Getting Started¶
Overview¶
dictlearn is a module for signal and image processing. This tool include easy-to-use algorithms for denoising, inpainting, feature enhancement and detection, and image segmentation. Additionally, this tool has some methods designed specifically for medical image processing, among these are vessel segmentation and denoising of large 3D images.
- Multiple algorithms for dictionary learning and sparse coding
- Accelerated with Cython and C
- Built on numpy, scipy and scikit-learn
This module is a part of a masters thesis in applied mathematics, which can be read here.
Installation¶
Clone the repository:
$ git clone git@github.com:permfl/dictlearn.git
Linux/OSX¶
Install dependencies with:
$ pip install -r requirements.txt
Make sure scipy and numpy are linked with BLAS/lapack. See the installation guides for numpy and scipy for more details.
Then install the library with:
$ python setup.py install
Windows¶
Using Anaconda is strongly recommended. The PyWavelet package in requirement.txt are not listed in anaconda package repository. Comment out this dependency with #, then install dependencies with conda install:
$ conda install --file requirements.txt
$ pip install PyWavelets
Then install the library with:
$ python setup.py install
Cython not compiling on Windows¶
- Make sure you have the Microsoft C++ compiler. Download the compiler for python 2.7:
- https://www.microsoft.com/en-us/download/details.aspx?id=44266
- For python 3 you need
Build Tools for Visual Studio 2017
: - https://www.visualstudio.com/downloads/#build-tools-for-visual-studio-2017
See here if downloading the above compiler doesn’t fix the problem.
Next steps¶
See the examples, or the dictionary learning tutorial