Skip to main content

Cross-platform 2d/3d image segmentation C++ library

Project description

# MAZAlib

Cross-platform 2d/3d image segmentation C++ library

Compliles with: MSVC 14.0 and later, GCC 9.2. Other GCC: not tested yet. Compatible with C++17

Authors: Roman V. Vasilyev, Timofey Sizonenko, Kirill M. Gerke, Marina V. Karsanina Moscow, 2017-2021

## Prerequisites

1. Install CMake 3.13 or later. (Or you may lower version requirements by hand to your actual version in all CMakeFiles.txt and hopefully it would work, just not tested yet). Linux (Ubuntu): sudo apt-get install cmake Windows: https://cmake.org/download/, add cmake into PATH system variable during installation 2. Install a modern C++ compiler. Linux (Ubuntu): sudo apt-get install g++ Windows: Visual Studio 2015 or later with C++ tools installed 3. Optionally, for hardware support of non-local means denoising, CUDA-enabled GPU and CUDA toolkit installed

## Building

  1. (Optionally) make a build subdirectory and move there, for example “build_release”

  2. run cmake <relative path to project>, for example “cmake ..” inside build directory. If you’re building project with CUDA support, you can specify compute capability of your GPU (to define the one, go to NVIDIA web site). For example, GeForce GTX 1080Ti has compute capability 6.1, then use following command: “cmake DCMAKE_CUDA_FLAGS=”-arch=sm61” ..”

  3. If you have CUDA compiler and NVIDIA GPU, the project automatically configures itself to use GPU for NLM denoising. Otherwise, CPU host code will be used

  4. Then under Linux just run “make”, under Windows open a generated solution file using Visual Studio and build “segmentation_test_exe” project. A library and “segmentation_probny_loshar.exe” will be compiled and built

  5. Run segmentation_probny_loshar under console to check that all is OK

## Config file structure

width height depth radius VarMethod CorMethod OutFormat LowThreshold HighThreshold binary_input_file_name

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mazalib-0.37-cp39-cp39-win_amd64.whl (4.1 MB view details)

Uploaded CPython 3.9Windows x86-64

File details

Details for the file mazalib-0.37-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: mazalib-0.37-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 4.1 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.2rc1

File hashes

Hashes for mazalib-0.37-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 f07824f4f8a2b22e694738c4bd55ea1e6ffd9affa1b87ce3656934fc59e9d557
MD5 56c9ff7dad8588e8da8370fc3289eb72
BLAKE2b-256 0aed86a2631ac1b1f343e7135c803c9b8b8d0427b3a4eda0738b847fee880c6f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page