Awesome

cm-vsm

A raster conversion and segmentation mask vectorization tool for KappaZeta cloudmask.

Dependencies

The following system dependencies are needed:

• g++8 or later
• CMake 3.4.3 or later
• cget (https://github.com/pfultz2/cget)
• OpenJPEG (libopenjp2-7-dev)
• GDAL (libgdal-dev, gdal-bin, gdal-data)
• Expat (libexpat1-dev)
• GraphicsMagick++ (libgraphicsmagick++1-dev)
• NetCDF (libnetcdf-dev)
• nlohmann's JSON (https://github.com/nlohmann/json)
• CppUnit (libcppunit-dev)
• Doxygen (for documentation only)

On Ubuntu, the following commands could be used to install the dependencies:

sudo add-apt-repository ppa:ubuntu-toolchain-r/test
sudo apt update
sudo apt-get install cmake gcc-9 g++-9 python3-pip libgdal-dev gdal-bin libexpat1-dev libgraphicsmagick++1-dev libcppunit-dev
pip3 install cget

On Fedora or CentOS, run

sudo yum install cmake gcc gcc-c++ python3-pip openjpeg2-devel libpng-devel gdal gdal-devel expat-devel GraphicsMagick-c++-devel netcdf-devel libjpeg-turbo-devel jbigkit-libs jbigkit-devel m4 cppunit-devel libtiff-devel

Make sure that your GDAL_DATA environment variable has been set, according to your GDAL version, which is indicated by the placeholder YOUR_GDAL_VERSION below:

GDAL_DATA=/usr/share/gdal/YOUR_GDAL_VERSION

Building

Ensure that there is no active Conda environment (except base) while building cm-vsm.

A release version of the tool can be built as follows:

cd vsm/build
cget install
cmake .. -DCMAKE_CXX_COMPILER=g++-9
make
sudo make install

Similarly, a debug version can be built as follows:

cd vsm/build
cget install
cmake .. -DCMAKE_CXX_COMPILER=g++-9 -DCMAKE_BUILD_TYPE=Debug
make
sudo make install

Once CMake has already been run in the build directory, the documentation can be built as follows:

cd vsm/build
make doc

Building in Visual Studio Code (Ubuntu Linux)

For the program to run additional packages from the "Extensions" tab are requred:

• C/C++ (Microsoft)
• CMake Tools (Microsoft)
• CMake (twxs)

Using terminal navigate to ~/cm-vsm/vsm/build and run:

cget install

To configure the project press Ctrl + Shift + P in Visual Studio Code and run:

>CMake: Configure

If CMake cannot find CMakeLists.txt, navigate to it manually or reopen vsm folder as a project.

To build the project press Ctrl + Shift + P in Visual Studio Code and run:

>CMake: Build

To debug the project set a breakpoint, press Ctrl + Shift + P in Visual Studio Code and run:

>CMake: Debug

To avoid #include errors caused by IntelliSense, press Ctrl + Shift + P in Visual Studio Code and run:

C/C++: Edit configurations (UI)

In the configuration window specify an additional include path:

/usr/include/GraphicsMagick

and select C++17 as a C++ standard down to the bottom.

Usage

With the -d option, cm_vsm can be used to subtile a Sentinel-2 L2A raster image, for example:

./vsm/build/bin/cm_vsm -d /your/data/path/S2A_MSIL2A_20200529T094041_N0214_R036_T35VLF_20200529T120441.SAFE

The image will be processed band by band, and it might take about an hour to process the whole raster. In order to limit processing to specific bands, the -b comma,separated,list,of,band,names argument could be used. The results would be stored in another directory with a suffix .CVAT instead of the original .SAFE.

A CVAT annotations XML file could be rasterized with the -r option. This is to be performed after the successful subtiling of the raster image. Rasterization of a labelled subtile 2, 3, for example:

./vsm/build/bin/cm_vsm -r /your/data/path/S2A_MSIL2A_20200529T094041_N0214_R036_T35VLF_20200529T120441.CVAT/tile_2_3/annotations.xml -n /your/data/path/S2A_MSIL2A_20200529T094041_N0214_R036_T35VLF_20200529T120441.CVAT/tile_2_3/T35VLF_tile_2_3.nc

Supported bands

The following bands / layers are supported: