Add docker setup

.dockerignore

@@ -0,0 +1 @@
+.gitignore

Dockerfile

@@ -0,0 +1,90 @@
+FROM gurobi/optimizer:9.1.2
+
+WORKDIR /opt/build
+
+# Set opencv version and disable gui
+ENV OPENCV_VERSION="4.7.0" \
+    QT_QPA_PLATFORM=offscreen
+
+# Install dependencies (boost, openmp, qt, opencv, eigen, numpy)
+RUN apt-get -qq update \
+    && apt-get -qq install -y --no-install-recommends \
+        build-essential \
+        cmake \
+        git \
+        wget \
+        unzip \
+        yasm \
+        pkg-config \
+        python3-dev \
+        libswscale-dev \
+        libtbb-dev \
+        libjpeg-dev \
+        libpng-dev \
+        libtiff-dev \
+        libopenjp2-7-dev \
+        libavformat-dev \
+        libpq-dev \
+        libz-dev \
+        libbz2-dev \
+        libatlas-base-dev \
+        qtbase5-dev \
+        libboost-all-dev \
+        libeigen3-dev \
+        libomp-dev \
+	time \
+    && pip install numpy \
+    && wget -q https://github.com/opencv/opencv/archive/refs/tags/${OPENCV_VERSION}.zip -O opencv.zip \
+    && unzip -qq opencv.zip -d /opt \
+    && rm -rf opencv.zip \
+    && cmake \
+        -D BUILD_TIFF=ON \
+        -D BUILD_opencv_java=OFF \
+        -D WITH_CUDA=ON \
+        -D WITH_OPENGL=ON \
+        -D WITH_OPENCL=ON \
+        -D WITH_IPP=ON \
+        -D WITH_TBB=ON \
+        -D WITH_EIGEN=ON \
+        -D WITH_V4L=ON \
+        -D BUILD_TESTS=OFF \
+        -D BUILD_PERF_TESTS=OFF \
+        -D CMAKE_BUILD_TYPE=RELEASE \
+        -D CMAKE_INSTALL_PREFIX=$(python3.11 -c "import sys; print(sys.prefix)") \
+        -D PYTHON_EXECUTABLE=$(which python3.11) \
+        -D PYTHON_INCLUDE_DIR=$(python3.11 -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())") \
+        -D PYTHON_PACKAGES_PATH=$(python3.11 -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())") \
+        /opt/opencv-${OPENCV_VERSION} \
+    && make -j$(nproc) \
+    && make install \
+    && rm -rf /opt/build/* \
+    && rm -rf /opt/opencv-${OPENCV_VERSION} \
+    && rm -rf /var/lib/apt/lists/* \
+    && apt-get -qq autoremove \
+    && apt-get -qq clean
+
+
+COPY . /workspace/line-drawing-vectorization-polyvector-flow
+WORKDIR /workspace/line-drawing-vectorization-polyvector-flow
+# Install python dependencies
+RUN pip install -U pip wheel \
+    && pip install -r requirements.txt \
+    && pip cache purge
+
+# Install paal
+RUN wget http://paal.mimuw.edu.pl/paal.zip && unzip paal.zip && mv home/paal/sources/paal/include/paal . && rm -rf home
+
+# Fix for: https://support.gurobi.com/hc/en-us/articles/360039093112-How-do-I-resolve-undefined-reference-errors-while-linking-Gurobi-in-C-
+RUN ln -s /opt/gurobi /opt/gurobi911 \
+    && cd /opt/gurobi/linux64/src/build \
+    && make \
+    && cp /opt/gurobi/linux64/src/build/libgurobi_c++.a /opt/gurobi/linux64/lib/
+
+# Build the vectorization algorithm
+RUN mkdir build 
+WORKDIR /workspace/line-drawing-vectorization-polyvector-flow/build
+RUN cmake -DCMAKE_BUILD_TYPE=Release .. && make -j$(nproc)
+WORKDIR /workspace/line-drawing-vectorization-polyvector-flow
+
+STOPSIGNAL SIGINT
+ENTRYPOINT ["/bin/bash", "run_vectorization.sh"]

docker-compose.yml

@@ -0,0 +1,18 @@
+version: "3.9"
+name: line-drawing-vectorization-polyvector-flow
+services:
+  gpu:
+    build:
+      context: .
+    volumes:
+      - ./inputs:/workspace/line-drawing-vectorization-polyvector-flow/inputs
+      - ./gurobi.lic:/opt/gurobi/gurobi.lic:ro
+    tmpfs:
+      - /tmp
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: all
+              capabilities: [gpu]

predict_points.sh

@@ -17,14 +17,14 @@ case "$(uname -s)" in
 
    Linux)
      echo 'Linux'
-     python prediction/usemodel.py --model prediction/best_model_checkpoint.pth --input $inputimage --output $outputpts
+     python prediction/usemodel.py --model prediction/best_model_checkpoint.pth --input "$inputimage" --output "$outputpts"
      echo 'Done!'
      ;;
 
    CYGWIN*|MINGW32*|MSYS*|MINGW*)
      echo 'MS Windows'
      # run python prediction
-     python usemodel.py --input $inputimage --output $outputpts
+     python usemodel.py --input "$inputimage" --output "$outputpts"
      # execute polyvector with arguments ../my_inputs/alligator_cut2.png ../my_inputs/pythontest.pts
 
      ;;

readme.md

@@ -22,14 +22,51 @@ Contact me if you need code for speed benchmarks. This release was tuned for bet
 }
 ```
 
-## Cmake build
+## Installation
+
+### Cmake build
 ```bash
 mkdir build
 cd build
 cmake -DCMAKE_BUILD_TYPE=Release ..
 make
 ```
 
+### Using Docker (alternative)
+Requires [Docker](https://docs.docker.com/engine/install/) and [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html) (for GPU acceleration).
+
+Retrieve a [Gurobi WLS license](https://www.gurobi.com/features/web-license-service/). This can be done by running:
+
+```
+grbgetkey
+```
+
+This will produce a `gurobi.lic` file. Place this into the repository directory.
+
+To build the Docker image using docker compose:
+
+```
+docker compose build
+```
+
+Alternatively, build it using `docker build`:
+
+```
+docker build -t line-drawing-vectorization-polyvector-flow-gpu .
+```
+
+Then, run a Docker container based on the built image using docker compose:
+
+```
+docker compose run gpu inputs/example.png
+```
+
+Alternatively, run it using `docker run`:
+
+```
+docker run --rm -v ./gurobi.lic:/opt/gurobi/gurobi.lic:ro -v ./inputs:/workspace/line-drawing-vectorization-polyvector-flow/inputs --gpus all line-drawing-vectorization-polyvector-flow-gpu inputs/example.png
+```
+
 ## Usage
 
 Running `build/vectorize` will start vectorization on default input parameters: `inputs/example.png` and `inputs/example.pts`

requirements.txt

@@ -0,0 +1,4 @@
+torch==1.10
+Pillow==9.2.0
+scikit-image==0.19.3
+matplotlib==3.5.2 

run_vectorization.sh

@@ -2,18 +2,18 @@
 
 # This script runs vectorization pipeline on imagefile provided (.png or .jpg)
 
-image=${1:-"examples/dog06.png"}
+image="${1:-"examples/dog06.png"}"
 
-ptsfile=${image//.png/_auto.pts}
-svgfile=${image//.png/_result.svg}
-txtfile=${image//.png/_logs.txt}
+ptsfile="${image//.png/_auto.pts}"
+svgfile="${image//.png/_result.svg}"
+txtfile="${image//.png/_logs.txt}"
 
-ptsfile=${ptsfile//.jpg/_auto.pts}
-svgfile=${svgfile//.jpg/_result.svg}
-txtfile=${txtfile//.jpg/_logs.txt}
+ptsfile="${ptsfile//.jpg/_auto.pts}"
+svgfile="${svgfile//.jpg/_result.svg}"
+txtfile="${txtfile//.jpg/_logs.txt}"
 
-echo $image - $ptsfile - $svgfile
+echo "$image - $ptsfile - $svgfile"
 
-bash predict_points.sh $image $ptsfile
+bash predict_points.sh "$image" "$ptsfile"
 
-build/vectorize $image $ptsfile $svgfile
+build/vectorize "$image" "$ptsfile" "$svgfile"