  In this paper we introduce the Perception for Autonomous Systems (PAZ)
software library. PAZ is a hierarchical perception library that allow users to
manipulate multiple levels of abstraction in accordance to their requirements
or skill level. More specifically, PAZ is divided into three hierarchical
levels which we refer to as pipelines, processors, and backends. These
abstractions allows users to compose functions in a hierarchical modular scheme
that can be applied for preprocessing, data-augmentation, prediction and
postprocessing of inputs and outputs of machine learning (ML) models. PAZ uses
these abstractions to build reusable training and prediction pipelines for
multiple robot perception tasks such as: 2D keypoint estimation, 2D object
detection, 3D keypoint discovery, 6D pose estimation, emotion classification,
face recognition, instance segmentation, and attention mechanisms.
