Showing 66 open source projects for "image processing"

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  • 1
    Lightningbeam

    Lightningbeam

    IDE for creating interactive Flash and HTML5 content

    Lightningbeam is a free, open-source alternative to Adobe Flash. It is written in Python, and uses PyGUI for a GUI, swfc for compiling, and Cairo for image processing. It has the ability to export to HTML5 as well as .swf, allowing for viewing on non-Flash-compatible devices (such as the iPhone or the Kindle), and can pack all resources into a single HTML file for portability. Lightningbeam supports ActionScript, allowing for interactive content creation.
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  • 2
    A extensible suite of tools for image capture and processing in a multi platform enviornment.
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  • 3
    VIPS is an image processing suite designed for extremely large images and colorimetry. It consists of a powerful re-usable library and a graphical user interface. http://www.vips.ecs.soton.ac.uk
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  • 4
    New Python bindings for the popular OpenCV image processing library.
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  • 5
    This project provides a fast distributed system for image processing, written in Python. It aim is to be used as service to PHP, Perl and Python application servers.
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  • 6
    MIVF - Medical Imaging and Visualization Factory, is a framework for medical applications. It supplies a platform, in which image processing and 3D visualization algorithms can be employed as reusable components (functional modules or plugins).
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  • 7
    Python library for parsing, processing and linearising VRML97 files
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  • 8
    Batch processing for Jpeg pictures packing. (written in python Compresseur d'images Jpeg par lot. (écrit en python)
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  • 9
    Image Processing software for combining information from images of the same scene, but with illumination variations or small changes. This work is the result of the coursework of an Image Processing regular course at IMPA.
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  • 10
    UIMP(Unified Image Manipulation Program) is an OS independent Image Processing system, which provides over 1000 algorithms and supports web online, console and GUI program.
    Downloads: 3 This Week
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  • 11
    GLEWpy aims to bring advanced OpenGL extensions to Python. This allows the Python OpenGL developer to use features such as fragment/vertex shaders and image processing on the GPU. It serves as a compliment to PyOpenGL and toolkits such as GLUT and SDL.
    Downloads: 1 This Week
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  • 12
    Written in Python and the Numeric package. It supports the examples of the book: Dougherty and Lotufo, Hands-on Morphological Image Proc., SPIE, 2003, ISSN=0-8194-4720-X. This toolbox has been continued at www.adessowiki.org under name ia870.
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  • 13
    ImageJ is a public domain Java image processing program inspired by NIH Image for the Macintosh. It runs, either as an online applet or as a downloadable application, on any computer with a Java 1.1 or later. HOME @ http://rsb.info.nih.gov/ij/
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    Downloads: 3 This Week
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  • 14
    Modama is a new software project for processing and analysing 2d detector data (images) provided by any available detectors, mainly SAX and WAX.
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  • 15

    golib

    C++ collection mostly for image processing

    libGo is a C++ class library containing all kinds of things that proved useful to me. Included are: - Linear algebra, using LAPACK and CBLAS - V4L(1) image grabber - Multithreading - Image containers (up to 3D) - Some simple optimisation code - Python embedding helper - Matlab interface - .. and other things, have a look at the HTML documentation! golib grew over many years, things I had use for have been added now and then. Some parts are better taken care of than others. If...
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  • 16

    geoscipy

    Python-accessible toolkit for Geoscience & Remote Sensing Applications

    ...There is also a Python API that provides a procedural as well as an object-oriented interface to these functions. A Python GUI for interacting with such datasets is also part of the project. While there are other open-source GIS, and image-processing packages available, this one is designed to be comprehensive, work on 3 major platforms, user-extensible, fast, and able to handle huge datasets. Click the Blog tab for more info.
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