SwinMM/Initialize the SwinMM project

SwinMM/INSTALL.md

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+# Installation
+
+We provide installation instructions here.
+
+## Setup
+
+### Using Docker
+
+The simplest way to use SwinMM is to use our docker image [`swinmm`](https://drive.google.com/file/d/1EGSoqN-HphyMV_gKUq-g7_BSwTTg35oA/view?usp=sharing), which has contained all the needed dependencies. Download the `swinmm.tar` into the `SwinMM` directory and try the following scripts:
+
+```bash
+cd SwinMM
+docker import - swinmm < swinmm.tar
+docker run --runtime=nvidia --gpus=all -m="800g" --shm-size="32g" -itd -v ./:/volume swinmm /bin/bash
+docker exec -it swinmm /bin/bash
+conda activate SwinMM
+```
+
+To use docker, make sure you have installed `docker` and `nvidia-docker`.
+
+### Manual
+
+For fast dataset loading, we required the users to install the Redis database, for example, on Ubuntu: `sudo apt-get install redis`
+
+We also recommend the users install the PyTorch-based version from the official website.
+
+Two packages are recommended to install manually according to their complicated dependencies: [bagua==0.9.2](https://github.com/BaguaSys/bagua), [monai==0.9.0](https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies)
+
+The others can be installed through `pip install -r requirements.txt`
+
+## Datasets
+
+Our pre-training dataset includes 5833 volumes from 8 public datasets:
+
+- [AbdomenCT-1K](https://github.com/JunMa11/AbdomenCT-1K)
+- [BTCV](https://www.synapse.org/#!Synapse:syn3193805/wiki/217789)
+- [MSD](http://medicaldecathlon.com/)
+- [TCIACovid19](https://wiki.cancerimagingarchive.net/display/Public/CT+Images+in+COVID-19/)
+- [WORD](https://github.com/HiLab-git/WORD)
+- [TCIA-Colon](https://wiki.cancerimagingarchive.net/display/Public/CT+COLONOGRAPHY/)
+- [LiDC](https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI/)
+- [HNSCC](https://wiki.cancerimagingarchive.net/display/Public/HNSCC)
+
+We choose two popular datasets to test the downstream segmentation performance:
+
+- [WORD](https://github.com/HiLab-git/WORD) (The Whole abdominal Organ Dataset)
+- [ACDC](https://www.creatis.insa-lyon.fr/Challenge/acdc/#challenge/584e75606a3c77492fe91bba) (Automated Cardiac Diagnosis Challenge)
+
+The dataset is organized as below:
+
+```text
+SwinMM
+├── WORD
+│   └── dataset
+│       └── dataset12_WORD
+│           ├── imagesTr
+│           ├── imagesTs
+│           ├── imagesVal
+│           ├── labelsTr
+│           ├── labelsTs
+│           ├── labelsVal
+│           └── dataset12_WORD.json
+└── Pretrain
+    ├── dataset
+    │   ├── dataset00_BTCV
+    │   ├── dataset02_Heart
+    │   ├── dataset03_Liver
+    │   ├── dataset04_Hippocampus
+    │   ├── dataset06_Lung
+    │   ├── dataset07_Pancreas
+    │   ├── dataset08_HepaticVessel
+    │   ├── dataset09_Spleen
+    │   ├── dataset10_Colon
+    │   ├── dataset11_TCIAcovid19
+    │   ├── dataset12_WORD
+    │   ├── dataset13_AbdomenCT-1K
+    │   ├── dataset_HNSCC
+    │   ├── dataset_TCIAcolon
+    │   └── dataset_LIDC
+    └── jsons
+        ├── dataset00_BTCV.json
+        ├── dataset01_BrainTumour.json
+        ├── dataset02_Heart.json
+        ├── dataset03_Liver.json
+        ├── dataset04_Hippocampus.json
+        ├── dataset05_Prostate.json
+        ├── dataset06_Lung.json
+        ├── dataset07_Pancreas.json
+        ├── dataset08_HepaticVessel.json
+        ├── dataset09_Spleen.json
+        ├── dataset10_Colon.json
+        ├── dataset11_TCIAcovid19.json
+        ├── dataset12_WORD.json
+        ├── dataset13_AbdomenCT-1K.json
+        ├── dataset_HNSCC.json
+        ├── dataset_TCIAcolon.json
+        └── dataset_LIDC.json
+
+```

SwinMM/Pretrain/jsons/dataset00_BTCV.json

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+{
+    "training": [
+        {
+            "image": "imagesTr/img0001.nii.gz",
+            "label": "labelsTr/label0001.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0002.nii.gz",
+            "label": "labelsTr/label0002.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0003.nii.gz",
+            "label": "labelsTr/label0003.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0004.nii.gz",
+            "label": "labelsTr/label0004.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0005.nii.gz",
+            "label": "labelsTr/label0005.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0006.nii.gz",
+            "label": "labelsTr/label0006.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0007.nii.gz",
+            "label": "labelsTr/label0007.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0008.nii.gz",
+            "label": "labelsTr/label0008.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0009.nii.gz",
+            "label": "labelsTr/label0009.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0010.nii.gz",
+            "label": "labelsTr/label0010.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0021.nii.gz",
+            "label": "labelsTr/label0021.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0022.nii.gz",
+            "label": "labelsTr/label0022.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0023.nii.gz",
+            "label": "labelsTr/label0023.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0024.nii.gz",
+            "label": "labelsTr/label0024.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0025.nii.gz",
+            "label": "labelsTr/label0025.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0026.nii.gz",
+            "label": "labelsTr/label0026.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0027.nii.gz",
+            "label": "labelsTr/label0027.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0028.nii.gz",
+            "label": "labelsTr/label0028.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0029.nii.gz",
+            "label": "labelsTr/label0029.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0030.nii.gz",
+            "label": "labelsTr/label0030.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0031.nii.gz",
+            "label": "labelsTr/label0031.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0032.nii.gz",
+            "label": "labelsTr/label0032.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0033.nii.gz",
+            "label": "labelsTr/label0033.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0034.nii.gz",
+            "label": "labelsTr/label0034.nii.gz"
+        }
+    ],
+    "validation": [
+        {
+            "image": "imagesTr/img0035.nii.gz",
+            "label": "labelsTr/label0035.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0036.nii.gz",
+            "label": "labelsTr/label0036.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0037.nii.gz",
+            "label": "labelsTr/label0037.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0038.nii.gz",
+            "label": "labelsTr/label0038.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0039.nii.gz",
+            "label": "labelsTr/label0039.nii.gz"
+        },
+        {
+            "image": "imagesTr/img0040.nii.gz",
+            "label": "labelsTr/label0040.nii.gz"
+        }
+    ]
+}