Machine Learning

pro

Features

Unlock the potential of Event-Based machine learning, with a set of dedicated tools providing everything you need to start execution of Deep Neural Network (DNN) with events.

Libraries

The Metavision SDK ML module contains a collection of python utility modules to facilitate the navigation into large event-based datasets, and prepare everything you need to develop your first neural network:

  • metavision_ml.event_io : events recordings & live event-based camera manipulation.

  • metavision_ml.preprocessing: functions to apply to events before feeding them them to a machine learning model.

  • metavision_ml.data contains a class that allows to build a Sequential Dataloader for a training loop.

It also contains a set of C++ components that can be connected to form a live Detection & Tracking pipeline, working on a live events stream from a camera. The C++ API is using TorchJit to run inference with pytorch models.

A pre-built demo pipeline is delivered in the module, running inference on a pretrained automotive model.

Datasets & models

Access a large HD automotive dataset, with 15h of recordings and 23 millions of labels. Use our pytorch automotive model trained on this dataset.

Note

You can already start looking in large event-based dataset, with our previously released QVGA dataset.

Demos

As part of the Metavision SDK ML module, run our Live detection and tracking pipeline, keeping track of targets in realtime at a 100Hz refresh rate.

More info

Want to know more, and start experimenting Machine Learning with Events?

Contact us and get access to Metavision Intelligence Professional.