Workspace: .
configs/mvsgs/dtu_pretrain.yaml
configs/mvsgs/colmap_eval.yaml
fatal: 不是 git 仓库（或者直至挂载点 / 的任何父目录）
停止在文件系统边界（未设置 GIT_DISCOVERY_ACROSS_FILESYSTEM）。
fatal: 不是 git 仓库（或者直至挂载点 / 的任何父目录）
停止在文件系统边界（未设置 GIT_DISCOVERY_ACROSS_FILESYSTEM）。
EXP NAME: dtu_pretrain
/home/zhang/miniconda3/envs/mvsgs/lib/python3.7/site-packages/torchvision/models/_utils.py:209: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
f"The parameter '{pretrained_param}' is deprecated since 0.13 and may be removed in the future, "
/home/zhang/miniconda3/envs/mvsgs/lib/python3.7/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or None for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing weights=VGG16_Weights.IMAGENET1K_V1. You can also use weights=VGG16_Weights.DEFAULT to get the most up-to-date weights.
warnings.warn(msg)
Setting up [LPIPS] perceptual loss: trunk [vgg], v[0.1], spatial [off]
/home/zhang/miniconda3/envs/mvsgs/lib/python3.7/site-packages/torchvision/models/_utils.py:209: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
f"The parameter '{pretrained_param}' is deprecated since 0.13 and may be removed in the future, "
/home/zhang/miniconda3/envs/mvsgs/lib/python3.7/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or None for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing weights=VGG16_Weights.IMAGENET1K_V1. You can also use weights=VGG16_Weights.DEFAULT to get the most up-to-date weights.
warnings.warn(msg)
Loading model from: /home/zhang/miniconda3/envs/mvsgs/lib/python3.7/site-packages/lpips/weights/v0.1/vgg.pth
load model: ./trained_model/mvsgs/dtu_pretrain/latest.pth
Success!
已杀死
Hello, has this happened to anyone? What went wrong with the problem? How to solve this problem?
Workspace: . configs/mvsgs/dtu_pretrain.yaml configs/mvsgs/colmap_eval.yaml fatal: 不是 git 仓库（或者直至挂载点 / 的任何父目录） 停止在文件系统边界（未设置 GIT_DISCOVERY_ACROSS_FILESYSTEM）。 fatal: 不是 git 仓库（或者直至挂载点 / 的任何父目录） 停止在文件系统边界（未设置 GIT_DISCOVERY_ACROSS_FILESYSTEM）。 EXP NAME: dtu_pretrain /home/zhang/miniconda3/envs/mvsgs/lib/python3.7/site-packages/torchvision/models/_utils.py:209: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead. f"The parameter '{pretrained_param}' is deprecated since 0.13 and may be removed in the future, " /home/zhang/miniconda3/envs/mvsgs/lib/python3.7/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or
Nonefor 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passingweights=VGG16_Weights.IMAGENET1K_V1. You can also useweights=VGG16_Weights.DEFAULTto get the most up-to-date weights. warnings.warn(msg) Setting up [LPIPS] perceptual loss: trunk [vgg], v[0.1], spatial [off] /home/zhang/miniconda3/envs/mvsgs/lib/python3.7/site-packages/torchvision/models/_utils.py:209: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead. f"The parameter '{pretrained_param}' is deprecated since 0.13 and may be removed in the future, " /home/zhang/miniconda3/envs/mvsgs/lib/python3.7/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum orNonefor 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passingweights=VGG16_Weights.IMAGENET1K_V1. You can also useweights=VGG16_Weights.DEFAULTto get the most up-to-date weights. warnings.warn(msg) Loading model from: /home/zhang/miniconda3/envs/mvsgs/lib/python3.7/site-packages/lpips/weights/v0.1/vgg.pth load model: ./trained_model/mvsgs/dtu_pretrain/latest.pth Success!已杀死 Hello, has this happened to anyone? What went wrong with the problem? How to solve this problem?