Skip to content
Back to the index

scikit-image

scikit-image.orgInfrastructure

No liveness check has reached it yet; it is registered on GitHub and has been in the index since 9 Oct 2026. How this is checked

scikit-image is a free, open-source Python library containing peer-reviewed algorithms for image processing and computer vision. Developers and researchers can use it for image transformation, analysis, segmentation, and feature extraction in Python applications.

Inferred · not functionally tested

Open SourceWebSelf-hostedCLI
scikit-image preview
Visit scikit-image.org
6.6kstars
2.4kforks
8features
2009since

Overview

6 features

Purpose: Processing and analyzing images in Python without building common algorithms from scratch.

Inferred · not functionally tested

Audience: Python developers, researchers, and data scientists

Inferred · not functionally tested

Functions: data_extraction

Inferred · not functionally tested

Interfaces: API: unknown · MCP: unknown · CLI: indicated (inferred, not tested) · Self-hosting: indicated (inferred, not tested)

Recorded constraints: pricing: open_source · license: Open Source · platforms: WEB · deployment: browser, self_hosted, cli

Constraint provenance is unknown; confirm requirements with the publisher.

Record sources: scikit-image.org · github.com. These links do not verify the individual claims.

scikit-image is a Frameworks & SDKs project. Inferred · not functionally tested: It focuses on processing and analyzing images in Python without building common algorithms from scratch. Inferred · not functionally tested: scikit-image is an open-source project aimed at python developers, researchers, and data scientists. Basis unknown · not verified: The project is open source (Open Source). Basis unknown · not verified: It ships for the web and the command line, and it can be self-hosted.

Behind scikit-image is scikit-image contributors, and it first shipped in 2009. Development happens publicly on GitHub with 6.6k stars and 31 commits in the last 90 days. Inferred · not functionally tested: Among its 6 catalogued features are image processing, image segmentation, and feature extraction.

Summary written by a language model from the project’s public pages.

Tasks: Inferred · not functionally tested

  • Image processing
  • Image segmentation
  • Feature extraction
  • Image transformation
  • Computer vision algorithms
  • Python API

Topics: Inferred · not functionally tested

Tags
python-libraryimage-processingcomputer-visionscientific-computing

JSON profile · Text profile · Access guide

Built with & integrations

Runs on
BrowserSelf-hostedCLI

Trust & compliance

License
Open Source
Public signals
HTTPSOpen SourceFree tierGitHub · ★ 6.6kActive maintenance

Indexing history

1

What PulseGate has recorded for this listing

  1. Indexed8 Oct · 21:37 UTC
    Scikit Image seen via Saashub
    Source: Saashub · Open

Frequently asked questions about scikit-image

What is scikit-image?
Inferred · not functionally tested: Scikit-image focuses on processing and analyzing images in Python without building common algorithms from scratch. It is catalogued under Frameworks & SDKs on PulseGate.
Who is scikit-image for?
Inferred · not functionally tested: scikit-image is an open-source project built for python developers, researchers, and data scientists.
Is scikit-image free?
Basis unknown · not verified: Yes — scikit-image is open source under the Open Source license and free to use.
What platforms does scikit-image run on?
Basis unknown · not verified: scikit-image runs on the web and the command line. It can also be self-hosted.
Is scikit-image still maintained?
The GitHub repository shows 31 commits in the last 90 days.
What projects are similar to scikit-image?
Similar projects tracked by PulseGate include async-matrix-bridge, loyaltydog-mcp, and Page Json.async-matrix-bridgeloyaltydog-mcpPage Json
Who makes scikit-image?
scikit-image is developed by scikit-image contributors.
When did scikit-image launch?
scikit-image first shipped in 2009.

Also in Frameworks & SDKs

Same category — not a similarity match