Accesses the Amazon Rekognition Service AI computer vision service to detect objects, faces, and text in images and to describe image contents and faces.

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Typical Uses

  • Submitting images to the Amazon AWS Rekognition service to
    • detect individual objects
    • describe the general contents
    • extract small amounts of text
    • detect faces and facial descriptions in an image
    • detect explicit or suggestive adult content in an image
    • detect PPE (Personal Protective Equipment) in an image

How does it work?

The RekognitionConnector uses your Amazon AWS account credentials (either via a previously defined FME web connection, or by setting up a new FME web connection right from the transformer) to access the computer vision service.

It will submit images to the service, and return features with attributes that describe the contents of the image. Object detection, text detection, and face detection can be performed.

  • For object detection, if the service is able to identify the exact location of an object in the image, a bounding box geometry will also be returned.
  • Text detection and face detection always return bounding boxes around the detected text or face.
  • Image moderation will return the input feature, with moderation labels added when unsafe content is detected.

Each input image may result in several output features.

Usage Notes

  • For better performance, requests to the Rekognition service are made in parallel, and are returned as soon as they complete. Consequently, detection results will not be returned in the same order as their associated requests.
  • The RekognitionConnector is able to extract up to 50 words per image when performing text detection. This makes it unsuitable for detecting full pages of text, as from a scanned document.

  • While powerful, the use of AI has important legal and ethical implications. Consult your local AI legislation and ethical guidelines before applying the RekognitionConnector in a production environment.
  • For an overview of Rekognition's capabilities and limitations, please see Amazon's FAQ on the topic:


Input Ports

Output Ports


The remaining parameters available depend on the value of the Request > Action parameter. Parameters for each Action are detailed below.

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 Amazon AWS Account with Rekognition access
Aliases AmazonAWSRekognitionConnector
History Released FME 2019.2

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