Dimension of Position Embedding

[HollowFire]

The original paper describes the position embedding as a 5-dimension vector which contains the coordinates of the top left and bottom right corner plus a relative area. But in the data preprocessing script (seq2seq_loader.py), the variable vis_pe, which I figure stands for the position embedding, has a dimension of 6. What causes the difference and what is the extra value used for?

[LuoweiZhou]

@HollowFire The last dimension in vis_pe stands for the confidence score of the proposal: https://github.com/LuoweiZhou/detectron-vlp/blob/master/tools/extract_features.py#L266