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lcopt-cv

lcopt-cv: Create fully functional LCA models from hand drawn pictures of process diagrams

Lcopt-cv is a python module for creating LCA foreground models from hand drawn pictures of process flow diagrams developed by James Joyce

Pretty much every LCA starts with drawing a process flow diagram. The difficult bit is turning that diagram into an LCA model which can be analysed.

What if you could just take a picture of the diagram you've just drawn and have it instantly turned into an LCA model?

Well now you can - introducing lcopt-cv, computer vision for LCA.

lcopt-cv workflow

Features

Installation


NOTE

lcopt-cv requires the lcopt and brightway2 packages to be installed, and for lcopt to be set up with ecoinvent 3.3 cutoff


The best way to install lcopt-cv is to use the conda package. The command is

conda install -y -q -c conda-forge -c cmutel -c haasad -c pjamesjoyce lcopt-cv

One additional dependency isn't available as a conda package and needs to be installed separately using pip. Here is the command

pip install opencv-python

If you already had lcopt installed and set up - that's it. If not you need to set up lcopt to talk to brightway.

Full instructions on how to do this are in the lcopt documentation

The short version is

lcopt-bw2-setup path/to/ecospold/files # use "" if there are spaces in your path

This will generate the lcopt template databases in brightway2 so that you can analyse your LCA models.

Use

To launch lcopt-cv at the command line type:

lcopt-cv

This will launch the lcopt-cv GUI.

lcopt-cv gui

More detailed documentation is available in the online documentation