VIAME is a computer vision library designed to integrate several image and video processing algorithms together in a common distributed processing framework, majorly targeting marine species analytics. As it contains many common algorithms and compiles several other popular repositories together as a part of its build process, VIAME is also useful as a general computer vision toolkit. The core infrastructure connecting different system components is currently the KWIVER library, which can connect C/C++, python, and matlab nodes together in a graph-like pipeline architecture. Alongside the pipelined image processing system are a number of standalone utilties for model training, output detection visualization, groundtruth annotation, detector/tracker evaluation (a.k.a. scoring), image/video search, and rapid model generation.
This manual is synced to the VIAME 'master' branch and is updated frequently, you may have to press ctrl-F5 to see the latest updates to avoid using your browser cache of this webpage.
.. toctree:: :maxdepth: 1 section_links/building_and_installing_viame section_links/example_capabilities section_links/image_enhancement section_links/object_detection section_links/object_tracking section_links/detection_file_conversions section_links/measurement_using_stereo section_links/object_detector_training section_links/search_and_rapid_model_generation section_links/annotation_and_visualization section_links/scoring_and_roc_generation section_links/archive_summarization Core C++/Python Object Types <http://kwiver.readthedocs.io/en/latest/vital/architecture.html> Core Pipelining Architecture <http://kwiver.readthedocs.io/en/latest/sprokit/architecture.html> Basic Pipeline Nodes <http://kwiver.readthedocs.io/en/latest/arrows/architecture.html> section_links/hello_world_pipeline section_links/external_plugin_creation section_links/using_detectors_in_cxx_code KWIVER Full Manual <http://kwiver.readthedocs.io/en/latest/>