Upload README_V5.md

README_V5.md

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+# Second Stage Test by Monash — Submission V3
+
+## 1. Download the Docker Image
+
+You can download the latest Docker image from [huggingface](https://huggingface.co/datasets/JianghaoWu/MBH-Seg_monash/blob/main/monash_v5_latest.tar.gz) as `monash_v5_latest.tar.gz`.
+
+## 2. Load the Docker Image
+
+To load the Docker image, use the following command:
+
+`docker load -i monash_v5_latest.tar.gz`
+
+After loading, you will see the message: `Loaded image: monash_v5:latest`, where `monash_v5:latest` is the name of the Docker image.
+
+
+## 3. Test the Docker Image
+
+To test the Docker container, run:
+
+`docker container run --gpus "device=0" --name monash_v5 --rm --shm-size=24g -v $PWD/relative_path/test/fold/:/workspace/inputs/ -v $PWD/relative_path/outputs/fold/:/workspace/outputs/ monash_v5:latest /bin/bash -c "sh predict.sh"`
+
+
+If you encounter any permission issues, you may need to run it with `sudo`:
+
+`sudo docker container run --gpus "device=0" --name monash_v5 --rm --shm-size=24g -v $PWD/relative_path/test/fold/:/workspace/inputs/ -v $PWD/relative_path/outputs/fold/:/workspace/outputs/ monash_v5:latest /bin/bash -c "sh predict.sh"`
+
+
+### Parameters:
+- `--gpus "device=0"`: Select the appropriate GPU ID.
+- Replace `relative_path/test/fold` with the **relative path** to your test folder, which should contain Nifti files (`.nii.gz`). This path is relative to your **current working directory**.
+- Replace `relative_path/outputs/fold` with the **relative path** to your desired output folder, which will store the results. This path is also relative to your **current working directory**.
+- `monash_v5:latest`: This is the Docker image name, which will be displayed after loading the image in step 2.
+- `--shm-size=24g`: If you encounter memory issues, please increase the shared memory space, for example, --shm-size=32g.
+
+or using absolute path:
+
+`docker container run --gpus "device=0" --name monash_v5 --rm --shm-size=24g -v /absolute/path/to/your/test/fold/:/workspace/inputs/ -v /absolute/path/to/my/team/outputs/fold/:/workspace/outputs/ monash_v5:latest /bin/bash -c "sh predict.sh"`
+
+- Replace `/absolute/path/to/your/test/fold/` with the **absolute path** to your test folder, which should contain Nifti files (`.nii.gz`).
+- Replace `/absolute/path/to/my/team/outputs/fold/` with the **absolute path** to your desired output folder, where the output results will be stored.
+
+