Localization consistency loss in csd.py

[lianqing11]

Hi author,
Thanks for your wonderful work and your released code. I am confused about the code for the Localization consistency loss in https://github.com/soo89/CSD-SSD/blob/30b184c86a87b0fc2d301cd8157b11d8cfe7da1e/train_csd.py#L297.

consistency_loc_loss_x = torch.mean(torch.pow(loc_sampled[:, 0] + loc_sampled_flip[:, 0], exponent=2))
  
consistency_loc_loss_y = torch.mean(torch.pow(loc_sampled[:, 1] - loc_sampled_flip[:, 1], exponent=2))
                
consistency_loc_loss_w = torch.mean(torch.pow(loc_sampled[:, 2] - loc_sampled_flip[:, 2], exponent=2))
                
consistency_loc_loss_h = torch.mean(torch.pow(loc_sampled[:, 3] - loc_sampled_flip[:, 3], exponent=2))

For y, w, and h you use '-' when calculating the mean squared loss. I am confused about why you use '+' for x when calculating the mean squared loss.

[soo89]

check equation (3) in our paper.

(https://papers.nips.cc/paper/9259-consistency-based-semi-supervised-learning-for-object-detection)

[ChenZiLiangSSS]

thanks for your great research. I have a question that after flipping x becomes -x, does it mean the coordinate center is the center of picture not top left corner？thank you!