Docker Setup

README.md

@@ -87,6 +87,46 @@ pip install -r requirements.txt
 </code></pre>
 </details>
 
+<details>
+<summary>Docker-Based Setup</summary>
+You can build with Docker which reduces the discrepencies between systems and standarizes it into one container.
+
+If you are on a Debian-based setup (Ubuntu, Debian, etc...), ensure you have installed:
+
+<pre><code>sudo apt-get install -y nvidia-container-toolkit</code></pre>
+If you come accross any issue, follow the instructions under the <a href="https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html">official NVIDIA Guide.</a>
+
+If you are on a Windows-based setup, follow these <a href="https://docs.docker.com/desktop/features/gpu/">instuctions</a> to use your NVIDIA GPU in Docker.
+
+
+Then, to build and run the Docker container:
+```bash
+cd docker # Execute this from the root directory of the project
+./run_docker.sh -h    # Display help and usage instructions
+./run_docker.sh -bu   # Build the Docker image and launch the container with docker-compose
+```
+
+### Additional Docker Notes
+
+> Ensure you specify your GPU architecture under the `TORCH_CUDA_ARCH_LIST` variable in the Dockerfile. This is necessary for proper and optimized compilation of CUDA-based libraries. For example, if your GPU architecture is 8.6, update the Dockerfile as follows:
+
+```dockerfile
+ENV TORCH_CUDA_ARCH_LIST="8.6"
+```
+
+Refer to [NVIDIA's CUDA GPU support matrix](https://developer.nvidia.com/cuda-gpus) to find the correct architecture for your GPU.
+
+#### Accessing the Project Inside the Container
+
+After starting the Docker container, navigate to the project directory inside the container:
+
+```bash
+cd projects/on-the-fly-nvs
+```
+
+Enjoy using the project as if it was on your local machine!
+</details>
+
 <details>
 <summary>Installing CUDA within a Conda Environment</summary>
 If <code>nvcc --version</code> returns an error, you can install CUDA within your Conda environment. 
@@ -106,6 +146,7 @@ conda activate &lt;env_path&gt;/onthefly_nvs
 Where <code>&lt;pkg_path&gt;</code> is the desired package download location and <code>&lt;env_path&gt;/onthefly_nvs</code> is the desired environment location.
 </details>
 
+
 ## Data Guidelines
 > Please note that our method **is not a drop-in replacement for COLMAP + 3DGS, as it does not reorder images**. We require sequential capture that implies several constraints on the kind of data that can be handled. Please follow the **[Capture Guidelines](#capture-guidelines) for best results on your own data.**
 

docker/Dockerfile

@@ -0,0 +1,79 @@
+FROM nvidia/cuda:12.8.0-devel-ubuntu24.04
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+# --- Base packages
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    build-essential \
+    curl \
+    git \
+    ca-certificates \
+    gnupg2 \
+    lsb-release \
+    locales \
+    python3 \
+    python3-pip \
+    python3-full \
+    python3-dev \
+    sudo \
+    x11-apps \
+    zenity \
+    openssh-client \
+    && apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# --- Python requirements
+COPY ./docker/requirements-docker.txt requirements.txt
+COPY ./submodules submodules
+
+RUN pip install --no-cache-dir --break-system-packages torch torchvision xformers --index-url https://download.pytorch.org/whl/cu128
+RUN pip install --no-cache-dir --break-system-packages cupy-cuda12x
+
+# === IMPORTANT: Set this to match your GPU Architecture ===
+ENV TORCH_CUDA_ARCH_LIST="8.6" 
+RUN pip install --no-cache-dir --break-system-packages --ignore-installed -r requirements.txt
+
+# --- User Setup
+ARG USER_UID
+ARG USER_GID
+ARG USERNAME
+
+RUN set -eux; \
+# Remove user with same UID if exists
+EXISTING_USER_BY_UID=$(getent passwd "${USER_UID}" | cut -d: -f1 || true); \
+if [ -n "$EXISTING_USER_BY_UID" ]; then \
+userdel -r "$EXISTING_USER_BY_UID" || true; \
+fi; \
+\
+# Remove user with same name if exists
+if id "${USERNAME}" >/dev/null 2>&1; then \
+userdel -r "${USERNAME}" || true; \
+fi; \
+\
+# Remove group with same GID if exists
+if getent group "${USER_GID}" >/dev/null; then \
+groupdel "$(getent group "${USER_GID}" | cut -d: -f1)"; \
+fi; \
+\
+# Remove group with same name if exists
+if getent group "${USERNAME}" >/dev/null; then \
+groupdel "${USERNAME}"; \
+fi; \
+\
+# Now create group and user cleanly
+groupadd --gid "${USER_GID}" "${USERNAME}"; \
+useradd -m -u "${USER_UID}" -g "${USER_GID}" "${USERNAME}"; \
+usermod -aG sudo "${USERNAME}"; \
+echo "${USERNAME} ALL=(ALL) NOPASSWD:ALL" >> /etc/sudoers
+
+# --- Include this last to avoid cache invalidation
+WORKDIR /
+
+# No clue why this is needed, but it is
+# Otherwise, build of submodules/diff-gaussian-rasterization fails
+RUN sed -i '1i#include <stdint.h>\n#include <cstdint>' submodules/diff-gaussian-rasterization/cuda_rasterizer/rasterizer_impl.h
+RUN pip install --no-cache-dir --break-system-packages submodules/diff-gaussian-rasterization
+
+# Set environment
+ENV USER=${USERNAME}
+ENV HOME=/home/${USERNAME}
+WORKDIR /home/${USERNAME}

docker/docker-compose.yml

@@ -0,0 +1,47 @@
+services:
+  otf-nvs:
+    container_name: otf-nvs
+    entrypoint: /bin/bash
+    build:
+      context: ../
+      dockerfile: ${DOCKERFILE}
+      args:
+        USER_UID: ${USER_UID}
+        USER_GID: ${USER_GID}
+        USERNAME: ${USERNAME}
+        HOSTNAME: ${HOSTNAME}
+        USER_PASSWORD: ${USER_PASSWORD}
+    image: otf-nvs
+    network_mode: "host"
+    working_dir: /home/${USERNAME}
+    cpus: 8
+    mem_limit: 16g
+    ipc: host
+    pid: host
+    privileged: true
+    user: "${USERNAME}:${USER_GID}"
+    hostname: ${HOSTNAME}
+    stdin_open: true
+    tty: true
+    runtime: nvidia
+    environment:
+      - USER_UID=${USER_UID}
+      - USER_GID=${USER_GID}
+      - USERNAME=${USERNAME}
+      - DISPLAY=unix${DISPLAY}
+      - XAUTHORITY=${XAUTHORITY}
+      - SSH_AUTH_SOCK=${SSH_AUTH_SOCK}
+      - NVIDIA_VISIBLE_DEVICES=all
+      - NVIDIA_DRIVER_CAPABILITIES=all
+    volumes:
+      - ../:/home/${USERNAME}/projects/on-the-fly-nvs
+      - /tmp/.X11-unix:/tmp/.X11-unix:rw
+      - ${HOME}/.Xauthority:/home/${USERNAME}/.Xauthority:rw
+      - ${HOME}/.ssh:/home/${USERNAME}/.ssh:ro
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: all
+              capabilities: [ gpu ]

docker/requirements-docker.txt

@@ -0,0 +1,7 @@
+plyfile
+tqdm
+opencv-python
+lpips
+submodules/fused-ssim
+submodules/simple-knn
+submodules/graphdecoviewer

docker/run_docker.sh

@@ -0,0 +1,62 @@
+#!/bin/bash
+
+usage() {
+    echo "Usage: $0 [-h] [-b] [-n] [-u] [-c] [-j | -f]"
+    echo " -h    Show this help message"
+    echo " -b    Build with cache"
+    echo " -n    Build without cache"
+    echo " -u    Start docker-compose and enter container"
+    echo " -c    Stop and clean up"
+}
+
+if [ "$#" -lt 1 ]; then
+    usage
+    exit 1
+fi
+
+# Default to Jazzy
+DOCKERFILE="docker/Dockerfile"
+BUILD=false
+BUILD_ARGS=""
+COMPOSEUP=false
+
+while getopts "hbnuc" opt; do
+    case ${opt} in
+        h ) usage; exit 0 ;;
+        b ) BUILD=true ;;
+        n ) BUILD=true; BUILD_ARGS="--no-cache" ;;
+        u ) COMPOSEUP=true ;;
+        c ) docker compose down --remove-orphans; exit 0 ;;
+        * ) usage; exit 1 ;;
+    esac
+done
+
+export USER_UID=$(id -u)
+export USER_GID=$(id -g)
+export USERNAME=$(id -un)
+export USER_PASSWORD=${USERNAME}
+export HOSTNAME=$(hostname)
+export HOME=$HOME
+export DISPLAY=$DISPLAY
+export XAUTHORITY=$XAUTHORITY
+export SSH_AUTH_SOCK=$SSH_AUTH_SOCK
+export DOCKERFILE  # Needed by docker-compose
+
+if [ "$BUILD" = true ]; then
+    echo -e "Building docker image with \033[0;31m$DOCKERFILE\033[0m..."
+    DOCKER_BUILDKIT=1 docker compose build $BUILD_ARGS
+    if [ "$?" -ne 0 ]; then
+        echo "Docker build failed!"
+        exit 1
+    fi
+fi
+
+if [ "$COMPOSEUP" = true ]; then
+    echo "Starting docker container..."
+    docker compose up -d
+    if [ "$?" -ne 0 ]; then
+        echo "Docker compose up failed!"
+        exit 1
+    fi
+    docker compose exec otf-nvs bash
+fi