Questions about the code

[shangbuhuan13]

ey :) I am sorry I have another question

in the recon_loss.py

res_vote = res_vote / 6 / bs

all the devisions by 6 is this because of the 6 distances paramters or is this related to the number of categories

and another question https://github.com/lolrudy/GPV_Pose/blob/5ac3307ac3af5892f09812a04621fdae415deec8/losses/recon_loss.py#L234

this line why is this not calculated for latop?

[shangbuhuan13]

and same question here how is this selected: https://github.com/lolrudy/GPV_Pose/blob/5ac3307ac3af5892f09812a04621fdae415deec8/network/GPVPose.py#L202

[lolrudy]

1. 6 is the number of the bounding box faces.
2. The category which obj_id==5 is "mug". Since the x-axis of the mug category is shifted by SPD, the ground truth of x-axis is hard to calculated. So we do not calculate the loss on x-axis for mug.
3. We follow the code of FS-Net and only imply box-cage augmentation on "bowl" and "mug". This augmentation preserves the geometry characteristics of these two categories and achieves best performance.

[HannahHaensen]

@lolrudy one question regarding that, but category 5 is the category laptop

https://github.com/lolrudy/GPV_Pose/blob/2b9afaf5c3960799afd7f554e6af3c1602f88396/datasets/load_data.py#L74

mug is category 'mug': 6 if I read it correctly

thanks in advance

[lolrudy]

The obj_id starts from 0. https://github.com/lolrudy/GPV_Pose/blob/2b9afaf5c3960799afd7f554e6af3c1602f88396/datasets/load_data.py#L264