ROS and PyTorch interfaces

The toolbox provides interfaces to ROS and PyTorch – two very important connections that connect the toolbox to physical sensors and machine learning frameworks.

ROS interface

The ROS interface allows you to read images, point clouds and other message from ROS bag files or published topics from a running ROS system.

Reading a ROS bag file

We can

>>> from machinevisiontoolbox import RosBag
>>> bag = RosBag('test_ros1.bag')
!! ImportError: rosbags is required for ROS bag support. Install it with: pip install rosbags or pip install machinevision-toolbox-python[ros] [ERR unknown:21:unknown (source/ros-pytorch.rst)]
>>> bag.print()
!! NameError: name 'bag' is not defined [ERR unknown:21:unknown (source/ros-pytorch.rst)]
>>> bag = RosBag('test_ros2.bag', topicfilter="camera")
!! ImportError: rosbags is required for ROS bag support. Install it with: pip install rosbags or pip install machinevision-toolbox-python[ros] [ERR unknown:21:unknown (source/ros-pytorch.rst)]

Subscribing to a ROS message stream

Publishing a ROS message

PyTorch interface

The ROS interface allows you to read images and point clouds from ROS bag files, and display them. The PyTorch interface allows you to use the toolbox’s image processing functions in PyTorch pipelines, and to convert between the toolbox’s Image class and PyTorch tensors.