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I checked the code and found that the pearson loss is not used at all:
def pearson_depth_loss(depth_src, depth_target):
#co = pearson(depth_src.reshape(-1), depth_target.reshape(-1))
src = depth_src - depth_src.mean()
target = depth_target - depth_target.mean()
src = src / (src.std() + 1e-6)
target = target / (target.std() + 1e-6)
co = (src * target).mean()
assert not torch.any(torch.isnan(co))
return 1 - co
Is there something I missed? Thanks!
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