The platform supports several microservices: Analytics, Annotations, Domain Adaptation and Preview. These microservices add additional metrics and processing for outputs of the Rendered.ai engine.
All of the microservices documented here can be accessed through the Rendered.ai SDK, ‘anatools’. For a complete list of the SDK functionality, see the SDK Developer Guide, and for a general overview see the developer guide Getting Started with the SDK.
The Analytics microservice is used to generate different types of statistical analytics about datasets. Call this microservice to learn more about objects in datasets and images properties.
Read about how to use the Analytics microservice with the SDK through this Jupyter Notebook.
The annotation microservice is used to convert the Ana annotations produced for each dataset by the Rendered.ai engine into common formats that are used in machine learning pipelines. It can be run through the UI or via the SDK.
Below is an image of a dataset which has a COCO annotation generated and ready to download. Pressing the button marked “+” next to “Annotations” in the bottom right will provide a prompt to create a new annotation of a chosen format.
Read about how to generate the Annotation locally on your machine with the SDK through this Jupyter Notebook.
The Domain Adaptation microservice is used to modify images of a dataset using a CycleGAN. This can lead to better results in machine learning pipelines by better matching real and synthetic data. For more information about CycleGAN, see here.
Read about how to use the Domain Adaptation microservice with the SDK through this Jupyter Notebook.
The Preview microservice is used to create an example instance of an output image that a graph may generate. Preview images may not be exact representations of output from the channel, especially if the preview is using any techniques to reduce rendering time which would not be used in the production output imagery.
The Preview microservice can be accessed through the Rendered.ai web interface in the top right of the graph editor by pressing “Preview” (see image below.) The preview will then generate with a status message shown in the bottom left. After a few moments the preview image will appear on the page. The preview image will then be used as a thumbnail for the associated graph.
Running the Preview Microservice in the Rendered.ai web interface