Pith. sign in

REVIEW 1 cited by

Mahotas: Open source software for scriptable computer vision

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1211.4907 v2 pith:DV45EZPN submitted 2012-11-21 cs.CV cs.SE

classification cs.CVcs.SE
keywords mahotaspythoncomputerlanguagevisionhttplibrarylicense
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Mahotas is a computer vision library for Python. It contains traditional image processing functionality such as filtering and morphological operations as well as more modern computer vision functions for feature computation, including interest point detection and local descriptors. The interface is in Python, a dynamic programming language, which is very appropriate for fast development, but the algorithms are implemented in C++ and are tuned for speed. The library is designed to fit in with the scientific software ecosystem in this language and can leverage the existing infrastructure developed in that language. Mahotas is released under a liberal open source license (MIT License) and is available from (http://github.com/luispedro/mahotas) and from the Python Package Index (http://pypi.python.org/pypi/mahotas).

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Exploring Superpixel Segmentation Methods in the Context of Citizen Science and Deforestation Detection

    cs.CV 2024-11 conditional novelty 4.0 of 10

    Seven of 22 superpixel methods (RSS, ERGC, ETPS, CRS, LSC, SH, GMMSP) outperform the SLIC baseline on a composite ranking for deforestation segment generation in the ForestEyes citizen science project.

Pith tools