Debian Science Project
Summary
Image analysis development
Debian Science development of image analysis applications

This metapackage will install Debian Science development libraries to develop scientific image analysis applications acquisitions.

Description

For a better overview of the project's availability as a Debian package, each head row has a color code according to this scheme:

If you discover a project which looks like a good candidate for Debian Science to you, or if you have prepared an unofficial Debian package, please do not hesitate to send a description of that project to the Debian Science mailing list

Links to other tasks

Debian Science Image analysis development packages

Official Debian packages with high relevance

Cimg-dev
powerful image processing library
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The CImg Library is a C++ toolkit providing simple classes and functions to load, save, process and display images in your own C++ code. It consists only of a single header file CImg.h that must be included in your program source. It contains useful image processing algorithms for loading/saving, resizing/rotating, filtering, object drawing (text, lines, faces, ellipses, ...), etc.

Images are instantiated by a class able to represent images up to 4-dimension wide (from 1-D scalar signals to 3-D volumes of vector-valued pixels), with template pixel types. It depends on a minimal number of libraries : you can compile it with only standard C libraries. No need for exotic libraries and complex dependencies.

The package is enhanced by the following packages: cimg-doc cimg-examples
Libcv-dev
Translation package for libcv-dev
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This package provide files for translation from libcv-dev to subdivided packages.

This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision).

The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance.

OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction.

Libimglib2-java
??? missing short description for package libimglib2-java :-(
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Liblimereg-dev
Library for lightweight image registration [development files]
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Liblimereg automatically aligns two images with similar content to each other. Given two 2D images the algorithm returns the rigid transformation parameters detected for the best possible alignment (shift, rotation). There are also functions for a rigid image transformation (shift, rotation) and for creating a difference image out of two images.

This package contains the static library and the header file.

Libsimage-dev
generic interface to various image file format libraries. Development files.
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The simage library provides a simplified and uniform interface to many image file format libraries, and it includes internal support for some image file formats too. The package ships development files.

Libvigraimpex-dev
development files for the C++ computer vision library
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Vision with Generic Algorithms (VIGRA) is a computer vision library that puts its main emphasis on flexible algorithms, because algorithms represent the principle know-how of this field. The library was consequently built using generic programming as introduced by Stepanov and Musser and exemplified in the C++ Standard Template Library. By writing a few adapters (image iterators and accessors) you can use VIGRA's algorithms on top of your data structures, within your environment.

This package contains the header and development files needed to build programs and packages using VIGRA.

Libvlfeat-dev
Computer vision library focussing on visual features and clustering
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VLFeat implements popular computer vision algorithms including SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, and quick shift. It is written in C for efficiency and compatibility, with interfaces in GNU octave for ease of use, and detailed documentation throughout

Development files

Python-vigra
Python bindings for the C++ computer vision library
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Vision with Generic Algorithms (VIGRA) is a computer vision library that puts its main emphasis on flexible algorithms, because algorithms represent the principle know-how of this field. The library was consequently built using generic programming as introduced by Stepanov and Musser and exemplified in the C++ Standard Template Library. By writing a few adapters (image iterators and accessors) you can use VIGRA's algorithms on top of your data structures, within your environment.

This package exports the functionality of the VIGRA library to Python.

Python3-imageio
library for reading and writing image data (Python 3)
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Imageio is a Python library that provides an easy interface to read and write a wide range of image data, including animated images, video, volumetric data, and scientific formats.

This package provides the library for Python 3.

Python3-meshio
??? missing short description for package python3-meshio :-(
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Official Debian packages with lower relevance

Lib3ds-dev
Autodesk 3D Studio file reader development files
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This library implements the functionality required to manage Autodesk's 3D Studio Release 3 and 4 format (.3DS) files.

It is a free alternative to Autodesk's 3DS File Toolkit for managing 3DS files.

This package contains the development files (headers and libs).

Libfreeimage-dev
Support library for graphics image formats (development files)
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FreeImage is an Open Source C/C++ library project for developers who would like to support popular graphics image formats like PNG, BMP, JPEG, TIFF and others as needed by today's multimedia applications. FreeImage is easy to use, fast, multithreading safe, and cross-platform (works both with Linux, 32 bit Windows and Mac OS X).

This package contains the headers and static libraries needed to develop programs using FreeImage.

Python-imageio
library for reading and writing image data (Python 2)
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Imageio is a Python library that provides an easy interface to read and write a wide range of image data, including animated images, video, volumetric data, and scientific formats.

This package provides the library for Python 2.

Packaging has started and developers might try the packaging code in VCS

Libvisad-java
Visualization for Algorithm Development
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Version: 2.0-1

VisAD is a Java component library for interactive and collaborative visualization and analysis of numerical data. The name VisAD is an acronym for "Visualization for Algorithm Development". The system combines:

The use of pure Java for platform independence and to support data sharing and real-time collaboration among geographically distributed users. Support for distributed computing is integrated at the lowest levels of the system using Java RMI distributed objects.

A general mathematical data model that can be adapted to virtually any numerical data, that supports data sharing among different users, different data sources and different scientific disciplines, and that provides transparent access to data independent of storage format and location (i.e., memory, disk or remote). The data model has been adapted to netCDF, HDF-5, FITS, HDF-EOS, McIDAS, Vis5D, GIF, JPEG, TIFF, QuickTime, ASCII and many other file formats.

A general display model that supports interactive 3-D, data fusion, multiple data views, direct manipulation, collaboration, and virtual reality. The display model has been adapted to Java3D and Java2D and used in an ImmersaDesk virtual reality display.

Data analysis and computation integrated with visualization to support computational steering and other complex interaction modes.

Support for two distinct communities: developers who create domain- specific systems based on VisAD, and users of those domain-specific systems. VisAD is designed to support a wide variety of user interfaces, ranging from simple data browser applets to complex applications that allow groups of scientists to collaboratively develop data analysis algorithms.

Developer extensibility in as many ways as possible.

*Popularitycontest results: number of people who use this package regularly (number of people who upgraded this package recently) out of 200581