Inference

In this section, we will see how to use our trained models. You can use either one of our pre-trained models or train a model yourself.

Using a model at inference-time typically consists of a few standard steps:

• The setup:

  • Load the model

  • Load a data file or open an event-based camera

  • Start streaming

• The processing loop:

  • Gather data from an event-based camera or from a RAW or DAT file

  • Pre-process the data using the same format used for training the model

  • Perform inference by passing the pre-processed data to the model

  • Gather and process the results

More details on the inference loop can be found in these examples:

• Detection and tracking pipeline

• Use directly a torchjit model

Note

Tutorials in this section were created using Jupiter Notebooks. You can execute them on your computer by downloading the source code at the top or bottom of the page. More information can be found on this page.