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+# MLCube for 3D Unet
+
+MLCube™ GitHub [repository](https://github.com/mlcommons/mlcube). MLCube™ [wiki](https://mlcommons.github.io/mlcube/).
+
+## Project setup
+
+An important requirement is that you must have Docker installed.
+
+```bash
+# Create Python environment and install MLCube Docker runner 
+virtualenv -p python3 ./env && source ./env/bin/activate && pip install mlcube-docker
+# Fetch the implementation from GitHub
+git clone https://github.com/mlcommons/training && cd ./training/image_segmentation/pytorch/mlcube
+```
+
+Inside the mlcube directory run the following command to check implemented tasks.
+
+```shell
+mlcube describe
+```
+
+### MLCube tasks
+
+Download dataset.
+
+```shell
+mlcube run --task=download_data -Pdocker.build_strategy=always
+```
+
+Process dataset.
+
+```shell
+mlcube run --task=process_data -Pdocker.build_strategy=always
+```
+
+Train SSD.
+
+```shell
+mlcube run --task=train -Pdocker.build_strategy=always
+```
+
+### Execute the complete pipeline
+
+You can execute the complete pipeline with one single command.
+
+```shell
+mlcube run --task=download_data,process_data,train -Pdocker.build_strategy=always
+```
+
+## Run a quick demo
+
+You can run a quick demo that first downloads a tiny dataset and then executes a short training workload.
+
+```shell
+mlcube run --task=download_demo,demo -Pdocker.build_strategy=always
+```