LabelU

Free plan APIMacSelf-hostedWebWindows

What LabelU is

LabelU is an open-source platform for annotating image, video and audio data, intended for work supporting complex data analysis and model training. Image tools include bounding boxes, semantic segmentation, polylines and keypoints; video and audio tools support segmentation, classification and information extraction. Users can load pre-annotated data for review and adjustment, or use AI model services to detect and segment image objects, including batch annotation with progress tracking. LabelU imports annotation data from S3-compatible storage such as AWS S3 and MinIO, and exports JSON, COCO and MASK formats. Its local setup uses Miniconda, Python 3.11 and pip, with a server at http://localhost:8000/. The platform includes SQLite and supports MySQL installation and migration. Its model server provides HTTP POST / and GET /health endpoints. Listed reference models require about 4GB VRAM for Florence-2 and GroundingDINO with SAM ViT-B, while SAM 3 requires about 8GB and CUDA 12.6 or later. The project is licensed under Apache 2.0.

Who it suits

LabelU suits teams annotating image, video or audio data for analysis and model training. It is aimed at users who can work with a local deployment and, for model-assisted labeling, the listed hardware requirements.

What it does well

Supports image, video and audio annotation.
Can refine pre-annotated data and use AI model services.
Imports from S3-compatible storage and exports three formats.
Apache 2.0 licensed.

What to know first

Local setup requires Miniconda, Python 3.11 and pip.
SAM 3 requires about 8GB VRAM and CUDA 12.6 or later.
The listed support channel is an OpenDataLab WeChat group.

Limits

Florence-2 and GroundingDINO with SAM ViT-B each require about 4GB VRAM. SAM 3 requires about 8GB VRAM and CUDA 12.6 or later.

Getting started

Open the LabelU GitHub project page.
For local deployment, install Miniconda and Python 3.11.
Install LabelU with pip and start the local server at http://localhost:8000/.
Import data from S3-compatible storage such as AWS S3 or MinIO, or load pre-annotated data.
Choose an annotation workflow for image, video, or audio, then export JSON, COCO, or MASK as needed.

Verdict

LabelU brings multimodal annotation, model-assisted labeling and several export formats into an open-source package. Its local setup and model requirements are relevant considerations for teams planning deployment.

Questions

Is LabelU free?

Yes. LabelU is free and open source under the Apache 2.0 license.

Which platforms does LabelU support?

The listed platforms are API, macOS, self-hosted, web, and Windows.

What data can I annotate?

LabelU supports image, video, and audio annotation. Its tools include image boxes, segmentation, polylines, and keypoints, plus video and audio segmentation, classification, and information extraction.

Can LabelU use AI-assisted labeling?

Yes. Users can load and refine pre-annotated data, or use AI model services to detect and segment image objects. Batch annotation has real-time progress tracking.

Which storage and export formats does it support?

It can import annotation data from S3-compatible storage such as AWS S3 and MinIO. Export formats include JSON, COCO, and MASK.

What are the listed model requirements?