ros-model-cloud

Clone the repository

The repository has to be cloned using submodules:

git clone --recursive https://github.com/ipa320/ros-model-cloud

If it has already been cloned, the submodules have to be initialized and updated:

git submodule init
git submodule update

Setup and start the web application

Using a docker container

./setup_helper.sh
docker-compose up

For the old version: https://github.com/ipa320/ros-model-cloud/tree/v1.0

Setup and start the web application

Using a docker container

Instructions on installing Docker can be found here:https://docs.docker.com/install/linux/docker-ce/ubuntu/

Build the docker image:

cd extractor-interface
[sudo] docker build --tag=haros .

Run the container:

[sudo] docker run -p 4000:4000 -ti haros:latest

Open on your browser the page: http://localhost:4000/ where the Git repository, node and package names can be set

Using a docker container on a server as a web service

[sudo] docker run -d --restart always -p 4000:4000 -ti haros:latest

where -d means in the background and --restart always that the daemon job will be automatically started if the system is rebooted.

Local testing

The app requires python 2.7 and a local installation of nodejs. It assumes that the terminal shell, in which it is started, has a source /opt/ros/<distro>/setup.bash. The setup described below has been tested on Ubuntu 16.04 with ROS Kinetic.

Install node (detailed instructions can be found here):

curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.34.0/install.sh | bash
nvm install 10

The dependencies needed for HAROS need to be set up:

[sudo] apt-get install cppcheck
[sudo] apt-get install cccc
[sudo] apt-get install libclang-3.8-dev

Additionally, install clang-3.8

[sudo] apt-get install clang-3.8

Set the LD_LIBRARY_PATH environmental variable:

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib/llvm-3.8/lib

To start the app in a virtual enviroment, install virtualenv:

sudo apt-get install python-virtualenv

Create a venv directory and install the requirements:

cd extractor-interface
virtualenv --system-site-packages -p python2.7 venv
source venv/bin/activate
pip install -r requirements.txt

Build the frontend:

npm install
npm run build

Run the app:

gunicorn -k flask_sockets.worker wsgi:app

To start the frontend in watch-mode (will rebuild automatically if one of the files in the static folder changes), run in a new terminal:

npm run watch

Open http://127.0.0.1:8000 in a browser.

All generated models will be saved in the folder extractor-interface/models. Temporary workspaces used for the extraction are created in the folder extractor-interface/workspaces.