PointCloudConsumer

Reads point cloud features for testing purposes, including any accumulated point cloud operations. No additional operations are performed, and nothing is done with the features.

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Typical Uses

Performance testing or benchmarking point cloud processing.
Debugging point cloud processing.
Testing point cloud feature validity.

How does it work?

The PointCloudConsumer receives point cloud features and reads all of their data at their current state in the workspace. It does not perform any new operations on the point clouds.

FME handles point clouds in a “delayed evaluation” model. A point cloud reader reads essential information about a point cloud, but does not read the actual point contents until it is absolutely necessary. Transformer operations are accumulated until the results are needed, often being held until the features enter a writer. At that point, the required data is fully read and processed.

This is intended to optimize performance - for example, if a point cloud is both clipped and reprojected, FME will optimize processing by not reprojecting data that falls outside of the clip boundary and is ultimately discarded.

The PointCloudConsumer transformer forces this read to occur, and any accumulated operations are performed as the features are read. Nothing is done with the read features, and the transformer will not improve performance - it simply emulates the effect that reading the data would have, wherever it is placed.

It can be used to test workspace performance without configuring writers, and can also be useful for debugging point cloud processing workspaces with multiple accumulated operations. It may also be used for point cloud geometry validation, as it will reject any non-point cloud features.

Note Though the transformer has a parameter that can be used to adjust the way in which the point cloud is read (Block Size), it is primarily of interest for internal Safe performance testing and is not generally useful in a production environment.

Examples

Usage Notes

The Enable Feature Caching option in FME Workbench should be disabled to obtain more accurate processing benchmarks.

Choosing a Point Cloud Transformer

FME has a selection of transformers for working specifically with point cloud data.

For information on point cloud geometry and properties, see Point Clouds (IFMEPointCloud).

Point Cloud Transformers

PointCloudCombiner	Combines features into a single point cloud. Point cloud and non-point cloud geometries are supported.
PointCloudComponentAdder	Adds new components with constant values to a point cloud.
PointCloudComponentCopier	Copies selected component values onto either a new or existing component
PointCloudComponentKeeper	Keeps only specified point cloud components, discarding all others.
PointCloudComponentRemover	Removes specified components from a point cloud.
PointCloudComponentRenamer	Renames an existing component.
PointCloudComponentTypeCoercer	Alters the data type of point cloud components, and converts component values if required.
PointCloudConsumer	Reads point cloud features for testing purposes, including any accumulated point cloud operations. No additional operations are performed, and nothing is done with the features.
PointCloudCreator	Creates a point cloud of specified size and density, with default component values.
PointCloudExpressionEvaluator	Evaluates expressions on each point in a point cloud feature, including algebraic operations and conditional statements, and sets individual point cloud component values.
PointCloudExtractor	Serializes the geometry of a point cloud feature into a Blob attribute, encoding the contents according to a choice of common binary point cloud formats.
PointCloudFilter	Separates point clouds into multiple features, based on evaluating expressions including component values, and creates a separate output port for each expression defined.
PointCloudMerger	Merges point clouds by joining points where selected component values match (join key), including x, y, z, and other components. Component values are transferred between point clouds and output is filtered based on matching success and duplication.
PointCloudOnRasterComponentSetter	Sets point cloud component values by overlaying a point cloud on a raster. The component values for each point are interpolated from band values at the point location.
PointCloudPropertyExtractor	Extracts the geometry properties of a point cloud feature and exposes them as attributes, optionally checking for their existence, retrieving component properties, and finding minimum and maximum values. Extents may also be recalculated and updated.
PointCloudReplacer	Decodes a binary attribute containing encoded point clouds stored as Blobs, replacing the feature’s geometry with the decoded point cloud.
PointCloudSimplifier	Reduces the number of points in a point cloud by selectively keeping points based on the shape of the point cloud. The simplified and removed points are output as two discrete point clouds.
PointCloudSorter	Sorts the points within a point cloud by one or more component values.
PointCloudSplitter	Separates point clouds into multiple features based on component values, color, or first/last return.
PointCloudStatisticsCalculator	Calculates statistics on point cloud components and adds the results as attributes.
PointCloudSurfaceBuilder	Takes an input point cloud and reconstructs it into an output mesh.
PointCloudThinner	Reduces the number of points in (thins) a point cloud by keeping points at a fixed interval, a maximum number of points, or a set quantity of first or last points. Remaining points are discarded.
PointCloudToPointCoercer	Converts point clouds to point or multipoint geometries, optionally retaining attribute and component values.
PointCloudTransformationApplier	Applies a point cloud’s scale, offset, or transformation matrix to it, recalculating component values and removing the transformation values.

Configuration

Input Ports

Output Ports

Parameters

Editing Transformer Parameters

Transformer parameters can be set by directly entering values, using expressions, or referencing other elements in the workspace such as attribute values or user parameters. Various editors and context menus are available to assist. To see what is available, click beside the applicable parameter.

How to Set Parameter Values

Defining Values

There are several ways to define a value for use in a Transformer. The simplest is to simply type in a value or string, which can include functions of various types such as attribute references, math and string functions, and workspace parameters.

Using the Text Editor

The Text Editor provides a convenient way to construct text strings (including regular expressions) from various data sources, such as attributes, parameters, and constants, where the result is used directly inside a parameter.

Text Editor

Using the Arithmetic Editor

The Arithmetic Editor provides a convenient way to construct math expressions from various data sources, such as attributes, parameters, and feature functions, where the result is used directly inside a parameter.

Arithmetic Editor

Conditional Values

Set values depending on one or more test conditions that either pass or fail.

Parameter Condition Definition Dialog

Content

Expressions and strings can include a number of functions, characters, parameters, and more.

When setting values - whether entered directly in a parameter or constructed using one of the editors - strings and expressions containing String, Math, Date/Time or FME Feature Functions will have those functions evaluated. Therefore, the names of these functions (in the form @<function_name>) should not be used as literal string values.

Content Types

String Functions	These functions manipulate and format strings.
Special Characters	A set of control characters is available in the Text Editor.
Math Functions	Math functions are available in both editors.
Date/Time Functions	Date and time functions are available in the Text Editor.
Math Operators	These operators are available in the Arithmetic Editor.
FME Feature Functions	These return primarily feature-specific values.
FME Parameters	FME and workspace-specific parameters may be used.
Creating and Modifying User Parameters	Create your own editable parameters.

Dialog Options - Tables

Table Tools

Transformers with table-style parameters have additional tools for populating and manipulating values.

Row Reordering

Enabled once you have clicked on a row item. Choices include:

Add a row
Remove a row
Move current row up one
Move current row down one
Move current row to top
Move current row to bottom

Cut, Copy, and Paste

Enabled once you have clicked on a row item. Choices include:

Cut a row - delete and copy to clipboard
Copy a row to the clipboard
Paste a row from the clipboard

Cut, copy, and paste may be used within a transformer, or between transformers.

Filter

Start typing a string, and the matrix will only display rows matching those characters. Searches all columns. This only affects the display of attributes within the transformer - it does not alter which attributes are output.

Import

Import populates the table with a set of new attributes read from a dataset. Specific application varies between transformers.

Reset/Refresh

Generally resets the table to its initial state, and may provide additional options to remove invalid entries. Behavior varies between transformers.

Note: Not all tools are available in all transformers.

For more information, see Transformer Parameter Menu Options.

Reference

Processing Behavior	Feature-Based
Feature Holding	No
Dependencies	None
Aliases
History

FME Community

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Search for all results about the PointCloudConsumer on the FME Community.

Examples may contain information licensed under the Open Government Licence – Vancouver, Open Government Licence - British Columbia, and/or Open Government Licence – Canada.

Keywords: point "point cloud" cloud PointCloud LiDAR sonar