  A significant number of images shared on social media platforms such as
Facebook and Instagram contain text in various forms. It's increasingly
becoming commonplace for bad actors to share misinformation, hate speech or
other kinds of harmful content as text overlaid on images on such platforms. A
scene-text understanding system should hence be able to handle text in various
orientations that the adversary might use. Moreover, such a system can be
incorporated into screen readers used to aid the visually impaired. In this
work, we extend the scene-text extraction system at Facebook, Rosetta, to
efficiently handle text in various orientations. Specifically, we incorporate
the Rotation Region Proposal Networks (RRPN) in our text extraction pipeline
and offer practical suggestions for building and deploying a model for
detecting and recognizing text in arbitrary orientations efficiently.
Experimental results show a significant improvement on detecting rotated text.
