  Neural Networks and Deep Learning have seen an upsurge of research in the
past decade due to the improved results. Generates text from the given image is
a crucial task that requires the combination of both sectors which are computer
vision and natural language processing in order to understand an image and
represent it using a natural language. However existing works have all been
done on a particular lingual domain and on the same set of data. This leads to
the systems being developed to perform poorly on images that belong to specific
locales' geographical context. TextMage is a system that is capable of
understanding visual scenes that belong to the Bangladeshi geographical context
and use its knowledge to represent what it understands in Bengali. Hence, we
have trained a model on our previously developed and published dataset named
BanglaLekhaImageCaptions. This dataset contains 9,154 images along with two
annotations for each image. In order to access performance, the proposed model
has been implemented and evaluated.
