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@@ -3,12 +3,7 @@ license: apache-2.0
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  ---
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  # Instructions
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- ### 1-Download
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- Download the singularity container.
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- ```
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- wget https://huggingface.co/qicq1c/SuPreM/resolve/main/suprem_final.sif
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- ```
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- ### 2-Data preparation
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  This is how `inputs_data` organizes
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  ```
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  $inputs_data/
@@ -20,9 +15,27 @@ This is how `inputs_data` organizes
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  β”‚ └── ct.nii.gz
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  ...
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  ```
 
 
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- ### 3-Inference
 
 
 
 
 
 
 
 
 
 
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  You can directly perform inference on your own data. Simply modify `inputs_data` into your data path and adjust `outputs_data` to specify the desired output location for the segmentation results.
 
 
 
 
 
 
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  ```
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  SINGULARITYENV_CUDA_VISIBLE_DEVICES=0 singularity run --nv -B $inputs_data:/workspace/inputs -B $outputs_data:/workspace/outputs suprem_final.sif
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  ```
 
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  ---
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  # Instructions
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+ ## 1-Data preparation
 
 
 
 
 
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  This is how `inputs_data` organizes
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  ```
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  $inputs_data/
 
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  β”‚ └── ct.nii.gz
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  ...
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  ```
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+ ## 2-Download
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+ You can choose to use the docker image (recommand) or the singularity container.
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+ #### Download the docker image.
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+ ```
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+ docker pull qchen99/suprem:v1
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+ ```
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+ or
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+ #### Download the singularity container.
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+ ```
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+ wget https://huggingface.co/qicq1c/SuPreM/resolve/main/suprem_final.sif
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+ ```
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+
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+ ## 3-Inference
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  You can directly perform inference on your own data. Simply modify `inputs_data` into your data path and adjust `outputs_data` to specify the desired output location for the segmentation results.
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+ #### Use Docker
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+ ```
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+ sudo docker container run --gpus "device=0" -m 128G --rm -v $inputs_data:/workspace/inputs/ -v $outputs_data:/workspace/outputs/ qchen99/suprem:v1 /bin/bash -c "sh predict.sh"
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+ ```
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+ or
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+ #### Use Singularity
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  ```
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  SINGULARITYENV_CUDA_VISIBLE_DEVICES=0 singularity run --nv -B $inputs_data:/workspace/inputs -B $outputs_data:/workspace/outputs suprem_final.sif
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  ```