  Deep learning based neural networks have gained popularity for a variety of
biomedical imaging applications. In the last few years several works have shown
the use of these methods for colon cancer detection and the early results have
been promising. These methods can potentially be utilized to assist doctor's
and may help in identifying the number of lesions or abnormalities in a
diagnosis session. From our literature survey we found out that there is a lack
of publicly available labeled data. Thus, as part of this work, we have aimed
at open sourcing a dataset which contains annotations of polyps and ulcers.
This is the first dataset that's coming from India containing polyp and ulcer
images. The dataset can be used for detection and classification tasks. We also
evaluated our dataset with several popular deep learning object detection
models that's trained on large publicly available datasets and found out
empirically that the model trained on one dataset works well on our dataset
that has data being captured in a different acquisition device.
