| – column separator within group).
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Type string
crs
Reference data coordinate system (csv format only).
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
delimiter
Column delimiter in csv format.
Type string
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
format
Shapes format.
Type ShapesFormat
group_delimiters
Combine consequitive delimiters in csv format.
Type bool
name
Task name.
Type string
path
Path to shape file.
Type string
replace
Replace current shapes with new data.
Type bool
skip_rows
Number of rows to skip in (csv format only).
Type int
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
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class ImportTiledModel
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
path
Path to tiled model.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ImportTrajectory
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
columns
Column order (t – time, x/y/z – coordinates, space – skip column).
Type string
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crs
Point cloud coordinate system.
Type CoordinateSystem
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
delimiter
CSV delimiter.
Type string
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
format
Trajectory format.
Type TrajectoryFormat
name
Task name.
Type string
path
Trajectory file path.
Type string
replace_asset
Replace default asset with imported point cloud.
Type bool
shift
Optional shift to be applied to point coordinates.
Type Vector
skip_rows
Number of rows to skip.
Type int
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class InvertMasks
Task class containing processing parameters.
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apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class LoadProject
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
archive
Override project format when using non-standard file extension.
Type bool
decode(dict)
Initialize task parameters with a dictionary.
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decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
path
Path to project file.
Type string
read_only
Open project in read only mode.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class MatchPhotos
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to match.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
downscale
Image alignment accuracy.
Type int
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encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
filter_mask
Filter points by mask.
Type bool
filter_stationary_points
Exclude tie points which are stationary across images.
Type bool
generic_preselection
Enable generic preselection.
Type bool
guided_matching
Enable guided image matching.
Type bool
keep_keypoints
Store keypoints in the project.
Type bool
keypoint_limit
Key point limit.
Type int
keypoint_limit_per_mpx
Key point limit per megapixel.
Type int
mask_tiepoints
Apply mask filter to tie points.
Type bool
max_workgroup_size
Maximum workgroup size.
Type int
name
Task name.
Type string
pairs
User defined list of camera pairs to match.
Type list of (int, int) tuples
reference_preselection
Enable reference preselection.
Type bool
reference_preselection_mode
Reference preselection mode.
Type ReferencePreselectionMode
reset_matches
Reset current matches.
Type bool
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subdivide_task
Enable fine-level task subdivision.
Type bool
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
tiepoint_limit
Tie point limit.
Type int
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
workitem_size_cameras
Number of cameras in a workitem.
Type int
workitem_size_pairs
Number of image pairs in a workitem.
Type int
class MergeAssets
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
assets
List of assets to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
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source_data
Asset type.
Type DataSource
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class MergeChunks
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
chunks
List of chunks to process.
Type list of int
copy_depth_maps
Copy depth maps.
Type bool
copy_elevations
Copy DEMs.
Type bool
copy_laser_scans
Copy laser scans.
Type bool
copy_models
Copy models.
Type bool
copy_orthomosaics
Copy orthomosaics.
Type bool
copy_point_clouds
Copy point clouds.
Type bool
copy_tiled_models
Copy tiled models.
Type bool
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decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
merge_assets
Merge default assets.
Type bool
merge_markers
Merge markers.
Type bool
merge_tiepoints
Merge tie points.
Type bool
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class OptimizeCameras
Task class containing processing parameters.
adaptive_fitting
Enable adaptive fitting of distortion coefficients.
Type bool
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
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decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
fit_b1
Enable optimization of aspect ratio.
Type bool
fit_b2
Enable optimization of skew coefficient.
Type bool
fit_corrections
Enable optimization of additional corrections.
Type bool
fit_cx
Enable optimization of X principal point coordinates.
Type bool
fit_cy
Enable optimization of Y principal point coordinates.
Type bool
fit_f
Enable optimization of focal length coefficient.
Type bool
fit_k1
Enable optimization of k1 radial distortion coefficient.
Type bool
fit_k2
Enable optimization of k2 radial distortion coefficient.
Type bool
fit_k3
Enable optimization of k3 radial distortion coefficient.
Type bool
fit_k4
Enable optimization of k3 radial distortion coefficient.
Type bool
fit_p1
Enable optimization of p1 tangential distortion coefficient.
Type bool
fit_p2
Enable optimization of p2 tangential distortion coefficient.
Type bool
name
Task name.
Type string
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supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
tiepoint_covariance
Estimate tie point covariance matrices.
Type bool
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class PlanMission
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
attach_viewpoints
Generate additional viewpoints to increase coverage.
Type bool
capture_distance
Image capture distance (m).
Type float
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
group_attached_viewpoints
Ignore minimum waypoint spacing for additional viewpoints.
Type bool
home_point
Home point shape key.
Type int
horizontal_zigzags
Cover surface with horizontal zigzags instead of vertical.
Type bool
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interesting_zone
Interesting zone shape layer key.
Type int
max_pitch
Maximum camera pitch angle.
Type int
min_altitude
Minimum altitude (m).
Type float
min_pitch
Minimum camera pitch angle.
Type int
min_waypoint_spacing
Minimum waypoint spacing (m).
Type float
name
Task name.
Type string
overlap
Overlap percent.
Type int
powerlines
Powerlines shape layer key.
Type int
restricted_zone
Restricted zone shape layer key.
Type int
safety_distance
Safety distance (m).
Type float
safety_zone
Safety zone shape layer key.
Type int
sensor
Sensor key.
Type int
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
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use_selection
Focus on model selection.
Type bool
workitem_count
Work item count.
Type int
class PublishData
Task class containing processing parameters.
account
Account name (Melown service).
Type string
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
description
Dataset description.
Type string
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
hostname
Service hostname (4DMapper service).
Type string
image_compression
Image compression parameters.
Type ImageCompression
is_draft
Mark dataset as draft (Sketchfab service).
Type bool
is_private
Set dataset access to private (Pointbox and Sketchfab services).
Type bool
is_protected
Set dataset access to protected (Pointbox service).
Type bool
max_zoom_level
Maximum zoom level.
Type int
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min_zoom_level
Minimum zoom level.
Type int
name
Task name.
Type string
owner
Account owner (Cesium and Mapbox services).
Type string
password
Account password (4DMapper, Melown, Pointscene and Sketchfab services).
Type string
point_classes
List of point classes to be exported.
Type list of int
projection
Output projection.
Type CoordinateSystem
raster_transform
Raster band transformation.
Type RasterTransformType
resolution
Output resolution in meters.
Type float
save_camera_track
Enables/disables export of camera track.
Type bool
save_point_color
Enables/disables export of point colors.
Type bool
service
Service to upload on.
Type ServiceType
source_data
Asset type to upload.
Type DataSource
supports_gpu
GPU support flag.
Type bool
tags
Dataset tags.
Type string
target
Task target.
Type Tasks.TargetType
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tile_size
Tile size in pixels.
Type int
title
Dataset title.
Type string
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
token
Account token (Cesium, Mapbox, Picterra, Pointbox and Sketchfab services).
Type string
username
Account username (4DMapper, Melown and Pointscene services).
Type string
workitem_count
Work item count.
Type int
class ReduceOverlap
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
overlap
Target number of cameras observing each point of the surface.
Type int
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
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toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
use_selection
Focus on model selection.
Type bool
workitem_count
Work item count.
Type int
class RefineMesh
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
downscale
Refinement quality.
Type int
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
iterations
Number of refinement iterations.
Type int
name
Task name.
Type string
smoothness
Smoothing strength. Should be in range [0, 1].
Type float
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
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toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class RemoveLighting
Task class containing processing parameters.
ambient_occlusion_multiplier
Ambient occlusion multiplier. Should be in range [0.25, 4].
Type float
ambient_occlusion_path
Path to ambient occlusion texture atlas. Can be empty.
Type string
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
color_mode
Enable multi-color processing mode.
Type bool
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
internal_blur
Internal blur. Should be in range [0, 4].
Type float
mesh_noise_suppression
Mesh normals noise suppression strength. Should be in range [0, 4].
Type float
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
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toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class RenderDepthMaps
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
export_depth
Enable export of depth map.
Type bool
export_diffuse
Enable export of diffuse map.
Type bool
export_normals
Enable export of normal map.
Type bool
name
Task name.
Type string
path_depth
Path to depth map.
Type string
path_diffuse
Path to diffuse map.
Type string
path_normals
Path to normal map.
Type string
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supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class ResetMasks
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
cameras
List of cameras to process.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
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class RunScript
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
args
Script arguments.
Type string
code
Script code.
Type string
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
path
Script path.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class SaveProject
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.
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workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
archive
Override project format when using non-standard file extension.
Type bool
chunks
List of chunks to be saved.
Type list of int
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
name
Task name.
Type string
path
Path to project.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
version
Project version to save.
Type string
workitem_count
Work item count.
Type int
class SmoothModel
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
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apply_to_selection
Apply to selected faces.
Type bool
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
fix_borders
Fix borders.
Type bool
name
Task name.
Type string
preserve_edges
Preserve edges.
Type bool
strength
Smoothing strength.
Type float
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class TargetType
Task target type in [DocumentTarget, ChunkTarget, FrameTarget]
class TrackMarkers
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
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decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
first_frame
Starting frame index.
Type int
last_frame
Ending frame index.
Type int
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
class TransformRaster
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
asset
Asset key to transform.
Type int
data_source
Selects between DEM and orthomosaic.
Type DataSource
decode(dict)
Initialize task parameters with a dictionary.
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decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
height
Raster height.
Type int
name
Task name.
Type string
nodata_value
No-data value (DEM export only).
Type float
north_up
Use north-up orientation for export.
Type bool
operand_asset
Operand asset key.
Type int
operand_chunk
Operand chunk key.
Type int
operand_frame
Operand frame key.
Type int
projection
Output projection.
Type OrthoProjection
region
Region to be processed.
Type BBox
resolution
Output resolution in meters.
Type float
resolution_x
Pixel size in the X dimension in projected units.
Type float
resolution_y
Pixel size in the Y dimension in projected units.
Type float
subtract
Subtraction flag.
Type bool
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supports_gpu
GPU support flag.
Type bool
target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
width
Raster width.
Type int
workitem_count
Work item count.
Type int
world_transform
2×3 raster-to-world transformation matrix.
Type Matrix
class TriangulateTiePoints
Task class containing processing parameters.
apply(object[, workitem ][, progress])
Apply task to specified object.
Parameters

object (Chunk or Document) – Chunk or Document object to be processed.

workitem (int) – Workitem index.

progress (Callable[[float], None]) – Progress callback.
decode(dict)
Initialize task parameters with a dictionary.
decodeJSON(json)
Initialize task parameters from a JSON string.
encode()
Create a dictionary with task parameters.
encodeJSON()
Create a JSON string with task parameters.
max_error
Reprojection error threshold.
Type float
min_image
Minimum number of point projections.
Type int
name
Task name.
Type string
supports_gpu
GPU support flag.
Type bool
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target
Task target.
Type Tasks.TargetType
toNetworkTask([objects])
Convert task to NetworkTask to be applied to specified objects.
Parameters objects (Document, Chunk or list of Chunk) – Objects to be processed.
workitem_count
Work item count.
Type int
createTask(name)
Create task object by its name.
Parameters name (string) – Task name.
Returns Task object.
Return type object
class Metashape.Thumbnail
Thumbnail instance
copy()
Returns a copy of thumbnail.
Returns Copy of thumbnail.
Return type Thumbnail
image()
Returns image data.
Returns Image data.
Return type Image
load(path[, layer])
Loads thumbnail from file.
Parameters

path (string) – Path to the image file to be loaded.

layer (int) – Optional layer index in case of multipage files.
setImage(image)
Parameters image (Image) – Image object with thumbnail data.
class Metashape.Thumbnails
A set of thumbnails generated for a chunk frame.
items()
List of items.
keys()
List of item keys.
meta
Thumbnails meta data.
Type MetaData
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modified
Modified flag.
Type bool
values()
List of item values.
class Metashape.TiePoints
Tie point cloud instance
class Cameras
Collection of TiePoints.Projections objects indexed by corresponding cameras
class Filter
Tie point cloud filter
The following example selects all tie points from the active chunk that have reprojection error higher than
defined threshold:
chunk = Metashape.app.document.chunk # active chunk
threshold = 0.5
f = Metashape.TiePoints.Filter()
f.init(chunk, criterion = Metashape.TiePoints.Filter.ReprojectionError)
f.selectPoints(threshold)
class Criterion
Point filtering criterion in [ReprojectionError, ReconstructionUncertainty, ImageCount, ProjectionAccuracy]
init(points, criterion, progress)
Initialize tie points filter based on specified criterion.
Parameters

points (TiePoints or Chunk) – Tie points to filter.

criterion (TiePoints.Filter.Criterion) – Point filter criterion.

progress (Callable[[float], None]) – Progress callback.
max_value
Maximum value.
Type int or double
min_value
Minimum value.
Type int or double
removePoints(threshold)
Remove points based on specified threshold.
Parameters threshold (float) – Criterion threshold.
resetSelection()
Reset previously made selection.
selectPoints(threshold)
Select points based on specified threshold.
Parameters threshold (float) – Criterion threshold.
values
List of values.
Type list of int or list of double
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class Point
3D point in the tie point cloud
coord
Point coordinates.
Type Vector
cov
Point coordinates covariance matrix.
Type Matrix
selected
Point selection flag.
Type bool
track_id
Track index.
Type int
valid
Point valid flag.
Type bool
class Points
Collection of 3D points in the tie point cloud
copy()
Returns a copy of points buffer.
Returns Copy of points buffer.
Return type TiePoints.Points
resize(count)
Resize points list.
Parameters count (int) – new point count
class Projection
Projection of the 3D point on the photo
coord
Projection coordinates.
Type tuple of 2 float
size
Point size.
Type float
track_id
Track index.
Type int
class Projections
Collection of TiePoints.Projection for the camera
copy()
Returns a copy of projections buffer.
Returns Copy of projections buffer.
Return type TiePoints.Projections
resize(count)
Resize projections list.
Parameters count (int) – new projections count
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class Track
Track in the tie point cloud
color
Track color.
Type tuple of numbers
class Tracks
Collection of tracks in the tie point cloud
copy()
Returns a copy of tracks buffer.
Returns Copy of tracks buffer.
Return type TiePoints.Tracks
resize(count)
Resize track list.
Parameters count (int) – new track count
bands
List of color bands.
Type list of string
cleanup([progress])
Remove points with insufficient number of projections.
Parameters progress (Callable[[float], None]) – Progress callback.
copy(keypoints=True)
Returns a copy of the tie point cloud.
Parameters keypoints (bool) – copy key points data.
Returns Copy of the tie point cloud.
Return type TiePoints
cropSelectedPoints()
Crop selected points.
cropSelectedTracks()
Crop selected tie points.
data_type
Data type used to store color values.
Type DataType
export(path, format=’obj'[, projection ])
Export tie points.
Parameters

path (string) – Path to output file.

format (string) – Export format in [‘obj’, ‘ply’].

projection (Matrix or CoordinateSystem) – Sets output projection.
meta
Tie points meta data.
Type MetaData
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modified
Modified flag.
Type bool
pickPoint(origin, target, endpoints=1)
Returns ray intersection with the tie point cloud (point on the ray nearest to some point).
Parameters

origin (Vector) – Ray origin.

target (Vector) – Point on the ray.

endpoints (int) – Number of endpoints to check for (0 – line, 1 – ray, 2 – segment).
Returns Coordinates of the intersection point.
Return type Vector
points
List of points.
Type TiePoints.Points
projections
Point projections for each photo.
Type TiePoints.Projections
removeKeypoints()
Remove keypoints from tie point cloud.
removeSelectedPoints()
Remove selected points.
removeSelectedTracks()
Remove selected tie points.
renderDepth(transform, calibration, point_size=1, cull_points=False, add_alpha=True)
Render tie points depth image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

point_size (int) – Point size.

cull_points (bool) – Enable normal based culling.

add_alpha (bool) – Generate image with alpha channel.
Returns Rendered image.
Return type Image
renderImage(transform, calibration, point_size=1, cull_points=False, add_alpha=True,
raster_transform=RasterTransformNone)
Render tie points image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.
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point_size (int) – Point size.

cull_points (bool) – Enable normal based culling.

add_alpha (bool) – Generate image with alpha channel.

raster_transform (RasterTransformType) – Raster band transformation.
Returns Rendered image.
Return type Image
renderMask(transform, calibration, point_size=1, cull_points=False)
Render tie points mask image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

point_size (int) – Point size.

cull_points (bool) – Enable normal based culling.
Returns Rendered image.
Return type Image
renderNormalMap(transform, calibration, point_size=1, cull_points=False, add_alpha=True)
Render image with tie points normals for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

point_size (int) – Point size.

cull_points (bool) – Enable normal based culling.

add_alpha (bool) – Generate image with alpha channel.
Returns Rendered image.
Return type Image
renderPreview(width = 2048, height = 2048[, transform ], point_size=1[, progress])
Generate tie points preview image.
Parameters

width (int) – Preview image width.

height (int) – Preview image height.

transform (Matrix) – 4×4 viewpoint transformation matrix.

point_size (int) – Point size.

progress (Callable[[float], None]) – Progress callback.
Returns Preview image.
Return type Image
tracks
List of tracks.
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Type TiePoints.Tracks
class Metashape.TiledModel
Tiled model data.
class FaceCount
Tiled model face count in [LowFaceCount, MediumFaceCount, HighFaceCount]
bands
List of color bands.
Type list of string
clear()
Clears tiled model data.
copy()
Create a copy of the tiled model.
Returns Copy of the tiled model.
Return type TiledModel
crs
Reference coordinate system.
Type CoordinateSystem or None
data_type
Data type used to store color values.
Type DataType
key
Tiled model identifier.
Type int
label
Tiled model label.
Type string
meta
Tiled model meta data.
Type MetaData
modified
Modified flag.
Type bool
pickPoint(origin, target, endpoints=1)
Returns ray intersection with the tiled model.
Parameters

origin (Vector) – Ray origin.

target (Vector) – Point on the ray.

endpoints (int) – Number of endpoints to check for (0 – line, 1 – ray, 2 – segment).
Returns Coordinates of the intersection point.
Return type Vector
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renderDepth(transform, calibration, resolution=1, cull_faces=True, add_alpha=True)
Render tiled model depth image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

resolution (float) – Level of detail resolution in screen pixels.

cull_faces (bool) – Enable back-face culling.

add_alpha (bool) – Generate image with alpha channel.
Returns Rendered image.
Return type Image
renderImage(transform, calibration, resolution=1, cull_faces=True, add_alpha=True,
raster_transform=RasterTransformNone)
Render tiled model image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

resolution (float) – Level of detail resolution in screen pixels.

cull_faces (bool) – Enable back-face culling.

add_alpha (bool) – Generate image with alpha channel.

raster_transform (RasterTransformType) – Raster band transformation.
Returns Rendered image.
Return type Image
renderMask(transform, calibration, resolution=1, cull_faces=True)
Render tiled model mask image for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

resolution (float) – Level of detail resolution in screen pixels.

cull_faces (bool) – Enable back-face culling.
Returns Rendered image.
Return type Image
renderNormalMap(transform, calibration, resolution=1, cull_faces=True, add_alpha=True)
Render image with tiled model normals for specified viewpoint.
Parameters

transform (Matrix) – Camera location.

calibration (Calibration) – Camera calibration.

resolution (float) – Level of detail resolution in screen pixels.

cull_faces (bool) – Enable back-face culling.
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add_alpha (bool) – Generate image with alpha channel.
Returns Rendered image.
Return type Image
renderPreview(width = 2048, height = 2048[, transform ][, progress])
Generate tiled model preview image.
Parameters

width (int) – Preview image width.

height (int) – Preview image height.

transform (Matrix) – 4×4 viewpoint transformation matrix.

progress (Callable[[float], None]) – Progress callback.
Returns Preview image.
Return type Image
transform
4×4 tiled model transformation matrix.
Type Matrix
class Metashape.TiledModelFormat
Tiled model format in [TiledModelFormatNone, TiledModelFormatTLS, TiledModelFormatLOD, TiledModelFormatZIP, TiledModelFormatCesium, TiledModelFormatSLPK, TiledModelFormatOSGB, TiledModelFormatOSGT, TiledModelFormat3MX]
class Metashape.TrajectoryFormat
Trajectory format in [TrajectoryFormatNone, TrajectoryFormatCSV, TrajectoryFormatSBET, TrajectoryFormatSOL, TrajectoryFormatTRJ]
class Metashape.Utils
Utility functions.
createChessboardImage(calib, cell_size=150, max_tilt=30)
Synthesizes photo of a chessboard.
Parameters

calib (Calibration) – Camera calibration.

cell_size (float) – Chessboard cell size.

max_tilt (float) – Maximum camera tilt in degrees.
Returns Resulting image.
Return type Image
createDifferenceMask(image, background, tolerance=10, fit_colors=True)
Creates mask from a pair of images or an image and specified color.
Parameters

image (Image) – Image to be masked.

background (Image or color tuple) – Background image or color value.

tolerance (int) – Tolerance value.

fit_colors (bool) – Enables white balance correction.
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Returns Resulting mask.
Return type Image
createMarkers(chunk, projections)
Creates markers from a list of non coded projections.
Parameters

chunk (Chunk) – Chunk to create markers in.

projections (list of (Camera, Target) tuples) – List of marker projections.
detectTargets(image, type=TargetCircular12bit, tolerance=50, inverted=False, noparity=False[,
minimum_size ][, minimum_dist])
Detect targets on the image.
Parameters

image (Image) – Image to process.

type (TargetType) – Type of targets.

tolerance (int) – Detector tolerance (0 – 100).

inverted (bool) – Detect markers on black background.

noparity (bool) – Disable parity checking.

minimum_size (int) – Minimum target radius in pixels to be detected (CrossTarget type
only).

minimum_dist (int) – Minimum distance between targets in pixels (CrossTarget type
only).
Returns List of detected targets.
Return type list of Target
dmat2euler(R, dR, euler_angles=EulerAnglesYPR)
Calculate tangent euler rotation vector from tangent rotation matrix.
Parameters

R (Matrix) – Rotation matrix.

dR (Matrix) – Tangent rotation matrix.

euler_angles (EulerAngles) – Euler angles to use.
Returns Tangent rotation angles in degrees.
Return type Vector
estimateImageQuality(image[, mask ])
Estimate image sharpness.
Parameters

image (Image) – Image to be analyzed.

mask (Image) – Mask of the analyzed image region.
Returns Quality metric.
Return type float
euler2mat(rotation, euler_angles=EulerAnglesYPR)
Calculate camera to world rotation matrix from euler rotation angles.
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Parameters

rotation (Vector) – Rotation vector.

euler_angles (EulerAngles) – Euler angles to use.
Returns Rotation matrix.
Return type Matrix
mat2euler(R, euler_angles=EulerAnglesYPR)
Calculate euler rotation angles from camera to world rotation matrix.
Parameters

R (Matrix) – Rotation matrix.

euler_angles (EulerAngles) – Euler angles to use.
Returns Rotation angles in degrees.
Return type Vector
mat2opk(R)
Calculate omega, phi, kappa from camera to world rotation matrix.
Parameters R (Matrix) – Rotation matrix.
Returns Omega, phi, kappa angles in degrees.
Return type Vector
mat2ypr(R)
Calculate yaw, pitch, roll from camera to world rotation matrix.
Parameters R (Matrix) – Rotation matrix.
Returns Yaw, pitch roll angles in degrees.
Return type Vector
opk2mat(angles)
Calculate camera to world rotation matrix from omega, phi, kappa angles.
Parameters angles (Vector) – Omega, phi, kappa angles in degrees.
Returns Rotation matrix.
Return type Matrix
ypr2mat(angles)
Calculate camera to world rotation matrix from yaw, pitch, roll angles.
Parameters angles (Vector) – Yaw, pitch, roll angles in degrees.
Returns Rotation matrix.
Return type Matrix
class Metashape.Vector
n-component vector
import Metashape
vect = Metashape.Vector( (1, 2, 3) )
vect2 = vect.copy()
vect2.size = 4
vect2.w = 5
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vect2 *= -1.5
vect.size = 4
vect.normalize()
Metashape.app.messageBox(« Scalar product is » + str(vect2 * vect))
copy()
Return a copy of the vector.
Returns A copy of the vector.
Return type Vector
cross(a, b)
Cross product of 2 vectors.
Parameters

a (Vector) – First vector.

b (Vector) – Second vector.
Returns Cross product.
Return type Vector
norm()
Return norm of the vector.
norm2()
Return squared norm of the vector.
normalize()
Normalize vector to the unit length.
normalized()
Return a new, normalized vector.
Returns a normalized copy of the vector
Return type Vector
size
Vector dimensions.
Type int
w
Vector W component.
Type float
x
Vector X component.
Type float
y
Vector Y component.
Type float
z
Vector Z component.
Type float
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zero()
Set all elements to zero.
class Metashape.Version
Version object contains application version numbers.
build
Build number.
Type int
copy()
Return a copy of the object.
Returns A copy of the object.
Return type Version
major
Major version number.
Type int
micro
Micro version number.
Type int
minor
Minor version number.
Type int
class Metashape.Viewpoint(app)
Represents viewpoint in the model view
center
Camera center.
Type Vector
coo
Center of orbit.
Type Vector
copy()
Return a copy of the object.
Returns A copy of the object.
Return type Viewpoint
fov
Camera vertical field of view in degrees.
Type float
height
OpenGL window height.
Type int
mag
Camera magnification defined by distance to the center of rotation.
Type float
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rot
Camera rotation matrix.
Type Matrix
width
OpenGL window width.
Type int
class Metashape.Vignetting
Vignetting polynomial
copy()
Return a copy of the object.
Returns A copy of the object.
Return type Vignetting
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CHAPTER
THREE
PYTHON API CHANGE LOG
3.1 Metashape version 2.0.2

Added PointCloudGroup class

Added TiledModelFormat3MX to TiledModelFormat enum

Added Chunk.addPointCloudGroup() and Chunk.findPointCloudGroup() methods

Added Chunk.point_cloud_groups attribute

Added PointCloud.group and PointCloud.is_laser_scan attributes
3.2 Metashape version 2.0.1

Added License.install() method

Added DetectFiducials.v_shape_detector attribute

Added model and save_metadata_xml attributes to ExportModel task

Added v_shape_detector argument to Chunk.detectFiducials() method

Added model and save_metadata_xml arguments to Chunk.exportModel() method

Replaced license_key argument with activation_params in License.activateOffline() method
3.3 Metashape version 2.0.0

Added TrajectoryFormat enum

Added DisplacementMap to Model.TextureType enum

Added ImportTrajectory class

Added ImportDepthImages class

Added Chunk.importTrajectory() method

Added Chunk.importDepthImages() method

Added AlignCameras.point_clouds attribute

Added ImportDepthImages.color_filenames attribute
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Added precision, is_laser_scan, replace_asset, import_images, scanner_at_origin, ignore_scanner_origin, ignore_trajectory, trajectory and frame_paths attributes to ImportPointCloud class

Added keep_existing, return_number and point_cloud attributes to ClassifyGroundPoints class

Added point_cloud attribute to ClassifyPoints, ColorizePointCloud, CalculatePointNormals, CompactPointCloud and ExportPointCloud classes

Added max_quantization_error attribute to DetectPowerlines class

Added use_rtc_center attribute to ExportTiledModel class

Added merge_assets, copy_laser_scans, copy_depth_maps, copy_point_clouds, copy_models,
copy_tiled_models, copy_elevations and copy_orthomosaics attributes to MergeChunks class

Added point_clouds argument to Chunk.alignCameras() method

Added color_filenames argument to Chunk.importDepthImages() method

Added precision, is_laser_scan, replace_asset, import_images, scanner_at_origin, ignore_scanner_origin, ignore_trajectory, trajectory and frame_paths arguments to Chunk.importPointCloud() method

Added point_cloud argument to Chunk.calculatePointNormals(), Chunk.colorizePointCloud() and
Chunk.exportPointCloud() methods

Added max_quantization_error argument to Chunk.detectPowerlines() method

Added keep_existing and return_number arguments to PointCloud.classifyGroundPoints() method

Added use_rtc_center argument to Chunk.exportTiledModel() method

Added merge_assets, copy_laser_scans, copy_depth_maps, copy_point_clouds, copy_models,
copy_tiled_models, copy_elevations and copy_orthomosaics arguments to Document.mergeChunks() method

Added drone_name, payload_name and payload_position arguments to CameraTrack.save() method

Change default source_data argument value for Chunk.buildModel() and Chunk.buildTiledModel() methods to
DepthMapsData

Renamed PointsFormat enum to PointCloudFormat

Renamed ModelView.PointCloudViewMode enum to ModelView.TiePointsViewMode

Renamed ModelView.DenseCloudViewMode enum to ModelView.PointCloudViewMode and added PointCloudViewSolid, PointCloudViewIntensity, PointCloudViewElevation, PointCloudViewReturnNumber, PointCloudViewScanAngle, PointCloudViewSourceId enumeration values

Renamed DataSource.PointCloudData enum value to DataSource.TiePointsData

Renamed DataSource.DenseCloudData enum value to DataSource.PointCloudData

Renamed PointCloud class to TiePoints

Renamed DenseCloud class to PointCloud

Renamed AnalyzePhotos class to AnalyzeImages

Renamed BuildDenseCloud class to BuildPointCloud

Renamed CalibrateLens class to CalibrateCamera

Renamed ColorizeDenseCloud class to ColorizePointCloud

Renamed CompactDenseCloud class to CompactPointCloud

Renamed ExportDepth class to RenderDepthMaps

Renamed ExportPoints class to ExportPointCloud
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Renamed FilterDenseCloud class to FilterPointCloud

Renamed ImportPoints class to ImportPointCloud

Renamed TriangulatePoints class to TriangulateTiePoints

Renamed Chunk.addDenseCloud() method to addPointCloud()

Renamed Chunk.analyzePhotos() method to analyzeImages()

Renamed Chunk.buildDenseCloud() method to buildPointCloud()

Renamed Chunk.colorizeDenseCloud() method to colorizePointCloud()

Renamed Chunk.exportPoints() method to exportPointCloud()

Renamed Chunk.filterDenseCloud() method to filterPointCloud()

Renamed Chunk.findDenseCloud() method to findPointCloud()

Renamed Chunk.importPoints() method to importPointCloud()

Renamed Chunk.thinPointCloud() method to thinTiePoints()

Renamed Chunk.triangulatePoints() method to triangulateTiePoints()

Renamed Chunk.point_cloud attribute to tie_points

Renamed Chunk.dense_cloud attribute to point_cloud

Renamed Chunk.dense_clouds attribute to point_clouds

Renamed ModelView.point_cloud_view_mode attribute to tie_points_view_mode

Renamed ModelView.dense_cloud_view_mode attribute to point_cloud_view_mode

Renamed AddFrames.copy_dense_cloud attribute to copy_point_cloud

Renamed DuplicateChunk.copy_dense_clouds attribute to copy_point_clouds

Renamed FilterPointCloud.asset attribute to point_cloud

Renamed PublishData.save_point_colors attribute to save_point_color

Renamed copy_dense_cloud argument in Chunk.addFrames() method to copy_point_cloud

Renamed save_point_colors argument in Chunk.publishData() method to save_point_color

Renamed asset argument in Chunk.filterPointCloud() method to point_cloud

Renamed source argument in PointCloud.classifyGroundPoints() method to source_class

Revised parameter names for point attributes in ExportPointCloud class and Chunk.exportPointCloud() methods

Removed ImportLaserScans class

Removed Chunk.importLaserScans() method

Removed Chunk.samplePoints() method

Removed use_trajectory, traj_path, traj_columns, traj_delimiter and traj_skip_rows attributes from ImportPointCloud class

Removed use_trajectory, traj_path, traj_columns, traj_delimiter and traj_skip_rows arguments from
Chunk.importPointCloud() method

Removed merge_depth_maps, merge_dense_clouds, merge_models, merge_elevations and merge_orthomosaics
attributes from MergeChunks class
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Removed merge_depth_maps, merge_dense_clouds, merge_models, merge_elevations and merge_orthomosaics
arguments from Document.mergeChunks() method
3.4 Metashape version 1.8.5

Added DetectPowerlines class

Added Chunk.detectPowerlines() method

Added CameraTrack.interpolate() method

Added generic_detector, right_angle_detector, fiducials_position_corners and fiducials_position_sides attributes
to DetectFiducials class

Added archive attribute to LoadProject and SaveProject classes

Added generic_detector, right_angle_detector, fiducials_position_corners and fiducials_position_sides arguments to Chunk.detectFiducials() method

Added archive argument to Document.open() and Document.save() methods
3.5 Metashape version 1.8.4

Added Shutter.Model enum

Added ImageFormatBZ2, ImageFormatASCII and ImageFormatKTX to ImageFormat enum

Added Shape.areaFitted() method

Added ExportPoints.folder_depth and ExportTiledModel.folder_depth attributes

Added ImportLaserScans.multiplane attribute

Added folder_depth argument to Chunk.exportPoints() and Chunk.exportTiledModel() methods

Added multiplane argument to Chunk.importLaserScans() method

Changed type of Sensor.rolling_shutter attribute to Shutter.Model

Fixed Antenna.location and Antenna.rotation attributes to return non-None values
3.6 Metashape version 1.8.3

Added CloudClient class

Added PublishData class

Added CalibrationFormatSTMap to CalibrationFormat enum

Reorganized arguments of Chunk.publishData() method
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3.7 Metashape version 1.8.2
No Python API changes
3.8 Metashape version 1.8.1

Added CamerasFormatMA to CamerasFormat enum

Added global_profile attribute to ExportRaster class

Added traj_columns, traj_delimiter, traj_path, traj_skip_rows and use_trajectory attributes to ImportPoints class

Added global_profile argument to Chunk.exportRaster() method

Added use_trajectory, traj_path, traj_columns, traj_delimiter and traj_skip_rows arguments to
Chunk.importPoints() method

Removed fix_pixel_aspect, fix_principal_point, and remove_distortions attributes from ConvertImages class
3.9 Metashape version 1.8.0

Added BuildPanorama and CalculatePointNormals classes

Added ImageFormatJXL to ImageFormat enum

Added Cylindrical to Sensor.Type enum

Added Chunk.buildPanorama(), Chunk.calculatePointNormals() and Chunk.filterDenseCloud() methods

Added findCamera(), findCameraGroup(), findCameraTrack(), findDenseCloud(), findDepthMaps(), findElevation(), findMarker(), findMarkerGroup(), findModel(), findOrthomosaic(), findScalebar(), findScalebarGroup(),
findSensor() and findTiledModel() methods to Chunk class

Added NetworkClient.serverStatus() method

Added NetworkClient.setBatchPaused() and NetworkClient.setNodePaused() methods

Added Settings.project_absolute_paths and Settings.project_compression attributes

Added CloseHoles.apply_to_selection attribute

Added ConvertImages.merge_planes attribute

Added ExportPoints.screen_space_error and ExportTiledModel.screen_space_error attributes

Added ExportReport.font_size attribute

Added ImportPoints.point_neighbors attribute

Added home_point, interesting_zone, powerlines, restricted_zone and safety_zone attributes to PlanMission
class

Added apply_to_selection argument to Model.closeHoles() method

Added file_format and max_waypoints arguments to CameraTrack.save() method

Added screen_space_error argument to Chunk.exportPoints() and Chunk.exportTiledModel() methods

Added font_size argument to Chunk.exportReport() method

Added point_neighbors argument to Chunk.importPoints() method
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Removed Shape.Type enum

Removed ExportPanorama class

Removed has_z, type, vertex_ids and vertices attributes from Shape class

Removed pauseBatch(), resumeBatch(), pauseNode() and resumeNode() methods from NetworkClient class

Removed PlanMission.max_waypoints attribute

Removed SaveProject.absolute_paths and SaveProject.compression attributes

Removed compression and absolute_paths arguments from Document.save() method

Changed default value of BuildTiledModel.face_count attribute to 20000

Changed default value of face_count argument in Chunk.buildTiledModel() method to 20000
3.10 Metashape version 1.7.6

Added Cylindrical to Sensor.Type enum
3.11 Metashape version 1.7.5

Added ClassifyGroundPoints.erosion_radius attribute

Added erosion_radius argument to DenseCloud.classifyGroundPoints() method
3.12 Metashape version 1.7.4

Added ServiceCesium to ServiceType enum

Added ImportLaserScans class

Added Chunk.colorizeDenseCloud() and Chunk.colorizeModel() methods

Added Chunk.exportTexture() and Chunk.importLaserScans() methods

Added breakpoints and rates attributed to GeneratePrescriptionMap class

Added SmoothModel.preserve_edges attribute

Added breakpoints and rates arguments to Chunk.generatePrescriptionMap() method

Added preserve_edges argument to Chunk.smoothModel method

Renamed ClusteringMethod enum to ClassificationMethod

Renamed cluster_count, clustering_method and boundary attributes in GeneratePrescriptionMap class

Renamed cluster_count, clustering_method and boundary arguments in Chunk.generatePrescriptionMap()
method

Removed ServiceSputnik from ServiceType enum

Removed min_value, max_value and grid_azimuth attributes from GeneratePrescriptionMap class

Removed min_value, max_value and grid_azimuth arguments from Chunk.generatePrescriptionMap() method
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3.13 Metashape version 1.7.3

Added ModelFormatOSGT and ModelFormatLandXML to ModelFormat enum

Added TiledModelFormatOSGT to TiledModelFormat enum

Added CoordinateSystem.datumTransform() method

Added DenseCloud.selectPointsByShapes() method

Added Sensor.makeMaster() method

Added Utils.dmat2euler() method

Added Settings.lanuage attribute

Added ShapeGroup.meta attribute

Added Shapes.group attribute

Added ExportPoints.compression attribute

Added ExportTiledModel.model_compression attribute

Added ImportModel.decode_udim attribute

Added MatchPhotos.keypoint_limit_per_mpx attribute

Added compression argument to Chunk.exportPoints() method

Added model_compression argument to Chunk.exportTiledModel() method

Added decode_udim argument to Chunk.importModel() method

Added keypoint_limit_per_mpx argument to Chunk.matchPhotos() method

Added uniform_sampling argument to Chunk.samplePoints() method
3.14 Metashape version 1.7.2

Added ClusteringMethod enum

Added PointsFormatSLPK to PointsFormat enum

Added DuplicateAsset and GeneratePrescriptionMap classes

Added Chunk.generatePrescriptionMap() method

Added merge, operand_chunk, operand_frame and operand_asset attributes to BuildTiledModel class

Added ExportReport.include_system_info attribute

Added GenerateMasks.depth_threshold attribute

Added merge, operand_chunk, operand_frame and operand_asset arguments to Chunk.buildTiledModel()
method

Added include_system_info argument to Chunk.exportReport() method

Added depth_threshold argument to Chunk.generateMasks() method
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3.15 Metashape version 1.7.1

Removed LegacyMapping from MappingMode enum

Removed ReduceOverlap.sensor attribute

Removed sensor argument from Chunk.reduceOverlap() method
3.16 Metashape version 1.7.0

Added Geometry and AttachedGeometry classes

Added FrameStep enum

Added ServiceType enum

Added Chunk.importVideo(), Chunk.publishData() and Chunk.samplePoints() methods

Added Shape.geometry and Shape.is_attached attributes

Added alpha component to ShapeGroup.color attribute value

Added ImportRaster.nodata_value and ImportRaster.has_nodata_value attributes

Added MatchPhotos.filter_stationary_points attribute

Added BuildOrthomosaic.ghosting_filter attribute

Added attach_viewpoints, group_attached_viewpoints and horizontal_zigzags attributes to PlanMission class

Added ReduceOverlap.sensor attribute

Added dir argument to Application.getExistingDirectory(), getOpenFileName(), getOpenFileNames() and getSaveFileName() methods

Added nodata_value and has_nodata_value arguments to Chunk.importRaster() method

Added filter_stationary_points argument to Chunk.matchPhotos() method

Added ghosting_filter argument to Chunk.buildOrthomosaic() method

Added sensor argument to Chunk.reduceOverlap() method

Renamed ImportMasks class to GenerateMasks

Renamed MaskSource enum to MaskingMode

Renamed Chunk.importMasks() method to Chunk.generateMasks()

Removed ReduceOverlap.max_cameras attribute

Removed max_cameras argument from Chunk.reduceOverlap() method
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3.17 Metashape version 1.6.6

Added Tasks.TransformRaster class

Added ExportReference.precision attribute

Added toNetworkTask() method to task classes

Added Chunk.transformRaster() method

Added precision argument to Chunk.exportReference() method
3.18 Metashape version 1.6.5

Added Sensor.meta attribute
3.19 Metashape version 1.6.4

Added Model.Vertex.confidence attribute

Added ConvertImages.use_initial_calibration attribute

Added image_orientation, save_invalid_matches and use_initial_calibration attributes to ExportCameras class

Added ExportModel.save_confidence attribute

Added crs and image_orientation attributes to ImportCameras class

Added CalibrationFormatPhotomod to CalibrationFormat enum

Added save_invalid_matches, use_initial_calibration and image_orientation arguments to
Chunk.exportCameras() method

Added save_confidence argument to Chunk.exportModel() method

Added crs and image_orientation arguments to Chunk.importCameras() method

Removed BuildUV.adaptive_resolution attribute

Removed adaptive_resolution argument from Chunk.buildUV() method
3.20 Metashape version 1.6.3

Added renderPreview() methods to DenseCloud, Model, Orthomosaic, PointCloud and TiledModel classes

Added BuildUV.texture_size attribute

Added DecimateModel.apply_to_selection attribute

Added DetectFiducials.cameras, DetectFiducials.frames and DetectFiducials.generate_masks attributes

Added ExportModel.embed_texture attribute

Added clip_to_boundary attribute to ExportPoints, ExportModel, ExportTiledModel and ExportRaster classes

Added RasterFormatGeoPackage to RasterFormat enum

Added ShapesFormatGeoPackage to ShapesFormat enum
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Added source argument to Chunk.addSensor() method

Added texture_size argument to Chunk.buildUV() method

Added apply_to_selection argument to Chunk.decimateModel() method

Added generate_masks, cameras and frames arguments to Chunk.detectFiducials() method

Added embed_texture argument to Chunk.exportModel() method

Added width, height, point_size and progress arguments to Chunk.renderPreview() method

Added clip_to_boundary argument to Chunk.exportPoints(), Chunk.exportModel(), Chunk.exportTiledModel()
and Chunk.exportRaster() methods

Added meta argument to NetworkClient.createBatch() method

Removed CalibrateLens.fit_p3 and CalibrateLens.fit_p4 attributes
3.21 Metashape version 1.6.2

Added Application.ModelView and Application.OrthoView classes

Added Application.removeMenuItem() method

Added Model.transform() method

Added PointCloud.cleanup() method

Added Application.model_view and Application.ortho_view attributes

Added BuildTexture.transfer_texture attribute

Added PlanMission.min_pitch and PlanMission.max_pitch attributes

Added columns, crs, delimiter, group_delimiters and skip_rows attributes to ImportShapes class

Added CamerasFormatNVM to CamerasFormat enum

Added PointsFormatPTX to PointsFormat enum

Added ShapesFormatCSV to ShapesFormat enum

Added transfer_texture argument to Chunk.buildTexture() method

Added columns, crs, delimiter, group_delimiters and skip_rows arguments to Chunk.importShapes() method

Moved ModelViewMode enum to ModelView class

Renamed Application.console attribute to console_pane

Renamed Application.captureModelView() method to ModelView.captureView()

Renamed Application.captureOrthoView() method to OrthoView.captureView()

Renamed Application.viewpoint attribute to ModelView.viewpoint

Removed ReduceOverlap.capture_distance attribute

Removed capture_distance argument from Chunk.reduceOverlap() method

Changed default values of AlignCameras.reset_alignment and MatchPhotos.reset_matches attributes to False

Changed default value of reset_alignment argument in Chunk.alignCameras() method to False

Changed default value of reset_matches argument in Chunk.matchPhotos() method to False
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3.22 Metashape version 1.6.1

Added Application.releaseFreeMemory() method

Added CoordinateSystem.towgs84 attribute

Added Marker.enabled attribute

Added BuildModel.subdivide_task attribute

Added subdivide_task argument to Chunk.buildModel() method

Changed default value of keep_depth argument in Chunk.buildModel() and Chunk.buildTiledModel() to True
3.23 Metashape version 1.6.0

Added BBox, ImageCompression, RPCModel and Model.Texture classes

Added Tasks.ImportTiledModel and Task.ColorizeModel classes

Added CalibrationFormat and ReferencePreselectionMode enums

Added Model.addTexture() and Model.remove() methods

Added Model.getActiveTexture() and Model.setActiveTexture() methods

Added NetworkClient.setMasterServer() method

Added setClassesFilter(), setConfidenceFilter(), setSelectionFilter() and resetFilters() methods to DenseCloud
class

Added renderDepth(), renderImage(), renderMask() and renderNormalMap() methods to PointCloud, DenseCloud and TiledModel classes

Added Chunk.renderPreview() method

Added Utils.euler2mat() and Utils.mat2euler() methods

Added Calibration.rpc attribute

Added Marker.position_covariance attribute

Added Model.textures attribute

Added TiledModel.crs and TiledModel.transform attributes

Added EulerAnglesPOK and EulerAnglesANK values to EulerAngles enum

Added PointsFormatPCD to PointsFormat enum

Added ShapesFormatGeoJSON to ShapesFormat enum

Added RPC to Sensor.Type enum

Added image_compression attribute to ExportOrthophotos, ExportRaster, ExportTiledModel and UndistortPhotos classes

Added AddPhotos.load_rpc_txt attribute

Added AlignCameras.min_image attribute

Added BuildDenseCloud.point_confidence attribute

Added BuildModel.vertex_confidence, BuildModel.max_workgroup_size and BuildModel.workitem_size_cameras attributes
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Added BuildTexture.source_model and BuildTexture.texture_type attributes

Added BuildUV.adaptive_resolution attribute

Added DecimateModel.asset attribute

Added ExportPanorama.image_compression attribute

Added ExportPoints.save_classes and ExportPoints.save_confidence attributes

Added ExportTexture.texture_type attribute

Added ExportTiledModel.crs attribute

Added ImportCameras.image_list and ImportCameras.load_image_list attributes

Added ImportPoints.calculate_normals attribute

Added MatchPhotos.guided_matching and MatchPhotos.reference_preselection_mode attributes

Added MergeChunks.merge_depth_maps, MergeChunks.merge_elevations and
MergeChunks.merge_orthomosaics attributes

Added OptimizeCameras.fit_corrections attribute

Added TriangulatePoints.max_error and TriangulatePoints.min_image attributes

Added endpoints argument to PointCloud.pickPoint(), DenseCloud.pickPoint(), Model.pickPoint() and TiledModel.pickPoint() methods

Added compression argument to Image.save() method

Added cull_faces and add_alpha arguments to Model.renderDepth() method

Added cull_faces, add_alpha and raster_transform arguments to Model.renderImage() method

Added cull_faces argument to Model.renderMask() method

Added cull_faces and add_alpha arguments to Model.renderNormalMap() method

Moved TiffCompression enum to ImageCompression class

Renamed Tasks.UndistortPhotos class to Tasks.ConvertImages

Renamed Chunk.estimateImageQuality() method to Chunk.analyzePhotos()

Renamed Chunk.buildPoints() method to Chunk.triangulatePoints()

Renamed Chunk.loadReference() method to Chunk.importReference()

Renamed Chunk.saveReference() method to Chunk.exportReference()

Renamed Chunk.refineModel() method to Chunk.refineMesh()

Renamed network_distribute tasks attribute to subdivide_task

Renamed AlignChunks.align_method attribute to method

Renamed AlignChunks.match_downscale attribute to downscale

Renamed AlignChunks.match_filter_mask attribute to filter_mask

Renamed AlignChunks.match_mask_tiepoints attribute to mask_tiepoints

Renamed AlignChunks.match_point_limit attribute to keypoint_limit

Renamed AlignChunks.match_select_pairs attribute to generic_preselection

Renamed BuildDenseCloud.store_depth attribute to keep_depth

Renamed BuildModel.store_depth attribute to keep_depth
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Renamed BuildOrthomosaic.ortho_surface attribute to surface_data

Renamed BuildTiledModel.store_depth attribute to keep_depth

Renamed BuildUV.texture_count attribute to page_count

Renamed CalibrateColors.data_source attribute to source_data

Renamed CalibrateColors.calibrate_color_balance attribute to white_balance

Renamed ClassifyGroundPoints.cls_from attribute to source_class

Renamed ClassifyPoints.cls_from attribute to source_class

Renamed ClassifyPoints.cls_to attribute to target_classes

Renamed DecimateModel.target_face_count attribute to face_count

Renamed DuplicateChunk.copy_dense_cloud attribute to copy_dense_clouds

Renamed ClassifyPoints.copy_elevation attribute to copy_elevations

Renamed ClassifyPoints.copy_model attribute to copy_models

Renamed ClassifyPoints.copy_orthomosaic attribute to copy_orthomosaics

Renamed ClassifyPoints.copy_tiled_model attribute to copy_tiled_models

Renamed ExportCameras.bingo_export_geoin attribute to bingo_save_geoin

Renamed ExportCameras.bingo_export_gps attribute to bingo_save_gps

Renamed ExportCameras.bingo_export_image attribute to bingo_save_image

Renamed ExportCameras.bingo_export_itera attribute to bingo_save_itera

Renamed ExportCameras.bundler_export_list attribute to bundler_save_list

Renamed ExportCameras.chan_order_rotate attribute to chan_rotation_order

Renamed ExportCameras.coordinates attribute to crs

Renamed ExportCameras.export_markers attribute to save_markers

Renamed ExportCameras.export_points attribute to save_points

Renamed ExportMarkers.coordinates attribute to crs

Renamed ExportModel.coordinates attribute to crs

Renamed ExportModel.export_alpha attribute to save_alpha

Renamed ExportModel.export_cameras attribute to save_cameras

Renamed ExportModel.export_colors attribute to save_colors

Renamed ExportModel.export_comment attribute to save_comment

Renamed ExportModel.export_markers attribute to save_markers

Renamed ExportModel.export_normals attribute to save_normals

Renamed ExportModel.export_texture attribute to save_texture

Renamed ExportModel.export_udim attribute to save_udim

Renamed ExportModel.export_uv attribute to save_uv

Renamed ExportOrthophotos.write_alpha attribute to save_alpha

Renamed ExportOrthophotos.write_kml attribute to save_kml
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Renamed ExportOrthophotos.write_world attribute to save_world

Renamed ExportPoints.coordinates attribute to crs

Renamed ExportPoints.data_source attribute to source_data

Renamed ExportPoints.export_colors attribute to save_colors

Renamed ExportPoints.export_comment attribute to save_comment

Renamed ExportPoints.export_images attribute to save_images

Renamed ExportPoints.export_normals attribute to save_normals

Renamed ExportPoints.tile_height attribute to block_height

Renamed ExportPoints.tile_width attribute to block_width

Renamed ExportPoints.write_tiles attribute to split_in_blocks

Renamed ExportRaster.data_source attribute to source_data

Renamed ExportRaster.kmz_section_enable attribute to network_links

Renamed ExportRaster.tile_width attribute to block_width

Renamed ExportRaster.tile_height attribute to block_height

Renamed ExportRaster.write_alpha attribute to save_alpha

Renamed ExportRaster.write_kml attribute to save_kml

Renamed ExportRaster.write_scheme attribute to save_scheme

Renamed ExportRaster.write_tiles attribute to split_in_blocks

Renamed ExportRaster.write_world attribute to save_world

Renamed ExportRaster.xyz_level_min attribute to min_zoom_level

Renamed ExportRaster.xyz_level_max attribute to max_zoom_level

Renamed ExportShapes.coordinates attribute to crs

Renamed ExportShapes.export_attributes attribute to save_attributes

Renamed ExportShapes.export_labels attribute to save_labels

Renamed ExportShapes.export_points attribute to save_points

Renamed ExportShapes.export_polygons attribute to save_polygons

Renamed ExportShapes.export_polylines attribute to save_polylines

Renamed ExportTexture.write_alpha attribute to save_alpha

Renamed ExportTiledModel.mesh_format attribute to model_format

Renamed ImportMasks.method attribute to source

Renamed ImportModel.coordinates attribute to crs

Renamed ImportPoints.coordinates attribute to crs

Renamed ImportReference.coordinates attribute to crs

Renamed MatchPhotos.preselection_generic attribute to generic_preselection

Renamed MatchPhotos.preselection_reference attribute to reference_preselection

Renamed MatchPhotos.store_keypoints attribute to keep_keypoints
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Renamed RefineMesh.niterations attribute to iterations

Renamed SmoothModel.apply_to_selected attribute to apply_to_selection

Renamed TrackMarkers.frame_start attribute to first_frame

Renamed TrackMarkers.frame_end attribute to last_frame

Renamed processing methods arguments to match task parameters names (e.g. dx/dy -> resolution_x/resolution_y, write_xxx -> save_xxx, export_xxx -> save_xxx, import_xxx -> load_xxx, preselection_generic -> generic_preselection, preselection_reference -> reference_preselection, source_data ->
data_source, etc.)

Replaced Chunk.importDem() method with Chunk.importRaster() method

Replaced Chunk.exportDem() and Chunk.exportOrthomosaic() methods with Chunk.exportRaster() method

Removed Accuracy and Quality enums

Removed Model.texture() and Model.setTexture() methods

Removed ExportPoints.precision attribute

Removed OptimizeCameras.fit_p3 and OptimizeCameras.fit_p4 attributes

Removed PlanMission.max_cameras and PlanMission.use_cameras attributes

Removed tiff_big, tiff_tiled and tiff_overviews attributes from ExportOrthophotos and ExportRaster classes

Removed tiff_compression attribute from ExportOrthophotos, ExportRaster and UndistortPhotos classes

Removed jpeg_quality attribute from ExportOrthophotos, ExportRaster, ExportTiledModel and UndistortPhotos
classes
3.24 Metashape version 1.5.5
No Python API changes
3.25 Metashape version 1.5.4

Added Tasks.FilterDenseCloud class

Added TiledModel.FaceCount enum

Added copy() method to Antenna, Calibration, ChunkTransform, CirTransform, CoordinateSystem, Document, MetaData, OrthoProjection, RasterTransform, Region, Shutter, Target, Version, Viewpoint and Vignetting
classes

Added CameraTrack.save() and CameraTrack.load() methods

Added Chunk.reduceOverlap() method

Added location_enabled and rotation_enabled attributes to Sensor.Reference class

Added CameraTrack.chunk and CameraTrack.meta attributes

Added BuildTiledModel.ghosting_filter and BuildTiledModel.transfer_texture attributes

Added ExportPoints.network_distribute and ExportPoints.region attributes

Added ExportTiledModel.jpeg_quality and ExportTiledModel.texture_format attributes

Added prevent_intersections argument to Chunk.buildContours() method
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Added transfer_texture argument to Chunk.buildTiledModel() method

Added region argument to Chunk.exportPoints() method

Added texture_format and jpeg_quality arguments to Chunk.exportTiledModel() method

Added progress argument to Chunk.importMarkers() method

Added ImageFormatWebP to ImageFormat enum
3.26 Metashape version 1.5.3

Added DepthMap.getCalibration() and DepthMap.setCalibration() methods

Added NetworkClient.dumpBatches(), NetworkClient.loadBatches() and NetworkClient.setBatchNodeLimit()
methods

Added location_enabled and rotation_enabled attributes to Camera.Reference class

Added keep_depth argument to Chunk.buildTiledModel() method

Added uv argument to Chunk.exportModel() method

Added level argument to DepthMap.image() and DepthMap.setImage() methods

Changed default value of keep_depth argument in Chunk.buildDenseCloud() and Chunk.buildModel() methods
to True

Changed default value of max_neighbors argument in Chunk.buildDenseCloud() method to 100
3.27 Metashape version 1.5.2

Added CameraTrack class

Added Tasks.PlanMission and Tasks.ReduceOverlap classes

Added Camera.Type enum

Added Chunk.addCameraTrack() method

Added Application.title attribute

Added Camera.type attribute

Added Chunk.camera_track and Chunk.camera_tracks attributes

Added BuildModel.trimming_radius attribute

Added DetectMarkers.filter_mask attribute

Added ImportReference.shutter_lag attribute

Added Bundler and BINGO specific attributes to ExportCameras class

Added supports_gpu attribute to task classes

Added x, y, w, h arguments to Image.open() method

Added filter_mask argument to Chunk.detectMarkers() method

Added image_list argument to Chunk.importCameras() method

Added shutter_lag argument to Chunk.loadReference() method
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Added ImageFormatBIL, ImageFormatXYZ, ImageFormatDDS to ImageFormat enum

Removed Tasks.PlanMotion class

Removed Animation class

Removed Chunk.animation attribute

Removed smoothness attribute from Tasks.BuildModel and Tasks.BuildTiledModel classes

Removed quality and reuse_depth arguments from Chunk.buildModel() method

Removed downscale, filter_mode, max_neighbors, max_workgroup_size, network_distribute, reuse_depth,
workitem_size_cameras from Tasks.BuildModel class
3.28 Metashape version 1.5.1

Added License class

Added Tasks.MergeAssets class

Added Metashape.license attribute

Renamed Tasks.OptimizeCoverage class to Tasks.PlanMotion
3.29 Metashape version 1.5.0

Added Sensor.Reference class

Added Tasks.ClassifyPoints and Tasks.OptimizeCoverage classes

Added DataType enum

Added Model.TextureType enum

Added Tasks.TargetType enum

Added Animation.Track.resize() method

Added Chunk.findFrame() method

Added DenseCloud.classifyPoints() method

Added Document.findChunk() method

Added Model.Faces.resize(), Model.Vertices.resize() and Model.TexVertices.resize() methods

Added Tasks.createTask() method

Added decode(), decodeJSON(), encodeJSON() methods to task classes

Added Antenna.location_covariance and Antenna.rotation_covariance attributes

Added Camera.calibration, Camera.location_covariance and Camera.rotation_covariance attributes

Added Chunk.image_contrast attribute

Added DenseCloud.bands and DenseCloud.data_type attributes

Added Model.bands and Model.data_type attributes

Added Elevation.palette attribute

Added Model.Face.tex_index attribute
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Added Orthomosaic.bands and Orthomosaic.data_type attributes

Added PointCloud.Point.cov attribute

Added PointCloud.bands and PointCloud.data_type attributes

Added Sensor.data_type, Sensor.film_camera, Sensor.location_covariance, Sensor.reference and Sensor.rotation_covariance attributes

Added Sensor.fixed_params and Sensor.photo_params attributes

Added TiledModel.bands and TiledModel.data_type attributes

Added AlignChunks.markers and AlignChunks.match_mask_tiepoints attributes

Added BuildOrthomosaic.refine_seamlines attribute

Added DetectMarkers.cameras and DetectMarkers.maximum_residual attributes

Added ExportModel.colors_rgb_8bit and ExportPoints.colors_rgb_8bit attributes

Added ExportOrthophotos.tiff_tiled and ExportRaster.tiff_tiled attributes

Added OptimizeCameras.tiepoint_covariance attribute

Added BuildModel.smoothness and BuildTiledModel.smoothness attributes

Added target and workitem_count attributes to task classes

Added max_workgroup_size and workitem_size_tiles attributes to Tasks.BuildDem class

Added max_workgroup_size and workitem_size_cameras attributes to Tasks.BuildDenseCloud class

Added max_workgroup_size and workitem_size_cameras attributes to Tasks.BuildDepthMaps class

Added max_workgroup_size and workitem_size_cameras attributes to Tasks.BuildModel class

Added max_workgroup_size, workitem_size_cameras and workitem_size_tiles attributes to
Tasks.BuildOrthomosaic class

Added max_workgroup_size, workitem_size_cameras and face_count attributes attributes to
Tasks.BuildTiledModel class

Added max_workgroup_size, workitem_size_cameras and workitem_size_pairs attributes to Tasks.MatchPhotos
class

Added refine_seamlines argument to Chunk.buildOrthomosaic() method

Added face_count argument to Chunk.buildTiledModel() method

Added keypoints argument to Chunk.copy() method

Added maximum_residual and cameras arguments to Chunk.detectMarkers() method

Added tiff_tiled argument to Chunk.exportDem(), Chunk.exportOrthomosaic() and Chunk.exportOrthophotos()
methods

Added colors_rgb_8bit argument to Chunk.exportModel() and Chunk.exportPoints() methods

Added tiepoint_covariance argument to Chunk.optimizeCameras() method

Added confidence argument to DenseCloud.classifyPoints() method

Added mask_tiepoints and markers arguments to Document.alignChunks() method

Added ignore_lock argument to Document.open() method

Added type argument to Model.setTexture() and Model.texture() methods

Added workitem argument to Task.apply() method
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Added ModelFormatGLTF and ModelFormatX3D to ModelFormat enum

Added Car and Manmade to PointClass enum

Changed default value of filter argument in Chunk.buildDepthMaps() to MildFiltering

Removed Tasks.BuildModel.visibility_mesh attribute
3.30 PhotoScan version 1.4.4

Added AddPhotos.strip_extensions attribute

Added ExportRaster.image_description attribute

Added ExportShapes.export_attributes, ExportShapes.export_labels and ExportShapes.polygons_as_polylines
attributes

Added image_description argument to Chunk.exportDem() and Chunk.exportOrthomosaic() methods

Added format, polygons_as_polylines, export_labels and export_attributes arguments to Chunk.exportShapes()
method

Added format argument to Chunk.importShapes() method

Added RasterFormatTMS to RasterFormat enum
3.31 PhotoScan version 1.4.3

Added Version class

Added Tasks.DetectFiducials class

Added Chunk.detectFiducials() method

Added Sensor.calibrateFiducials() method

Added CoordinateSystem.addGeoid() method

Added PhotoScan.version attribute

Added Sensor.normalize_to_float attribute

Added minimum_dist attribute to Tasks.DetectMarkers class

Added minimum_dist argument to Chunk.detectMarkers() and Utils.detectTargets() methods

Added keypoints argument to PointCloud.copy() method

Changed default value of adaptive_fitting argument in Chunk.alignCameras() to False
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3.32 PhotoScan version 1.4.2

Added Tasks.ColorizeDenseCloud class

Added PointCloud.removeKeypoints() method

Added CoordinateSystem.transformationMatrix() method

Added Vector.cross() method

Added Shapes.updateAltitudes() method

Added log_enable, log_path, network_enable, network_host, network_path and network_port attributes to Application.Settings class

Added covariance_matrix and covariance_params attributes to Calibration class

Added flip_x, flip_y, flip_z attributes to Tasks.BuildDem and Tasks.BuildOrthomosaic classes

Added max_neighbors attribute to Tasks.BuildDenseCloud, Tasks.BuildDepthMaps and Tasks.BuildModel
classes

Added jpeg_quality, tiff_compression and update_gps_tags attributes to Tasks.UndistortPhotos class

Added copy_keypoints attribute to Tasks.DuplicateChunk class

Added width, height and world_transform attributes to Tasks.ExportRaster class

Added store_depth attribute to Tasks.BuildTiledModel class

Added DenseCloud.crs and DenseCloud.transform attributes

Added CoordinateSystem.wkt2 attribute

Added keep_keypoints argument to Chunk.matchPhotos() method

Added flip_x, flip_y, flip_z arguments to Chunk.buildDem() and Chunk.buildOrthomosaic() methods

Added max_neighbors argument to Chunk.buildDenseCloud() and Chunk.buildDepthMaps() methods

Added cull_faces argument to Chunk.buildOrthomosaic() method

Added reuse_depth and ghosting_filter arguments to Chunk.buildTiledModel() method

Added use_reflectance_panels and use_sun_sensor arguments to Chunk.calibrateReflectance() method

Added width, height and world_transform arguments to Chunk.exportDem() and Chunk.exportOrthomosaic()
methods

Added filter_mask argument to Chunk.estimateImageQuality() method

Added revision argument to NetworkClient.nodeList() method

Added ImagesData to DataSource enum

Added ModelFormatOSGB to ModelFormat enum

Added TiledModelFormatOSGB to TiledModelFormat enum
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3.33 PhotoScan version 1.4.1

Added OrthoProjection.Type enum

Added Camera.image() method

Added Chunk.loadReflectancePanelCalibration() method

Added PointCloud.Points.copy() and PointCloud.Points.resize() methods

Added PointCloud.Projections.resize() method

Added PointCloud.Tracks.copy() and PointCloud.Tracks.resize() methods

Added OrthoProjection.matrix, OrthoProjection.radius and OrthoProjection.type attributes

Added Tasks.AnalyzePhotos.filter_mask attribute

Added Tasks.CalibrateReflectance.use_reflectance_panels and Tasks.CalibrateReflectance.use_sun_sensor attributes

Added Tasks.MatchPhotos.mask_tiepoints attribute

Added Tasks.OptimizeCameras.adaptive_fitting attribute

Added strip_extensions argument to Chunk.addPhotos() method

Added keep_depth argument to Chunk.buildDenseCloud() method

Added adaptive_resolution argument to Chunk.buildUV() method

Added alpha argument to Chunk.exportModel() method

Added mask_tiepoints argument to Chunk.matchPhotos() method

Added adaptive_fitting argument to Chunk.optimizeCameras() method

Added mask argument to Utils.estimateImageQuality() method

Added CamerasFormatABC and CamerasFormatFBX to CamerasFormat enum

Added ImageFormatJP2 to ImageFormat enum

Added LegacyMapping to MappingMode enum
3.34 PhotoScan version 1.4.0

Added Tasks classes

Added Animation, OrthoProjection, Target and Vignetting classes

Added ShapesFormat enum

Added Marker.Type enum

Added Chunk.calibrateColors(), Chunk.calibrateReflectance() and Chunk.locateReflectancePanels() methods

Added Chunk.buildDepthMaps(), Chunk.importPoints(), Chunk.refineModel() and Chunk.removeLighting()
methods

Added Chunk.addDenseCloud(), Chunk.addDepthMaps(), Chunk.addElevation(), Chunk.addModel(),
Chunk.addOrthomosaic() and Chunk.addTiledModel() methods

Added Chunk.sortCameras(), Chunk.sortMarkers() and Chunk.sortScalebars() methods

Added DenseCloud.clear() method
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Added DepthMaps.clear() and DepthMaps.copy() methods

Added Elevation.clear() and Elevation.copy() methods

Added Model.clear() method

Added Orthomosaic.clear() and Orthomosaic.copy() methods

Added TiledModel.clear() and TiledModel.copy() methods

Added Image.gaussianBlur() and Image.uniformNoise() methods

Added NetworkTask.encode() method

Added Utils.createChessboardImage() and Utils.detectTargets() methods

Added Camera.Reference.location_accuracy and Camera.Reference.rotation_accuracy attributes

Added Camera.layer_index, Camera.master and Camera.vignetting attributes

Added Chunk.dense_clouds, Chunk.depth_maps_sets, Chunk.elevations, Chunk.models, Chunk.orthomosaics
and Chunk.tiled_models attributes

Added Chunk.animation, Chunk.camera_crs, Chunk.marker_crs and Chunk.world_crs attributes

Added CoordinateSystem.geoccs and CoordinateSystem.geoid_height attributes

Added Marker.Projection.valid attribute

Added Sensor.black_level, Sensor.fiducials, Sensor.fixed_calibration, Sensor.fixed_location, Sensor.fixed_rotation, Sensor.layer_index, Sensor.location, Sensor.master, Sensor.normalize_sensitivity, Sensor.rolling_shutter, Sensor.rotation, Sensor.sensitivity and Sensor.vignetting attributes

Added Camera.chunk, Marker.chunk, Scalebar.chunk and Sensor.chunk attributes

Added Marker.sensor and Marker.type attributes

Added Elevation.projection, Orthomosaic.projection and Shapes.projection attributes

Added DenseCloud.key and DenseCloud.label attributes

Added DepthMaps.key and DepthMaps.label attributes

Added Elevation.key and Elevation.label attributes

Added Model.key and Model.label attributes

Added Orthomosaic.key and Orthomosaic.label attributes

Added TiledModel.key and TiledModel.label attributes

Added point_colors argument to Chunk.buildDenseCloud() method

Added ghosting_filter argument to Chunk.buildTexture() method

Added minimum_size argument to Chunk.detectMarkers() method

Added raster_transform argument to Chunk.exportModel(), Chunk.exportPoints(), Chunk.exportTiledModel()
methods

Added tiff_overviews argument to Chunk.exportDem(), Chunk.exportOrthomosaic() and
Chunk.exportOrthophotos() methods

Added min_zoom_level and max_zoom_level arguments to Chunk.exportDem() and
Chunk.exportOrthomosaic() methods

Added cameras argument to Chunk.exportOrthophotos() method

Added image_format argument to Chunk.exportPoints() method
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Added page_numbers argument to Chunk.exportReport() method

Added items, crs, ignore_labels, threshold and progress arguments to Chunk.loadReference() method

Added create_markers argument to Chunk.loadReference() method

Added progress argument to Chunk.saveReference() method

Added quality, volumetric_masks, keep_depth and reuse_depth arguments to Chunk.buildModel() method

Added selected_faces and fix_borders arguments to Chunk.smoothModel() method

Added export_points, export_markers, use_labels and progress arguments to Chunk.exportCameras() method

Added channels and datatype arguments to Photo.image() method

Added CamerasFormatBlocksExchange and CamerasFormatORIMA to CamerasFormat enum

Added ImageFormatNone to ImageFormat enum

Added UndefinedLayout to ImageLayout enum

Added ModelFormatNone and ModelFormatABC to ModelFormat enum

Added PointsFormatNone and PointsFormatCesium to PointsFormat enum

Added RasterFormatNone to RasterFormat enum

Added ReferenceFormatNone and ReferenceFormatAPM to ReferenceFormat enum

Added TiledModelFormatNone, TiledModelFormatCesium and TiledModelFormatSLPK to TiledModelFormat
enum

Renamed Chunk.master_channel attribute to Chunk.primary_channel

Removed MatchesFormat enum

Removed Chunk.exportMatches() method

Removed Camera.Reference.accuracy_ypr attribute

Removed quality, filter, cameras, keep_depth, reuse_depth arguments from Chunk.buildDenseCloud() method

Removed color_correction argument from Chunk.buildOrthomosaic() and Chunk.buildTexture() methods

Removed fit_shutter argument from Chunk.optimizeCameras() method
3.35 PhotoScan version 1.3.5
No Python API changes
3.36 PhotoScan version 1.3.4
No Python API changes
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3.37 PhotoScan version 1.3.3

Added network_links argument to Chunk.exportDem() and Chunk.exportOrthomosaic() methods

Added read_only argument to Document.open() method

Added NetworkClient.setNodeCPUEnable() and NetworkClient.setNodeGPUMask() methods

Added Chunk.modified, DenseCloud.modified, DepthMaps.modified, Document.modified, Elevation.modified,
Masks.modified, Model.modified, Orthomosaic.modified, PointCloud.modified, Shapes.modified, Thumbnails.modified, TiledModel.modified attributes

Added Document.read_only attribute

Added CamerasFormatSummit to CamerasFormat enum
3.38 PhotoScan version 1.3.2

Added vertex_colors argument to Chunk.buildModel() method

Added Shape.vertex_ids attribute
3.39 PhotoScan version 1.3.1

Added Settings and TiledModel classes

Added Application.getBool() method

Added Camera.unproject() method

Added Chunk.addFrames(), Chunk.addMarkerGroup(), Chunk.addScalebarGroup() and
Chunk.buildSeamlines() methods

Added DenseCloud.pickPoint() and DenseCloud.updateStatistics() methods

Added Elevation.altitude() method

Added Matrix.svd() method

Added Model.pickPoint() method

Added Orthomosaic.reset() and Orthomosaic.update() methods

Added PointCloud.pickPoint() method

Added filter argument to Application.getOpenFileName(), Application.getOpenFileNames() and Application.getSaveFileName() methods

Added point and visibility arguments to Chunk.addMarker() method

Added raster_transform and write_scheme arguments to Chunk.exportDem() method

Added write_scheme and white_background arguments to Chunk.exportOrthomosaic() method

Added white_background argument to Chunk.exportOrthophotos() method

Added projection argument to Chunk.exportMarkers() method

Added markers argument to Chunk.exportModel() method

Added pairs argument to Chunk.matchPhotos() method
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Added columns and delimiter arguments to Chunk.saveReference() method

Added version argument to Document.save() method

Renamed npasses argument in Chunk.smoothModel() method to strength and changed its type to float

Renamed from and to arguments in CoordinateSystem.transform(), DenseCloud.assignClass(), DenseCloud.assignClassToSelection() and DenseCloud.classifyGroundPoints() methods to avoid collision with reserved words

Added Application.settings attribute

Added Chunk.tiled_model attribute

Added ShapeGroup.color and ShapeGroup.show_labels attributes

Added ImageFormatTGA to ImageFormat enum
3.40 PhotoScan version 1.3.0

Added MarkerGroup, Masks, ScalebarGroup, Shutter and Thumbnails classes

Added Application.PhotosPane class

Added Model.Statistics class

Added Orthomosaic.Patch and Orthomosaic.Patches classes

Added PointCloud.Filter class

Added CamerasFormat, EulerAngles, ImageFormat, ImageLayout, MaskOperation, MaskSource, MatchesFormat, ModelFormat, ModelViewMode, PointClass, PointsFormat, RasterFormat, ReferenceFormat, ReferenceItems, RotationOrder, TiffCompression, TiledModelFormat enums

Added Application.captureOrthoView() method

Added Chunk.refineMarkers() method

Added CoordinateSystem.listBuiltinCRS() class method

Added Matrix.translation() method

Added Model.statistics() method

Added NetworkClient.serverInfo(), NetworkClient.nodeStatus(), NetworkClient.setNodeCapability() and NetworkClient.quitNode() methods

Added Photo.imageMeta() method

Added Shape.area(), Shape.perimeter2D(), Shape.perimeter3D() and Shape.volume() methods

Added Utils.createMarkers() method

Added source argument to Application.captureModelView() method

Added image_format argument to Chunk.exportDem() mehod

Added write_alpha argument to Chunk.exportOrthophotos() method

Added image_format and write_alpha arguments to Chunk.exportOrthomosaic() method

Added groups, projection, shift and progress arguments to Chunk.exportShapes() method

Added items and progress arguments to Chunk.copy() method

Added sensor argument to Chunk.addCamera() method
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Added layout argument to Chunk.addPhotos() method

Added jpeg_quality argument to Chunk.exportOrthomosaic() and Chunk.exportOrthophotos() methods

Added fill_holes argument to Chunk.buildOrthomosaic() method

Added fit_shutter argument to Chunk.optimizeCameras() method

Added settings argument to Chunk.exportReport() method

Added progress argument to various DenseCloud methods

Added from argument to DenseCloud.classifyGroundPoints() method

Added chunks and progress arguments to Document.append() method

Added progress argument to Document.alignChunks() and Document.mergeChunks() methods

Added revision argument to NetworkClient.batchList(), NetworkClient.batchStatus() methods

Added Application.photos_pane attribute

Added Camera.shutter attribute

Added Chunk.masks and Chunk.thumbnails attributes

Added Chunk.marker_groups and Chunk.scalebar_groups attributes

Added Chunk.euler_angles and Chunk.scalebar_accuracy attributes

Added CoordinateSystem.name attribute

Added Marker.group and Scalebar.group attributes

Added Orthomosaic.patches attribute

Added RasterTransform.false_color attribute

Added Sensor.bands attribute

Added Shape.attributes attribute

Added DepthMapsData, TiledModelData and OrthomosaicData to DataSource enum

Added CircularTarget14bit to TargetType enum

Renamed CameraReference class to Camera.Reference

Renamed ConsolePane class to Application.ConsolePane

Renamed MarkerProjection class to Marker.Projection

Renamed MarkerProjections class to Marker.Projections

Renamed MarkerReference class Marker.Reference

Renamed MeshFace class to Model.Face

Renamed MeshFaces class to Model.Faces

Renamed MeshTexVertex class to Model.TexVertex

Renamed MeshTexVertices class to Model.TexVertices

Renamed MeshVertex class to Model.Vertex

Renamed MeshVertices class to Model.Vertices

Renamed PointCloudCameras class to PointCloud.Cameras

Renamed PointCloudPoint class to PointCloud.Point
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Renamed PointCloudPoints class to PointCloud.Points

Renamed PointCloudProjection class to PointCloud.Projection

Renamed PointCloudProjections class to PointCloud.Projections

Renamed PointCloudTrack class to PointCloud.Track

Renamed PointCloudTracks class to PointCloud.Tracks

Renamed ScalebarReference class to Scalebar.Reference

Renamed ShapeVertices class to Shape.Vertices

Renamed Application.enumOpenCLDevices() method to Application.enumGPUDevices()

Renamed Shape.boundary attribute to Shape.boundary_type

Renamed Chunk.accuracy_cameras to Chunk.camera_location_accuracy

Renamed Chunk.accuracy_cameras_ypr to Chunk.camera_rotation_accuracy

Renamed Chunk.accuracy_markers to Chunk.marker_location_accuracy

Renamed Chunk.accuracy_projections to Chunk.marker_projection_accuracy

Renamed Chunk.accuracy_tiepoints to Chunk.tiepoint_accuracy

Renamed method argument in Chunk.importMasks() method to source and changed its type to MaskSource

Replaced preselection argument with generic_preselection and reference_preselection arguments in
Chunk.matchPhotos() method

Replaced fit_cxcy argument with fit_cx and fit_cy arguments in Chunk.optimizeCameras() method

Replaced fit_k1k2k3 argument with fit_k1, fit_k2 and fit_k3 arguments in Chunk.optimizeCameras() method

Replaced fit_p1p2 argument with fit_p1 and fit_p2 arguments in Chunk.optimizeCameras() method

Replaced Application.cpu_cores_inactive with Application.cpu_enable attribute

Changed type of source_data argument in Chunk.buildContours() to DataSource

Changed type of format argument in Chunk.importCameras() and Chunk.exportCameras() methods to CamerasFormat

Changed type of rotation_order argument in Chunk.exportCameras() to RotationOrder

Changed type of format argument in Chunk.exportDem() and Chunk.exportOrthomosaic() methods to RasterFormat

Changed type of format argument in Chunk.exportMatches() method to MatchesFormat

Changed type of texture_format argument in Chunk.exportModel() method to ImageFormat

Changed type of format argument in Chunk.importModel() and Chunk.exportModel() methods to ModelFormat

Changed type of format argument in Chunk.exportPoints() method to PointsFormat

Changed type of tiff_compression argument in Chunk.exportOrthomosaic() and Chunk.exportOrthophotos()
methods to TiffCompression

Changed type of items argument in Chunk.exportShapes() method to Shape.Type

Changed type of format argument in Chunk.exportTiledModel() method to TiledModelFormat

Changed type of mesh_format argument in Chunk.exportTiledModel() method to ModelFormat

Changed type of operation argument in Chunk.importMasks() method to MaskOperation
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Changed type of format argument in Chunk.loadReference() and Chunk.saveReference() methods to ReferenceFormat

Changed type of items argument in Chunk.saveReference() method to ReferenceItems

Removed return values from Camera.open(), Chunk.addPhotos(), Chunk.alignCameras(),
Chunk.buildContours(), Chunk.buildDem(), Chunk.buildDenseCloud(), Chunk.buildModel(),
Chunk.buildOrthomosaic(), Chunk.buildPoints(), Chunk.buildTexture(), Chunk.buildTiledModel(),
Chunk.buildUV(), Chunk.decimateModel(), Chunk.detectMarkers(), Chunk.estimateImageQuality(),
Chunk.exportCameras(), Chunk.exportDem(), Chunk.exportMarkers(), Chunk.exportMatches(),
Chunk.exportModel(), Chunk.exportOrthomosaic(), Chunk.exportOrthophotos(), Chunk.exportPoints(),
Chunk.exportReport(), Chunk.exportShapes(), Chunk.exportTiledModel(), Chunk.importCameras(),
Chunk.importDem(), Chunk.importMarkers(), Chunk.importMasks(), Chunk.importModel(),
Chunk.importShapes(), Chunk.loadReference(), Chunk.loadReferenceExif(), Chunk.matchPhotos(),
Chunk.optimizeCameras(), Chunk.remove(), Chunk.saveReference(), Chunk.smoothModel(),
Chunk.thinPointCloud(), Chunk.trackMarkers(), CirTransform.calibrate(), CoordinateSystem.init(),
DenseCloud.classifyGroundPoints(), DenseCloud.compactPoints(), DenseCloud.selectMaskedPoints(),
DenseCloud.selectPointsByColor(), Document.alignChunks(), Document.append(), Document.clear(),
Document.mergeChunks(), Document.open(), Document.remove(), Document.save(), Mask.load(),
Model.closeHoles(), Model.fixTopology(), Model.loadTexture(), Model.removeComponents(),
Model.saveTexture(), Model.setTexture(), NetworkClient.abortBatch(), NetworkClient.abortNode(), NetworkClient.connect(), NetworkClient.pauseBatch(), NetworkClient.pauseNode(), NetworkClient.resumeBatch(),
NetworkClient.resumeNode(), NetworkClient.setBatchPriority(), NetworkClient.setNodePriority(),
Photo.open(), PointCloud.export(), RasterTransform.calibrateRange(), Thumbnail.load() methods in favor
of exceptions

Removed Chunk.exportContours() method

Removed obsolete Matrix.diag() and Matrix.translation() class methods

Removed unused focal_length argument from Calibration.save() method

Modified Utils.mat2opk() and Utils.opk2mat() methods to work with camera to world rotation matrices
3.41 PhotoScan version 1.2.6
No Python API changes
3.42 PhotoScan version 1.2.5

Added ShapeGroup and ShapeVertices classes

Added CoordinateSystem.proj4 and CoordinateSystem.geogcs attributes

Added Shapes.shapes and Shapes.groups attributes

Added Shape.label, Shape.vertices, Shape.group, Shape.has_z, Shape.key and Shape.selected attributes

Added Shapes.addGroup(), Shapes.addShape() and Shapes.remove() methods

Added CoordinateSystem.transform() method

Added Matrix.Diag(), Matrix.Rotation(), Matrix.Translation() and Matrix.Scale() class methods

Added Matrix.rotation() and Matrix.scale() methods

Added DenseCloud.restorePoints() and DenseCloud.selectPointsByColor() methods
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Added Application.captureModelView() method

Added Mask.invert() method

Added adaptive_fitting parameter to Chunk.alignCameras() method

Added load_rotation and load_accuracy parameters to Chunk.loadReferenceExif() method

Added source parameter to Chunk.buildTiledModel() method

Added fill_holes parameter to Chunk.buildTexture() method
3.43 PhotoScan version 1.2.4

Added NetworkClient and NetworkTask classes

Added Calibration.f, Calibration.b1, Calibration.b2 attributes

Added Chunk.exportMatches() method

Added DenseCloud.compactPoints() method

Added Orthomosaic.removeOrthophotos() method

Added fit_b1 and fit_b2 parameters to Chunk.optimizeCameras() method

Added tiff_big parameter to Chunk.exportOrthomosaic(), Chunk.exportDem() and Chunk.exportOrthophotos()
methods

Added classes parameter to Chunk.exportPoints() method

Added progress parameter to processing methods

Removed Calibration.fx, Calibration.fy, Calibration.skew attributes
3.44 PhotoScan version 1.2.3

Added tiff_compression parameter to Chunk.exportOrthomosaic() and Chunk.exportOrthophotos() methods
3.45 PhotoScan version 1.2.2

Added Camera.orientation attribute

Added chunks parameter to Document.save() method
3.46 PhotoScan version 1.2.1

Added CirTransform and RasterTransform classes

Added Chunk.cir_transform and Chunk.raster_transform attributes

Added Chunk.exportOrthophotos() method

Added udim parameter to Chunk.exportModel() method

Renamed RasterTransform enum to RasterTransformType
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3.47 PhotoScan version 1.2.0

Added Elevation and Orthomosaic classes

Added Shape and Shapes classes

Added Antenna class

Added DataSource enum

Added Camera.error() method

Added Chunk.buildContours() and Chunk.exportContours() methods

Added Chunk.importShapes() and Chunk.exportShapes() methods

Added Chunk.exportMarkers() and Chunk.importMarkers() methods

Added Chunk.importDem() method

Added Chunk.buildDem(), Chunk.buildOrthomosaic() and Chunk.buildTiledModel() methods

Added PointCloud.removeSelectedPoints() and PointCloud.cropSelectedPoints() methods

Added Utils.mat2opk(), Utils.mat2ypr(), Utils.opk2mat() and Utils.ypr2mat() methods

Added Chunk.elevation, Chunk.orthomosaic and Chunk.shapes attributes

Added Chunk.accuracy_cameras_ypr attribute

Added Sensor.antenna, Sensor.plane_count and Sensor.planes attributes

Added Calibration.p3 and Calibration.p4 attributes

Added Camera.planes attribute

Added CameraReference.accuracy_ypr attribute

Added CameraReference.accuracy, MarkerReference.accuracy and ScalebarReference.accuracy attributes

Added Application.activated attribute

Added Chunk.image_brightness attribute

Added fit_p3 and fit_p4 parameters to Chunk.optimizeCameras() method

Added icon parameter to Application.addMenuItem() method

Added title and description parameters to Chunk.exportReport() method

Added operation parameter to Chunk.importMasks() method

Added columns, delimiter, group_delimiters, skip_rows parameters to Chunk.loadReference() method

Added items parameter to Chunk.saveReference() method

Renamed Chunk.exportModelTiled() to Chunk.exportTiledModel()

Renamed Chunk.exportOrthophoto() to Chunk.exportOrthomosaic()

Removed OrthoSurface and PointsSource enums

Removed PointCloud.groups attribute

Removed Chunk.camera_offset attribute
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3.48 PhotoScan version 1.1.1

Added Chunk.exportModelTiles() method

Added noparity parameter to Chunk.detectMarkers() method

Added blockw and blockh parameters to Chunk.exportPoints() method
3.49 PhotoScan version 1.1.0

Added CameraOffset and ConsolePane classes

Added CameraGroup, CameraReference, ChunkTransform, DepthMap, DepthMaps, MarkerReference, MarkerProjection, Mask, PointCloudGroups, PointCloudTrack, PointCloudTracks, ScalebarReference, Thumbnail
classes

Added Chunk.key, Sensor.key, Camera.key, Marker.key and Scalebar.key attributes

Added Application.console attribute

Added Application.addMenuSeparator() method

Added Chunk.importMasks() method

Added Chunk.addSensor(), Chunk.addCameraGroup(), Chunk.addCamera(), Chunk.addMarker(),
Chunk.addScalebar() methods

Added Chunk.addPhotos(), Chunk.addFrame() methods

Added Chunk.master_channel and Chunk.camera_offset attributes

Added Calibration.error() method

Added Matrix.mulp() and Matrix.mulv() methods

Added DenseCloud.assignClass(), DenseCloud.assignClassToSelection(), DenseCloud.removePoints() methods

Added DenseCloud.classifyGroundPoints() and DenseCloud.selectMaskedPoints() methods

Added Model.renderNormalMap() method

Added DenseCloud.meta and Model.meta attributes

Added PointCloud.tracks, PointCloud.groups attributes

Added Image.tostring() and Image.fromstring() methods

Added Image.channels property

Added U16 data type support in Image class

Added classes parameter to Chunk.buildModel() method

Added crop_borders parameter to Chunk.exportDem() method

Added chunk parameter to Document.addChunk() method

Added format parameter to Calibration.save() and Calibration.load() methods

Moved OpenCL settings into Application class

Converted string constants to enum objects

Removed Cameras, Chunks, DenseClouds, Frame, Frames, GroundControl, GroundControlLocations, GroundControlLocation, Markers, MarkerPositions, Models, Scalebars, Sensors classes
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3.50 PhotoScan version 1.0.0

Added DenseCloud and DenseClouds classes

Added Chunk.exportModel() and Chunk.importModel() methods

Added Chunk.estimateImageQuality() method

Added Chunk.buildDenseCloud() and Chunk.smoothModel() methods

Added Photo.thumbnail() method

Added Image.resize() method

Added Application.enumOpenCLDevices() method

Added Utils.estimateImageQuality() method

Added Camera.meta, Marker.meta, Scalebar.meta and Photo.meta attributes

Added Chunk.dense_cloud and Chunk.dense_clouds attributes

Added page parameter to Model.setTexture() and Model.texture() methods

Added shortcut parameter to Application.addMenuItem() method

Added absolute_paths parameter to Document.save() method

Added fit_f, fit_cxcy, fit_k1k2k3 and fit_k4 parameters to Chunk.optimizePhotos() method

Changed parameters of Chunk.buildModel() and Chunk.buildTexture() methods

Changed parameters of Chunk.exportPoints() method

Changed parameters of Model.save() method

Changed return value of Chunks.add() method

Removed Chunk.buildDepth() method

Removed Camera.depth() and Camera.setDepth() methods

Removed Frame.depth() and Frame.setDepth() methods

Removed Frame.depth_calib attribute
3.51 PhotoScan version 0.9.1

Added Sensor, Scalebar and MetaData classes

Added Camera.sensor attribute

Added Chunk.sensors attribute

Added Calibration.width, Calibration.height and Calibration.k4 attributes

Added Chunk.refineMatches() method

Added Model.area() and Model.volume() methods

Added Model.renderDepth(), Model.renderImage() and Model.renderMask() methods

Added Chunk.meta and Document.meta attributes

Added Calibration.project() and Calibration.unproject() methods

Added Application.addMenuItem() method
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Added Model.closeHoles() and Model.fixTopology() methods
3.52 PhotoScan version 0.9.0

Added Camera, Frame and CoordinateSystem classes

Added Chunk.exportReport() method

Added Chunk.trackMarkers() and Chunk.detectMarkers() methods

Added Chunk.extractFrames() and Chunk.removeFrames() methods

Added Chunk.matchPhotos() method

Added Chunk.buildDepth() and Chunk.resetDepth() methods

Added Chunk.cameras property

Added Utils.createDifferenceMask() method

Revised Chunk.alignPhotos() method

Revised Chunk.buildPoints() method

Revised Chunk.buildModel() method

Removed Photo class (deprecated)

Removed GeoProjection class (deprecated)

Removed Chunk.photos property (deprecated)
3.53 PhotoScan version 0.8.5

Added Chunk.fix_calibration property

Added Chunk.exportCameras() method

Added Chunk.exportPoints() method for dense/sparse point cloud export

Added accuracy_cameras, accuracy_markers and accuracy_projections properties to the GroundControl class

Added Image.undistort() method

Added PointCloudPoint.selected and PointCloudPoint.valid properties

Added GeoProjection.authority property

Added GeoProjection.init() method

Moved GroundControl.optimize() method to Chunk.optimize()

Removed “fix_calibration” parameter from Chunk.alignPhotos() method

Removed GeoProjection.epsg property
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3.54 PhotoScan version 0.8.4

Added GroundControl.optimize() method

Command line scripting support removed
3.55 PhotoScan version 0.8.3
Initial version of PhotoScan Python API
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PYTHON MODULE INDEX
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