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openlabel

OpenLabel is an open-source data labeling platform designed to facilitate the creation of labeled datasets for machine learning, computer vision, natural language processing, and audio processing. It is a web-based tool that can be deployed locally or hosted in the cloud and supports labeling tasks for images, text, audio, and video. Annotation types typically include bounding boxes, polygons, keypoints, text tags, transcription, and segmentation.

OpenLabel emphasizes collaborative workflows. It supports multi-user projects, role-based access control, task queues, review and quality-control

For data interoperability, OpenLabel offers import and export capabilities to common formats and pipelines. Users can

As an open-source project, OpenLabel is community-driven, with ongoing contributions from developers, researchers, and practitioners. Documentation,

The platform is used by academic researchers, industry teams, and non-profit organizations to create labeled datasets

steps,
and
change
tracking
to
maintain
reproducibility
of
annotations.
export
labeled
data
in
various
formats
suitable
for
ML
models
and
evaluation,
and
an
API
enables
automation
and
integration
with
data
processing
pipelines.
tutorials,
and
community
forums
accompany
the
project
to
assist
new
users
and
share
best
practices.
more
efficiently,
supporting
a
range
of
applications
from
computer
vision
to
speech
and
text
analysis.