Now I get the training data of 3D-coded, and make a training experiment with 1000 data. But I got a bad result. Could you tell me how to set the parameters related to SURREAL?
In the process of training, I also found that in dataset.py, the values of source_normals and target_normals were set to none, which led to the two lines of code could not run.
data["source_normals"] = torch.cat([_source_normals, _target_normals, _source_normals], dim=0).contiguous()
data["target_normals"] = torch.cat([_target_normals, _source_normals, _source_normals], dim=0).contiguous()
I think if the value passed in is none, then these two lines of code will not work, so I annotated them. What negative impact will this have on the training process?
Looking forward to your help, thx!
Now I get the training data of 3D-coded, and make a training experiment with 1000 data. But I got a bad result. Could you tell me how to set the parameters related to SURREAL?
In the process of training, I also found that in dataset.py, the values of source_normals and target_normals were set to none, which led to the two lines of code could not run.
data["source_normals"] = torch.cat([_source_normals, _target_normals, _source_normals], dim=0).contiguous()data["target_normals"] = torch.cat([_target_normals, _source_normals, _source_normals], dim=0).contiguous()I think if the value passed in is none, then these two lines of code will not work, so I annotated them. What negative impact will this have on the training process?
Looking forward to your help, thx!