sandboxed-api/oss-internship-2020/gdal/raster_to_gtiff
Christian Blichmann 75bbd0e1c1 Internal change
Only externally visible changes should be a few changed includes as well as
some formatting changes.

PiperOrigin-RevId: 353226662
Change-Id: Iebf5be13774efcbd94c5d5a17b9b27e47275b229
2021-01-22 06:01:34 -08:00
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testdata Updated CMake and tests, wrote README 2020-10-06 04:06:54 -07:00
CMakeLists.txt Move utility code into sandboxed_api/util 2021-01-13 09:25:52 -08:00
gdal_sandbox.h Merge pull request #64 from bohdanty:gdal_sandbox 2020-10-19 08:08:03 -07:00
get_raster_data.cc Merge pull request #64 from bohdanty:gdal_sandbox 2020-10-19 08:08:03 -07:00
get_raster_data.h Merge pull request #64 from bohdanty:gdal_sandbox 2020-10-19 08:08:03 -07:00
gtiff_converter.cc Internal change 2021-01-22 06:01:34 -08:00
gtiff_converter.h Merge pull request #64 from bohdanty:gdal_sandbox 2020-10-19 08:08:03 -07:00
raster_to_gtiff.cc Move utility code into sandboxed_api/util 2021-01-13 09:25:52 -08:00
README.md Merge pull request #64 from bohdanty:gdal_sandbox 2020-10-19 08:08:03 -07:00
tests.cc Move utility code into sandboxed_api/util 2021-01-13 09:25:52 -08:00
utils.cc Move utility code into sandboxed_api/util 2021-01-13 09:25:52 -08:00
utils.h Merge pull request #64 from bohdanty:gdal_sandbox 2020-10-19 08:08:03 -07:00

GDAL Raster to GeoTIFF Workflow Sandbox

This repository is an example of how Sandboxed API can be used with GDAL C Raster API to implement the creation of the GeoTIFF dataset inside the sandbox.

Workflow details

Implemented workflow consists of a few steps:

  1. Register needed drivers inside the sandbox
  2. Get specific driver by name (GTiff)
  3. Map output file inside the sandbox and create a GeoTIFF dataset backed by this file
  4. Set affine transformation coefficients if needed
  5. Set projection reference string if needed
  6. Write raster bands data to the dataset using RasterIO
  7. Set No data value if needed
  8. Clean up data and close the dataset

Implementation details

This project consists of a CMake file that shows how you can connect Sandboxed API and GDAL, a raster data parser using unsandboxed GDAL to generate sample input for the sandboxed workflow, sample sandbox policy that could work with GeoTIFF files without any violations, command-line utility that uses sandboxed GDAL to implement the workflow and GoogleTest unit tests to compare raster data of original datasets with the raster data of datasets that have been created inside the sandbox.

Build GDAL sandbox

Because GDAL doesn't use CMake or Bazel it's required to have a static build of libgdal and libproj. Moreover, proj.db file path is required to be able to map it inside the sandbox and use it internally for some of the projections.

Build GDAL and PROJ from sources

To get the latest version of both GDAL and PROJ you will need to build them from sources. To make a clean installation you can use the build folder as an installation path, with this approach you won't affect any system files and will be able to easily delete everything later. First, you will need to build PROJ, which is used internally in the GDAL. You can't use the libproj-dev package because it contains an outdated version, while GDAL requires a more recent one. To install PROJ from sources you can do the following:

mkdir build && cd build
wget https://download.osgeo.org/proj/proj-7.1.1.tar.gz
tar xvzf proj-7.1.1.tar.gz
mkdir proj_build
cd proj-7.1.1
./configure --prefix=/path/to/build/proj_build
make -j8
make install
make check

The static version of libproj will be available at proj_build/lib/libproj.a. Then, you can start GDAL installation:

cd build
git clone https://github.com/OSGeo/gdal
mkdir gdal_build
cd gdal/gdal
./configure --prefix=/path/to/build/gdal_build --with-proj=/path/to/build/proj_build
make -j8
make install

To verify that everything is installed correctly you can run gdalinfo utility.

cd ../../gdal_build/bin/
./gdalinfo --version

The static version of libgdal will be available at gdal_build/lib/libgdal.a. You will need to specify paths to those static libraries as the CMake arguments to build the project. Also, the Sandboxed API generator needs gdal.h header, which is located at build/gdal/gdal/gcore/gdal.h.

Build sandboxed GDAL

To build the examples from this repository you can use CMake in the following way:

mkdir build
cd build
cmake .. -G Ninja -DSAPI_ROOT=/path/to/sapi

This build expects lib/ folder with both libgdal.a and libproj.a to be present near the source files. Also, you need to have gdal.h header so Sandboxed API generator could parse it, the default expected path to it is /usr/local/include. Finally, you could enable tests with the -DENABLE_TESTS=ON option for the CMake. You can specify those paths as a CMake argument, so the complete example looks like this:

mkdir build
cd build
cmake .. -G Ninja -DSAPI_ROOT=/path/to/sapi    \
-DGDAL_HEADER_PREFIX=/path/to/gdal/header      \
-DLIBGDAL_PREFIX=/path/to/libgdal_static_build \
-DLIBPROJ_PREFIX=/path/to/libproj_static_build \
-DENABLE_TESTS=ON

After CMake build is completed, you can run ninja to build the executables.

Examples

PROJ uses proj.db database to work correctly with different transformations and you will need to map it to the sandbox manually to be able to retrieve it in the restricted environment. After the installation you can find proj.db in /path/to/proj/share/proj/proj.db.

You can use environment variables to set path to proj:

export PROJ_DB_PATH=/path/to/proj.db

The code will check this variable and if it represents a valid file it will be mounted inside the sandbox. Alternatively, if there is no such environment variable program will try to use the default path /usr/local/share/proj/proj.db. There is a simple command-line utility that takes path to the GeoTIFF file and absolute path to the output file as arguments, parses raster data from the input file and, re-creates the same GeoTIFF file (except some metadata) inside the sandbox.

You can run it in the following way:

./raster_to_gtiff path/to/input.tif /absolute/path/to/output.tif

After that, you can compare both files using the gdalinfo utility. Also, there are unit tests that automatically convert a few files and then compare input and output raster data to make sure that they are equal. To run tests your CMake build must use -DENABLE_TESTS=ON, then you can run tests using ctest. Note that it will also run Sandboxed API related tests. To run tests manually you will need to specify a few environmental variables and then run tests executable.

export TEST_TMPDIR=/tmp/
export TEST_SRCDIR=/path/to/project/source

All test data is from osgeo samples.