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Oceanit’s Versatile Image Processing Architecture (VIPA) makes computer vision and video processing easy and intuitive.

VIPA is a software development platform for processing streams of data, with particular emphasis on manipulating images and extracting information from them. It provides an intuitive interface for creating applications that ingest, process, and display streaming audio, video, and image data, from a variety of sources.

Computer vision typically entails laboriously generating text-based code that can interpret images or video as the human visual system would. A VIPA developer can simply link discrete processing modules in a graphical environment to achieve this. This creates a fertile environment for rapid prototyping and development. It allows users to test and evolve, making computer vision software development a fluid creative process.

VIPA has a rich set of over 400 modules for reading and writing data, interacting with hardware, manipulating color, detecting objects, time domain filtering, mathematical operations, spatial transforms, plotting, fast Fourier transforms, audio processing, point clouds, 3D rendering, interprocess communication, and more.

VIPA runs on Ubuntu Linux, Microsoft Windows, MacOS, and on the Raspberry Pi. Applications developed on one platform can run on any other. Applications can run in the graphical development environment, standalone, or embedded in Python.

VIPA is well documented, with in-line help, a 200+ page tutorial-style user guide and over 100 demo apps.

To learn more about VIPA, please contact Oceanit.

  • Graphical development environment, allows individuals without extensive software experience to participate in development
  • Great for rapid prototyping and development
  • Supports a wide range of sensors, data formats/codecs, processing algorithms, and display environments
  • Multi-threaded to enable the spreading of tasks over multiple processors
  • Cross platform – Ubuntu Linux, Windows MacOS and Raspberry Pi
  • Rich set of processing modules to tackle a wide variety of tough problems quickly
  • Can be embedded in Python to build end-user applications