Recently we had an issue to use this repository as the dependency on deeplabcut crashed our mac workflow (we think this might be related to the context of the following issue https://github.com/DeepLabCut/DeepLabCut/pull/1430). While using state of the art deep learning libraries is a necessity for performing the powerful analysis that deeplabcut enables they are also know to have brittle installation process and introduce hard dependency management problems in the ecosystem. In that context, we think it might be useful to enable this repository to work as stand-alone post-processing tool on itself. That is, running a conversion pipeline in an environment that does not have deeplabcut as a dependency.
Two illustrate this need more concretely, consider the two following scenarios:
A research runs the deeplabcut processing pipeline in a workstation machine but then runs the data analysis or paper writing in another computer and wants to modify the writing-to-nwb pipeline quickly.
A researcher gets the deeplabcut data from a collaborator and is going to integrate this data in a pipeline that includes other modalities but does not have the environment where the initial analysis was carried out.
In the cases above, the results are already produced and this library role would be just transforming the data into nwb. Therefore, installing deeplabcut in those scenarios is unnecessary and, as discussed above, might be brittle.
I am opening an accompanying PR that achieves this with minimal changes.
Recently we had an issue to use this repository as the dependency on
deeplabcutcrashed our mac workflow (we think this might be related to the context of the following issue https://github.com/DeepLabCut/DeepLabCut/pull/1430). While using state of the art deep learning libraries is a necessity for performing the powerful analysis thatdeeplabcutenables they are also know to have brittle installation process and introduce hard dependency management problems in the ecosystem. In that context, we think it might be useful to enable this repository to work as stand-alone post-processing tool on itself. That is, running a conversion pipeline in an environment that does not havedeeplabcutas a dependency.Two illustrate this need more concretely, consider the two following scenarios:
deeplabcutprocessing pipeline in a workstation machine but then runs the data analysis or paper writing in another computer and wants to modify the writing-to-nwb pipeline quickly.deeplabcutdata from a collaborator and is going to integrate this data in a pipeline that includes other modalities but does not have the environment where the initial analysis was carried out.In the cases above, the results are already produced and this library role would be just transforming the data into nwb. Therefore, installing
deeplabcutin those scenarios is unnecessary and, as discussed above, might be brittle.I am opening an accompanying PR that achieves this with minimal changes.