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.


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).


Input Ports

Output Ports


Editing Transformer Parameters

Using a set of menu options, transformer parameters can be assigned by referencing other elements in the workspace. More advanced functions, such as an advanced editor and an arithmetic editor, are also available in some transformers. To access a menu of these options, click beside the applicable parameter. For more information, see Transformer Parameter Menu Options.

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. There are a number of tools and shortcuts that can assist in constructing values, generally available from the drop-down context menu adjacent to the value field.

Dialog Options - Tables

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


Processing Behavior


Feature Holding


Dependencies None

FME Community

The FME Community is the place for demos, how-tos, articles, FAQs, and more. Get answers to your questions, learn from other users, and suggest, vote, and comment on new features.

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


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

Keywords: point "point cloud" cloud PointCloud LiDAR sonar