yuanpengpeng

Hello, I use the image size 128 * 128 * 48 48 as the layer thickness, your model reports an error File "/home/yuanpeng/anaconda3/envs/python37/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, **kwargs)...

train error

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输出x的shape: torch.Size([1, 1, 304, 224, 112]) 输出y的shape: torch.Size([1, 1, 304, 224, 112]) 输出model_in的shape: torch.Size([1, 2, 304, 224, 112]) Traceback (most recent call last): File "/home/yuanpeng/Registration/Vit/ViT-V-Net/train.py", line 171, in main() File...

Hi, you can adapt the trick mentioned [here](https://github.com/MECLabTUDA/M3d-Cam/issues/13#issuecomment-911541129) to work with either multiple inputs, outputs or both. _Originally posted by @burhr2 in https://github.com/MECLabTUDA/M3d-Cam/issues/31#issuecomment-1755152607_ Is there any other way? I don’t...

Error found after running File "vgg_face.py", line 104, in im = torch.Tensor(im).permute(2, 0, 1).view(1, 3, 224, 224).double() TypeError: new(): data must be a sequence (got NoneType)

This pytorch version is to load the weight file directly, is there any training code?

Generally, when recognizing a human face, a picture is compared with a picture in the base library. Is the LFW data set you use here? Why is a picture directly...

How to convert DisplacementFieldTransform to Image format and save it?

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How to convert DisplacementFieldTransform to Image format and save it? For example, as shown below: final_transform = sitk.DisplacementFieldTransform(displacement_field) I want to save final_transform to .nii.gz format

Please tell me why I am reporting a cuda memory error when I perform data preprocessing according to your operation. Please help me. I will be grateful.

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Please tell me why I am reporting a cuda memory error when I perform data preprocessing according to your operation. Please help me. I will be grateful. (python310Tigre) yuanpeng@DESKTOP-6RR65PH:/mnt/d/谷歌下载/DIF-Net-main/DIF-Net-main/scripts$ ./test.sh...

Please tell me. I see that your data preprocessing is processed as uint8. I want to process lung data. The uint8 precision lung details will be lost. Is it okay if I save it as float32? After trying it, it seems that the GPU will overrun.

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Error reported during testing Namespace(name='dif-net', epoch=400, dst_list='knee_cbct', split='test', combine='mlp', num_views=3, view_offset=0, out_res=256, eval_npoint=100000, visualize=False) mixed_dataset: ['knee_cbct'] 输出dst_name: knee_cbct CBCT_dataset, name: knee_cbct, split: test, len: 1. load ckpt from /mnt/d/谷歌下载/DIF-Net-main/DIF-Net-main/scripts/logs/dif-net/ep_400.pth DIF_Net,...

May I ask that LiftReg-noLift3D does not need the PCA method for dimensionality reduction?

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May I ask that LiftReg-noLift3D does not need the PCA method for dimensionality reduction?