How to run Machine Learning (PyTorch, Tensorflow) with ROS Melodic/Python 2.7?

• dotmask

  2 26 0.0 Python
  

Do you have all your Python 3 files in a different workspace with cv_bridge? In the tutorial you shared they create a new catkin_build_ws to avoid any future problems with catkin_make? How would I compile my existing c++ files when I make changes? The steps of the tutorial seem very similar to the ones at the start of this repo: https://github.com/introlab/dotmask. In the repo, however, they use catkin_make instead of catkin build with the following arguments:

• ros-semantic-segmentation-pytorch

  1 10 0.0 Python

  Pytorch implementation of Semantic Segmentation in ROS on MIT ADE20K dataset based on semantic-segmentation-pytorch by CSAIL

As an example, this repo (https://github.com/pranay731/ros-semantic-segmentation-pytorch) seems to simply install ROS Melodic normally and some python 3 dependencies:

• InfluxDB

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  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• ur_openai_gym

  1 15 2.5 Python

  OpenAI Gym interface for Universal Robots with ROS Gazebo

I've been able to work with tensorflow 2 and Ros melodic here https://github.com/cambel/ur_openai_gym I use dockers because it makes it easy to use. Compiling your custom packages with python3 and the rest mostly works fine. I had troubles with tf but I found a work around it. Though working with docket and Ros noetic would be a better idea.

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