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https://github.com/ukoethe/vigra

a generic C++ library for image analysis
https://github.com/ukoethe/vigra

Last synced: 21 days ago
JSON representation

a generic C++ library for image analysis

Host: GitHub
URL: https://github.com/ukoethe/vigra
Owner: ukoethe
License: other
Created: 2011-07-06T08:34:57.000Z (almost 13 years ago)
Default Branch: master
Last Pushed: 2024-03-26T15:37:02.000Z (about 2 months ago)
Last Synced: 2024-03-26T16:46:08.026Z (about 2 months ago)
Language: C++
Homepage: http://ukoethe.github.io/vigra/
Size: 104 MB
Stars: 400
Watchers: 42
Forks: 190
Open Issues: 104
Metadata Files:
- Readme: README.md
- License: LICENSE.txt

Lists

awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
fucking-awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-cpp - VIGRA - 用于图像分析通用C++计算机视觉库. [MIT X11] (图像处理)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-cpp-completed - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-machine-learnings - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-machine-learning - VIGRA - VIGRA is a generic cross-platform C++ computer vision and machine learning library for volumes of arbitrary dimensionality with Python bindings. (C++ / Speech Recognition)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-cpp-completed - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-machine-learning - VIGRA - VIGRA is a genertic cross-platform C++ computer vision and machine learning library for volumes of arbitrary dimensionality with Python bindings. (C++ / [Tools](#tools-1))
awesome-machine-learning-library - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-advanced-metering-infrastructure - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-android-cpp - ukoethe/vigra - a generic C++ library for image analysis (TODO scan for Android support in followings)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
AI - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-cpp - VIGRA - A generic C++ computer vision library for image analysis. [MIT X11] (Image Processing)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-machine-learning - VIGRA - VIGRA is a generic cross-platform C++ computer vision and machine learning library for volumes of arbitrary dimensionality with Python bindings. (C++ / Speech Recognition)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)
awesome-machine-learning - Vigranumpy - Python bindings for the VIGRA C++ computer vision library. (Python / General-Purpose Machine Learning)

README

VIGRA Computer Vision Library
=============================

[![Build Status](https://dev.azure.com/ullrichkoethe/vigra/_apis/build/status/ukoethe.vigra)](https://dev.azure.com/ullrichkoethe/vigra/_build/latest?definitionId=1)

This file is part of the VIGRA computer vision library.
You may use, modify, and distribute this software according
to the terms stated in the LICENSE.txt file included in
the VIGRA distribution.

The VIGRA Website is
http://ukoethe.github.io/vigra/
Please direct questions, bug reports, and contributions to
[email protected] or
[email protected]

THIS SOFTWARE IS PROVIDED AS IS AND WITHOUT ANY EXPRESS OR
IMPLIED WARRANTIES, INCLUDING, WITHOUT LIMITATION, THE IMPLIED
WARRANTIES OF MERCHANTIBILITY AND FITNESS FOR A PARTICULAR PURPOSE.

Installation
------------

Installation instructions can be found in the file
```
$VIGRA_PATH/doc/vigra/Installation.html
```
If the documentation has not yet been generated (e.g. when you build from a development
snapshot), you find these instructions in
```
$VIGRA_PATH/docsrc/installation.dxx
```
or online at
http://ukoethe.github.io/vigra/doc-release/vigra/Installation.html

Documentation
-------------

If you downloaded an official release, the documentation can be found in `$VIGRA_PATH/doc/vigra/`, the start file
is `$VIGRA_PATH/doc/vigra/index.html` or online at http://ukoethe.github.io/vigra/#documentation.

When you use the development version from github, you can generate documentation by `make doc`.

Download
--------

VIGRA can be downloaded at http://ukoethe.github.io/vigra/#download. The official development
repository is at https://github.com/ukoethe/vigra

What is VIGRA
-------------

VIGRA is a computer vision library that puts its main emphasis on flexible algorithms, because algorithms represent the principal 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. Alternatively, you can also use the data structures provided within VIGRA, which can be easily adapted to a wide range of applications. VIGRA's flexibility comes almost for free: Since the design uses compile-time polymorphism (templates), performance of the compiled program approaches that of a traditional, hand tuned, inflexible, solution.