  We present the largest publicly available synthetic OCR benchmark dataset for
Indic languages. The collection contains a total of 90k images and their ground
truth for 23 Indic languages. OCR model validation in Indic languages require a
good amount of diverse data to be processed in order to create a robust and
reliable model. Generating such a huge amount of data would be difficult
otherwise but with synthetic data, it becomes far easier. It can be of great
importance to fields like Computer Vision or Image Processing where once an
initial synthetic data is developed, model creation becomes easier. Generating
synthetic data comes with the flexibility to adjust its nature and environment
as and when required in order to improve the performance of the model. Accuracy
for labeled real-time data is sometimes quite expensive while accuracy for
synthetic data can be easily achieved with a good score.
