Add Docker and devcontainer

.devcontainer/Dockerfile

@@ -0,0 +1,40 @@
+FROM nvidia/cuda:12.2.2-base-ubuntu20.04
+
+ARG USERNAME=ubuntu
+ARG USER_UID=1000
+ARG USER_GID=$USER_UID
+ARG DEBIAN_FRONTEND=noninteractive
+
+ENV TERM=xterm-256color
+ENV TZ=Europe/Paris
+ENV LANG=en_US.UTF-8
+ENV SHELL=/bin/bash
+
+RUN groupadd --gid $USER_GID $USERNAME \
+    && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME \
+    && apt-get update \
+    && apt-get install -y sudo \
+    && echo $USERNAME ALL=\(root\) NOPASSWD:ALL > /etc/sudoers.d/$USERNAME \
+    && chmod 0440 /etc/sudoers.d/$USERNAME
+
+# Install language
+RUN apt-get update && apt-get install -y \
+  locales \
+  && locale-gen en_US.UTF-8 \
+  && update-locale LC_ALL=en_US.UTF-8 LANG=en_US.UTF-8 \
+  && rm -rf /var/lib/apt/lists/*
+
+# Install packages
+RUN apt update && apt install -y \
+    git \
+    tmux \
+    python3-pip
+
+# Set python as python3
+RUN ln -s /usr/bin/python3 /usr/bin/python
+
+# Install pytorch
+RUN pip3 install torch==1.8.1 torchvision==0.9.1
+
+USER $USERNAME
+CMD ["/bin/bash", "-l"]

.devcontainer/devcontainer.json

@@ -0,0 +1,25 @@
+{
+	"name": "WaSR-T",
+	"build": { "dockerfile": "Dockerfile" },
+	"runArgs": [
+		"--net", "host",
+		"--privileged",
+		"--gpus", "all",
+		"--shm-size", "16g"
+  	],
+	"containerEnv": {
+        "DISPLAY": "${localEnv:DISPLAY}"
+    },
+	"mounts": [
+        "source=/tmp/.X11-unix,target=/tmp/.X11-unix,type=bind,consistency=cached"
+	],
+	"customizations": {
+		"vscode": {
+			"extensions": [
+				"ms-python.python",
+				"ms-vscode.cpptools-extension-pack"
+			]
+		}
+	},
+	"postCreateCommand": "pip install -r /workspaces/WaSR-T/requirements.txt"
+}

.gitignore

@@ -7,4 +7,5 @@ __pycache__/
 venv/
 
 # Project specific
-/output/
+/output/
+/dataset/

README.md

@@ -36,6 +36,14 @@ The required Python libraries can be installed using the following pip command
 pip install -r requirements.txt
 ```
 
+<details> 
+  <summary> :whale: <b>Docker</b> </summary>
+
+   To use Docker along GPU, you might need to install [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html).
+   Now using [devcontainers extension](https://code.visualstudio.com/docs/devcontainers/tutorial) for vscode, you will be able to open the project automaticly in a Docker container.
+</details>
+
+
 ## Usage
 
 The WaSR-T model used in our experiments (ResNet-101 backbone) can be initialized with the following code.

requirements.txt

@@ -4,3 +4,4 @@ pytorch-lightning==1.4.4
 torchmetrics==0.5.0
 tqdm
 albumentations
+six