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Speech, vision & media

MMSegmentation

A shared experimental and deployment foundation dedicated to semantic segmentation.

Overview

Research summary

MMSegmentation focuses on assigning semantic labels to image pixels through a common training and evaluation framework. It provides segmentation model implementations, dataset integrations, configuration files and a model zoo built on OpenMMLab's infrastructure. Developers can start from a published configuration, adapt data and class definitions, and use the same toolkit for inference and evaluation.

This makes it useful for comparing segmentation methods and developing task-specific visual perception systems. Its scope is distinct from object detection even though the projects share infrastructure. Source code is Apache-2.0, with separate terms for datasets and checkpoints.

Repository summary

Stars
9,966
Open issues
Unavailable
Last push
2024-08-13
Commits, 90 days
Unavailable
Repository activity
Not scored
Version
Unavailable

Recorded catalogue figures. View repository data and provenance →

Classification

Pricing & services

Paid services unknown

Whether the provider offers paid products or services has not been established.

Licence scope

Implementation

Recorded implementation details and interfaces for MMSegmentation.

Implementation details

Python/PyTorch toolbox using OpenMMLab infrastructure

Languages
Python
Repository type
source

Recorded interfaces and capabilities

Licence scope

Repository

Repository snapshots, release information and recorded maintenance signals.

Repository snapshot

open-mmlab/mmsegmentation ↗

Stars
9,966
Open issues
Unavailable
Last push
2024-08-13
Commits, 90 days
Unavailable
Repository activity
Not scored
Archived
Not recorded

Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).

Maintenance and provenance

Catalogue snapshot
2026-10-06
Stars source
Recorded fallback
Last push source
Recorded fallback

Documentation

Recorded references and research provenance for this entry.

Recorded sources 4

Research metadata

Research date
2026-10-02
Catalogue snapshot
2026-10-06

Community & social 3 channels

Video

Communities

Social & updates