TransUNet
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This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.
I am looking at your code and found some problems https://github.com/Beckschen/TransUNet/blob/main/networks/vit_seg_modeling.py#L133 patch_size = (img_size[0] // 16 // grid_size[0], img_size[1] // 16 // grid_size[1]) The training image size is 224 then...
Thank you for your excellent work. I am working on 2d image segmentation. I have some doubt about how to resize the images and masks. Should I simply use bilinear...
Hi, Thanks a lot for sharing your code. I have a question regarding the computation of the evaluation metrics. Your code is: ``` def calculate_metric_percase(pred, gt): pred[pred > 0] =...
Thanks for this terrific repository! Your results are impressive! I notice that the Synapse data is not normalized to between 0 and 1 but instead I'm getting the following values...
Very impressive works. I trying to use the transUnet in my dataset. But my dataset shape is (672,448) which length and width not equal. I find this will lead bugs....
Thanks for your excellent work. While I try to make my own dataset, I meet some troubles. My first question is that what the dimensions of "image" and "label" in...
The model does not scale on multiple GPU units on a single CPU. It create multiple copies of model (when using distributed data parallel) and add all the load to...
Thanks for your work. I have some questions about the patch size of patch embedding when using CNN and Transformer as the encoder. In the section 3.2 of the paper,...
 What kind of file is in the red place? I didn’t understand it. The error is also because of the path problem.