  Ocular conditions are a global concern and computational tools utilizing
retinal fundus color photographs can aid in routine screening and management.
Obtaining comprehensive and sufficiently sized datasets, however, is
non-trivial for the intricate retinal fundus, which exhibits heterogeneities
within pathologies, in addition to variations from demographics and
acquisition. Moreover, retinal fundus datasets in the public space suffer
fragmentation in the organization of data and definition of a healthy
observation. We present Integrated Retinal Fundus Set (IRFundusSet), a dataset
that consolidates, harmonizes and curates several public datasets, facilitating
their consumption as a unified whole and with a consistent is_normal label.
IRFundusSet comprises a Python package that automates harmonization and avails
a dataset object in line with the PyTorch approach. Moreover, images are
physically reviewed and a new is_normal label is annotated for a consistent
definition of a healthy observation. Ten public datasets are initially
considered with a total of 46064 images, of which 25406 are curated for a new
is_normal label and 3515 are deemed healthy across the sources.
