RadeGS——添加法向量损失

`# original_normal_file = viewpoint_cam.image_name+".npy"

original_normal_dir = "/root/autodl-tmp/MoGe/output_all/"

gt_normal = np.load(original_normal_dir+original_normal_file)

gt_normal_tensor = torch.tensor(gt_normal, dtype=torch.float32, device="cuda")

gt_normal_tensor = gt_normal_tensor.permute(2, 0, 1)

gt_normal_tensor = gt_normal_tensor/gt_normal_tensor.norm(p=2, dim=1, keepdim=True)`

`# rendered_normal = rendered_normal/rendered_normal.norm(p=2, dim=1, keepdim=True)

normal_mask = render_pkg["mask"].squeeze().float()

normal_diff = torch.norm(gt_normal_tensor - rendered_normal, p=2, dim=0)

moge_normal_loss = (normal_diff*normal_mask).sum()/(normal_mask.sum()+1e-6)`

loss = rgb_loss + depth_normal_loss * lambda_depth_normal+0.2*moge_normal_loss