Using pre-trained models from lvm-med-resnet
Traceback (most recent call last):
File "train_segmentation.py", line 14, in
train_2d_R50(yml_args, cfg)
File "/root/autodl-tmp/LVM-Med/segmentation_2d/train_R50_seg_adam_optimizer_2d.py", line 224, in train_2d_R50
net = smp.Unet(encoder_name="resnet50", encoder_weights=cfg.base.original_checkpoint,
File "/root/miniconda3/envs/lvm_med/lib/python3.8/site-packages/segmentation_models_pytorch/unet/model.py", line 59, in init
self.encoder = get_encoder(
File "/root/miniconda3/envs/lvm_med/lib/python3.8/site-packages/segmentation_models_pytorch/encoders/init.py", line 38, in get_encoder
settings = encoders[name]["pretrained_settings"][weights]
KeyError: 'lvm-med-resnet
Hello!I had come across a problem as above.I don't know whether it related to source code or not.Please inform me why it happened, I'll be appreciated.
Error shows below: INFO: Using device cuda:5
Using pre-trained models from lvm-med-resnet Traceback (most recent call last): File "train_segmentation.py", line 14, in
train_2d_R50(yml_args, cfg)
File "/root/autodl-tmp/LVM-Med/segmentation_2d/train_R50_seg_adam_optimizer_2d.py", line 224, in train_2d_R50
net = smp.Unet(encoder_name="resnet50", encoder_weights=cfg.base.original_checkpoint,
File "/root/miniconda3/envs/lvm_med/lib/python3.8/site-packages/segmentation_models_pytorch/unet/model.py", line 59, in init
self.encoder = get_encoder(
File "/root/miniconda3/envs/lvm_med/lib/python3.8/site-packages/segmentation_models_pytorch/encoders/init.py", line 38, in get_encoder
settings = encoders[name]["pretrained_settings"][weights]
KeyError: 'lvm-med-resnet