The experimental logic is inconsistent with the description in the paper

According to Eq.(3) and the γ definition in the paper, segmentation loss should be applied to negative images as well. However, the provided code (end2end.py) only applies segmentation loss when is_segmented=True, excluding negative samples even though their segmentation label is implicitly zero. This appears to contradict the definition of γ in the paper.