lsst.meas.transiNet

meas_transiNet provides a PipelineTask interface for the TransiNet machine learning real/bogus classification package.

Contributing

lsst.meas.transiNet is developed at https://github.com/lsst/meas_transiNet. You can find Jira issues for this module under the meas_transiNet component.

Python API reference

lsst.meas.transiNet Package

Classes

CutoutInputs(*, science, template, difference)	Science/template/difference cutouts of a single object plus other metadata.
RBTransiNetConfig(*args, **kw)
RBTransiNetInterface(task[, device])	The interface between the LSST AP pipeline and a trained pytorch-based RBTransiNet neural network model.
RBTransiNetTask(**kwargs)	Task for running TransiNet real/bogus classification on the output of the image subtraction pipeline.