Paket: python3-vigra (1.12.1+dfsg-1)

[ Kaynak: libvigraimpex  ]

Python3 bindings for the C++ computer vision library

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 Python3.

python3-vigra ile İlgili Diğer Paketler

• dep: libboost-python1.83.0 (>= 1.83.0)

  Boost.Python Library

• dep: libboost-python1.83.0-py312

  sanal paketi sağlayan libboost-python1.83.0

• dep: libc6 (>= 2.35)

  GNU C Library: Shared libraries
  ayrıca şunun tarafından sağlanan bir sanal paket libc6-udeb

• dep: libfftw3-single3 (>= 3.3.10)

  Library for computing Fast Fourier Transforms - Single precision

• dep: libgcc-s1 (>= 3.5)

  GCC support library

• dep: libhdf5-103-1t64

  HDF5 C runtime files - serial version

• dep: libhdf5-hl-100t64

  HDF5 High Level runtime files - serial version

• dep: libstdc++6 (>= 14)

  GNU Standard C++ Library v3

• dep: libvigraimpex11 (= 1.12.1+dfsg-1)

  C++ computer vision library

• dep: python3

  interactive high-level object-oriented language (default python3 version)

  dep: python3 (<< 3.13)

  dep: python3 (>= 3.12~)

• dep: python3-numpy (>= 1:1.25.0)

  Fast array facility to the Python language (Python 3)

• dep: python3-numpy-abi9

  sanal paketi sağlayan python3-numpy

• rec: python3-pyqt4

  Paket mevcut değil

• sug: python-vigra-doc

  Documentation for Python3 bindings for the C++ computer vision library

• sug: python3-h5py

  general-purpose Python interface to hdf5

python3-vigra indir

Tüm mevcut mimariler için indir

Mimari	Paket Boyutu	Kurulu Boyut	Dosyalar
armhf	3.770,5 kB	23.333,0 kB	[dosya listesi]