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README.md
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---
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# Instructions
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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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$inputs_data/
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β βββ ct.nii.gz
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```
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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 βββ 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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## 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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```
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