  We present a catalogue of 16551 edge-on galaxies created using the public DR2
data of the Pan-STARRS survey. The catalogue covers the three quarters of the
sky above Dec.=-30 degrees. The galaxies were selected using a convolutional
neural network, trained on a sample of edge-on galaxies identified earlier in
the SDSS survey. This approach allows us to dramatically improve the quality of
the candidate selection and perform a thorough visual inspection in a
reasonable amount of time. The catalogue provides homogeneous information on
astrometry, SExtractor photometry, and non-parametric morphological statistics
of the galaxies. The photometry is reliably for objects in the 13.8-17.4 r-band
magnitude range. According to the HyperLeda database, redshifts are known for
about 63 percent of the galaxies in the catalogue. Our sample is well separated
into the red sequence and blue cloud galaxy populations. The edge-on galaxies
of the red sequence are systematically Delta(g-i)~0.1 mag redder than galaxies
oriented at an arbitrary angle to the observer. We found a variation of the
galaxy thickness with the galaxy colour. The red sequence galaxies are thicker
than the galaxies of the blue cloud. In the blue cloud, on average, thinner
galaxies turn out to be bluer. In the future, based on this catalogue it is
intended to explore the three-dimensional structure of galaxies of different
morphologies, as well as to study the scaling relations for discs and bulges.
