 Tensorpacks Cascade-RCNN with FPN and Group Normalization on ResNext32xd4-50 trained on Pubtabnet for Semantic Segmentation of tables. 
 
 The model and its training code has been mainly taken from: [Tensorpack](https://github.com/tensorpack/tensorpack/tree/master/examples/FasterRCNN) . 
 
 Regarding the dataset, please check: [Xu Zhong et. all. - Image-based table recognition: data, model, and evaluation](https://arxiv.org/abs/1911.10683). 
 
 The model has been trained on detecting rows and columns for tables. As rows and column bounding boxes are not a priori an element of the annotations they are
 calculated using the bounding boxes of the cells and the intrinsic structure of the enclosed HTML.
 
 The code has been adapted so that it can be used in a **deep**doctection pipeline. 
 
 