Rosetta: large scale system for text detection and recognition in images
Rosetta: large scale system for text detection and recognition in images Borisyuk et al., KDD’18
Rosetta is Facebook’s production system for extracting text (OCR) from uploaded images.
In the last several years, the volume of photos being uploaded to social media platforms has grown exponentially to the order of hundreds of millions every day, presenting technological challenges for processing increasing volumes of visual information… our problem can be stated as follows: to build a robust and accurate system for optical character recognition capable of processing hundreds of millions of images per day in realtime.

Images uploaded by clients are added to a distributed processing queue from which Rosetta inference machines pull jobs. Online image processing consists of the following steps:
- The image is downloaded to a local machine in the Rosette cluster and pre-processing steps such as resizing (to 800px in the larger dimension) and normalization are performed.
- A text detection model is executed to obtain bounding box coordinates and scores for all the words in the image.
- The word location information is passed to a text recognition model that extracts characters given each cropped word region from the image.
- The extracted text along with the location of the Continue reading




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