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*PRF photometry with Kepler*
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<a href="https://github.com/ssdatalab/psfmachine/workflows/tests.yml">
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<img src="https://github.com/ssdatalab/psfmachine/workflows/pytest/badge.svg" alt="Test status"/>
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</a> <a href="https://pypi.python.org/pypi/tess-ephem"><img src="https://img.shields.io/pypi/v/tess-ephem", alt="pypi status"></a>
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<a href="https://github.com/ssdatalab/psfmachine/workflows/tests.yml"><img src="https://github.com/ssdatalab/psfmachine/workflows/pytest/badge.svg" alt="Test status"/></a>
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<a href="https://pypi.python.org/pypi/tess-ephem"><img src="https://img.shields.io/pypi/v/tess-ephem" alt="pypi status"></a>
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<a href="https://zenodo.org/record/4784073"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.4784073.svg"></a>
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`PSFMachine` is an open source Python tool for creating models of instrument effective Point Spread Functions (ePSFs), a.k.a Pixel Response Functions (PRFs). These models are then used to fit a scene in a stack of astronomical images. `PSFMachine` is able to quickly derive photometry from stacks of *Kepler* images and separate crowded sources.
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