GithubHelp home page GithubHelp logo

imclab / maptk Goto Github PK

View Code? Open in Web Editor NEW

This project forked from kitware/telesculptor

0.0 2.0 0.0 8.09 MB

Motion-imagery Aerial Photogrammetry Toolkit

License: Other

Shell 0.23% CMake 4.27% C++ 90.20% C 0.12% Python 3.43% Ruby 1.76%

maptk's Introduction

MAP-Tk

/gui/icons/64x64/mapgui.png

Motion-imagery Aerial Photogrammetry Toolkit

MAP-Tk is an open source C++ collection of libraries and tools for making measurements from aerial video. Initial capability focuses on estimating the camera flight trajectory and a sparse 3D point cloud of the scene. These products are jointly optimized via sparse bundle adjustment and are geo-localized if given additional control points or GPS metadata.

This project has similar goals as projects like Bundler and VisualSFM. However, the focus here in on efficiently processing aerial video rather than community photo collections. Special attention has been given to the case where the variation in depth of the 3D scene is small compared to distance to the camera. In these cases, planar homographies can be used to assist feature tracking, stabilize the video, and aid in solving loop closure problems.

The MAP-Tk software architecture is highly modular and provides an algorithm abstraction layer that allows seamless interchange and run-time selection of algorithms from various other open source projects like OpenCV, VXL, Ceres Solver, and PROJ4. The core library is light-weight with minimal dependencies (C++ standard library, Vital, and Eigen). The tools are written to depend only on the MAP-Tk and Vital core libraries. Additional capabilities are provided in plugin modules that use third party libraries to implement various abstract algorithm interfaces defined in the core. Plugin modules may also implement additional versions of core MAP-Tk data structures.

In addition to the libraries and tools, a Qt GUI application is provided to assist with visualization of data and results with the help of VTK. The screenshots below show the MAP-Tk GUI visualizing results of MAP-Tk run on example videos from the VIRAT Video Dataset and CLIF 2007 Dataset. More information about this example data can be found in the examples directory.

Mac OS X Screenshot

Windows Screenshot

Linux Screenshot

While the initial software implementation relies on batch post-processing of aerial video, our intent is to move to an online video stream processing framework and optimize the algorithms to real-time performance for use onboard unmanned aerial vehicles.

Overview of Directories

CMake contains CMake helper scripts
config contains reusable default algorithm configuration files
doc contains release notes, manuals, and other documentation
examples contains example tool configuration for public datasets
gui contains the visualization GUI source code and headers
gui/icons contains the visualization GUI icon resources
maptk contains the core library source and headers
maptk/plugins/ceres contains the Ceres Solver plugin source and headers
maptk/plugins/core contains core plugin source and headers
maptk/plugins/ocv contains the OpenCV plugin source and headers
maptk/plugins/proj contains the PROJ4 plugin source and headers
maptk/plugins/viscl contains the VisCL plugin source and headers
maptk/plugins/vxl contains the VXL plugin source and headers
packaging contains support files for CPack packaging
scripts contains Python helper scripts
scripts/blender contains Python plug-ins for Blender
tests contains testing framework and tests for each module
tools contains source for command line utilities

Building MAP-Tk

MAP-Tk uses CMake (www.cmake.org) for easy cross-platform compilation. The minimum required version of CMake is 3.0, but newer versions are recommended.

Currently, a compiler with at least partial C++11 support (e.g. GCC 4.4, Visual Studio 2013) is required.

Running CMake

We recommend building MAP-Tk out of the source directory to prevent mixing source files with compiled products. Create a build directory in parallel with the MAP-Tk source directory. From the command line, enter the empty build directory and run:

$ ccmake /path/to/maptk/source

where the path above is the location of your MAP-Tk source tree. The ccmake tool allows for interactive selection of CMake options. Alternatively, using the CMake GUI you can set the source and build directories accordingly and press the "Configure" button.

CMake Options

BUILD_SHARED_LIBS Build shared libraries (.so/.dylib/.dll)
CMAKE_BUILD_TYPE The compiler mode, usually Debug or Release
CMAKE_INSTALL_PREFIX The path to where you want MAP-Tk to install
MAPTK_ENABLE_MANUALS Turn on building the user documentation (manuals)
MAPTK_ENABLE_DOCS Turn on building the Doxygen documentation
MAPTK_INSTALL_DOCS Install Doxygen documentation (requires above enabled)
MAPTK_ENABLE_TESTING Build the unit tests
MAPTK_ENABLE_CERES Turn on building the Ceres Solver plugin module
MAPTK_ENABLE_OPENCV Turn on building the OpenCV plugin module
MAPTK_ENABLE_PROJ Turn on building the PROJ.4 plugin module
MAPTK_ENABLE_VISCL Turn on building the VisCL plugin module
MAPTK_ENABLE_VXL Turn on building the VXL plugin module
MAPTK_USE_BUILD_PLUGIN_DIR Add the path to plugins in the build directory to the plugin search path

Note

Shared libraries (BUILD_SHARED_LIBS=ON) is required to support dynamic plugin loading

Dependencies

MAP-Tk has minimal required dependencies at the core level. Enabling plugins adds additional capabilities as well as additional dependencies. Some functionality is duplicated between modules to provide choices. Feature tracking requires OpenCV or VisCL. Bundle adjustment requires Ceres Solver or VXL. Geographic transformations require PROJ4.

Required

The only hard dependencies of MAP-Tk are on the C++ standard library, Vital (≥ 0.1), and Eigen (≥ 3.0; also required by Vital).

Optional Plugins

Each MAP-Tk plugin module brings in more dependencies for additional functionality. Dependencies for each module are:

GUI

The visualization application (GUI) is optional, and has additional dependencies. To build the GUI, you need:

Documentation

Documentation generation is another optional component that brings in additional dependencies. To build the API documentation, you need:

To build the user manual(s), you need:

(At present, only the GUI has a user manual. Other manuals may be added in the future.)

Nightly builds of the Doxygen documentation for the primary branches are here:

Nightly master Documentation http://www.kwiver.org/maptk/docs/nightly/master
Nightly release Documentation http://www.kwiver.org/maptk/docs/nightly/release

Doxygen documentation for released versions are here:

MAP-Tk v0.6.1 Documentation http://www.kwiver.org/maptk/docs/release/v0.6.1
MAP-Tk v0.7.2 Documentation http://www.kwiver.org/maptk/docs/release/v0.7.2
MAP-Tk v0.8.0 Documentation http://www.kwiver.org/maptk/docs/release/v0.8.0

Building Documentation

If MAPTK_ENABLE_DOCS is enabled, and CMake finds, or is provided with, a path to the Doxygen tool, then the HTML documentation is built as part of the normal build process under the target "doxygen". Open ${MAPTK_BUILD_DIR}/docs/index.html in your browser to view the documentation.

If MAPTK_ENABLE_MANUALS is enabled, and CMake finds, or is provided with, a path to the Python executable which is able to import docutils, then the user manuals are built as part of the normal build process under the target "manuals". The GUI manual can be viewed from inside the GUI by choosing the "MapGUI User Manual" action from the "Help" menu.

Testing

Continuous integration testing is provided by CDash. Our MAP-Tk dashboard hosts nightly build and test results across multiple platforms including Windows, Mac, and Linux.

Anyone can contribute a build to this dashboard using the dashboard script provided. Follow the instructions in the comments.

Travis CI is also used for continued integration testing. Travis CI is limited to a single platform (Ubuntu Linux), but provides automated testing of all topic branches and pull requests whenever they are created.

Travis CI master branch: CI:master
Travis CI release branch: CI:release

MAP-Tk Tools

MAP-Tk command line tools are placed in the bin directory of the build or install path. These tools are described below.

Summary of MAP-Tk Tools

The primary tools are maptk_track_features and maptk_bundle_adjust_tracks. Together these form the sparse bundle adjustment pipeline. The other tools are for debugging and analysis purposes.

maptk_track_featues
Takes a list of images and produces a feature tracks file.
maptk_bundle_adjust_tracks
Takes feature tracks and produces cameras (KRTD files) and 3D points (PLY file). Can also take input POS files or geo-reference points and produce optimized POS files.
maptk_pos2krtd
Takes POS files and directly produces KRTD.
maptk_analyze_tracks
Takes images and feature tracks and produces tracking statistics or images with tracks overlaid.
maptk_estimate_homography
Estimates a homography transformation between two images, outputting a file containing the matrices.

Running MAP-Tk Tools

Each MAP-Tk tool has the same interface and accepts three command line arguments:

  • -c to specify an input configuration file
  • -o to output the current configuration to a file
  • -h for help (lists these options)

Each tool has all of its options, including paths to input and output files, specified in the configuration file. To get started, run one of the tools like this:

$ maptk_track_features -o config_file.conf

This will produce an initial set of configuration options. You can then edit config_file.conf to specify input/output files, choices of algorithms, and algorithm parameters. Just as in CMake, configuring some parameters will enable new sub-parameters and you need to re-run the tool to get the updated list of parameters. For example:

$ maptk_track_features -c config_file.conf -o config_file.conf

The above command will overwrite the existing config file with a new file. Ordering of entries and comments are not preserved. Use a different output file name to prevent overwriting the original. Continue to adjust parameters and re-run the above command until the tool no longer reports the message:

ERROR: Configuration not valid.

Note that the config file itself contains detail comments documenting each parameter. For each abstract algorithm you must specify the name of variant to use, but the list of valid names (based on which modules are compiled) is provided directly in the comment for easy reference. When the config file is complete and valid, run the tool one final time as:

$ maptk_track_features -c config_file.conf

An easier way to get started is to use the sample configuration files for each tool that are provided in the examples directory. These examples use recommended default settings that are known to produce useful results on some selected public data samples. The example configuration files include the default configuration files for each algorithm in the config directory.

Getting Help

MAP-Tk is a component of Kitware's collection of open source computer vision tools known as KWIVER. Please join the kwiver-users mailing list to discuss MAP-Tk or to ask for help with using MAP-Tk. For less frequent announcements about MAP-Tk and other KWIVER components, please join the kwiver-announce mailing list.

Acknowledgements

The authors would like to thank AFRL/Sensors Directorate for their support of this work via SBIR Contract FA8650-14-C-1820. This document is approved for public release via 88ABW-2015-2555.

maptk's People

Contributors

alouis38 avatar collinsr avatar dstoup avatar kfieldho avatar laurennlam avatar linus-sherrill avatar mattdawkins avatar mleotta avatar mwoehlke-kitware avatar purg avatar rustyblue avatar smithe4 avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.