Download and Installation
Picasso can be installed and used in Windows 10 and Linux (tested on Centos 5). Since Picasso is developed in Matlab (r2014a), it’s required to have Matlab with compatible version installed in your machine.
Download
Picasso project is hosted in GitHub. The source code can be easily downloaded by running the command below, if Git was installed in your local machine.
Note
Git is a very handy tool for code management and version control.
$ git clone https://github.com/PollyNET/Pollynet_Processing_Chain/
Dependencies
Since Picasso is a very powerful lidar data processing platform, including data pre-processing, lidar calibration and data visualization, etc. It relies on many dependencies for realizing these features. Below are the list of Picasso dependencies:
Python 3.6
curl
It’s recommended to use Anaconda for managing Python. Meanwhile, matplotlib is required for data visualization, but it’s pre-installed in Anaconda. And some additional Python packages are necessary for calculations and Sphinx docs. Below is the list of required Python packages:
alabaster==0.7.12
Babel==2.9.1
certifi==2021.5.30
charset-normalizer==2.0.4
colorama==0.4.4
commonmark==0.9.1
cycler==0.10.0
docutils==0.16
future==0.18.2
idna==3.2
imagesize==1.2.0
Jinja2==3.0.1
kiwisolver==1.3.1
MarkupSafe==2.0.1
matplotlib==3.3.4
numpy==1.19.5
packaging==21.0
Pillow==8.2.0
pycodestyle==2.7.0
Pygments==2.9.0
pyparsing==2.4.7
python-dateutil==2.8.1
pytz==2021.1
recommonmark==0.7.1
requests==2.26.0
rstcheck==3.3.1
scipy==1.5.4
six==1.16.0
snowballstemmer==2.1.0
Sphinx==4.1.2
sphinx-rtd-theme==0.5.2
sphinxcontrib-applehelp==1.0.2
sphinxcontrib-devhelp==1.0.2
sphinxcontrib-htmlhelp==2.0.0
sphinxcontrib-jsmath==1.0.1
sphinxcontrib-matlabdomain==0.12.0
sphinxcontrib-qthelp==1.0.3
sphinxcontrib-serializinghtml==1.1.5
urllib3==1.26.6
wincertstore==0.2
To get all packages ready at once you can also import the python environment via the ‘picasso.yaml’ file.
SQLite is necessary for saving lidar calibration results. The Java connector has been provided in the folder of ./include. But it needs to restart Matlab to activate this Java connector.
NOTE: one has to run addSQLiteJDBC(‘path_tosqlite-jdbc-3.30.1.jar’) once!