qqlu/Entity

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1048 stars · 61 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

EntitySeg is an open-source PyTorch toolbox for open-world, high-quality image segmentation, built on Detectron2. It aggregates multiple research implementations including entity segmentation, ultra-high-resolution image segmentation, and semi-supervised detection/segmentation.

Use cases

• segment entities in images without predefined categories
• segment ultra high-resolution images with high quality
• run class-agnostic semi-supervised detection and segmentation
• evaluate open-vocabulary segmentation metrics
• fine-tune pretrained segmentation models on custom data

When to choose

• you need state-of-the-art open-world or high-quality entity segmentation models
• you want research-grade implementations of CVPR/ICCV/NeurIPS segmentation papers
• you already use Detectron2 and want segmentation extensions with pretrained weights

When to avoid

• you need a production-ready segmentation service with an API
• you need a simple out-of-the-box segmentation tool without deep learning setup
• you require a permissive open-source license (license is non-standard)

Facets

library · maturity active

image-processing computer-vision machine-learning deep-learning computer-vision image-processing deep-learning machine-learning python image-segmentation panoptic-segmentation instance-segmentation semantic-segmentation detectron2 pytorch open-world-segmentation research-toolbox pretrained-models gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="qqlu/Entity")