Polyp_Base Computer Vision Project

Hyper_Kvasir dataset segmented image part, annotated in YOLO format. Suitable to train object detection models. if you use this dataset than cite the orignal paper of this dataset

@article{Borgli2020, author = { Borgli, Hanna and Thambawita, Vajira and Smedsrud, Pia H and Hicks, Steven and Jha, Debesh and Eskeland, Sigrun L and Randel, Kristin Ranheim and Pogorelov, Konstantin and Lux, Mathias and Nguyen, Duc Tien Dang and Johansen, Dag and Griwodz, Carsten and Stensland, H{\aa}kon K and Garcia-Ceja, Enrique and Schmidt, Peter T and Hammer, Hugo L and Riegler, Michael A and Halvorsen, P{\aa}l and de Lange, Thomas }, doi = {10.1038/s41597-020-00622-y}, issn = {2052-4463}, journal = {Scientific Data}, number = {1}, pages = {283}, title = {{HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy}}, url = {https://doi.org/10.1038/s41597-020-00622-y}, volume = {7}, year = {2020} }