qqlu/Entity
An open-source toolbox for open-world and high-quality image segmentation using deep learning models.
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EntitySeg is a computer vision research toolbox focused on image segmentation tasks including instance, semantic, and panoptic segmentation. It provides implementations of multiple algorithms such as open-world entity segmentation, high-quality segmentation for ultra high-resolution images, and class-agnostic semi-supervised learning for detection and segmentation. Built on PyTorch and Detectron2, it includes pretrained models and weights for various segmentation benchmarks.
Frequently asked
- What is qqlu/Entity?
- An open-source toolbox for open-world and high-quality image segmentation using deep learning models.
- Is Entity open source?
- Yes — qqlu/Entity is an open-source project tracked on heatdrop.
- What language is Entity written in?
- qqlu/Entity is primarily written in Jupyter Notebook.
- How popular is Entity?
- qqlu/Entity has 1k stars on GitHub.
- Where can I find Entity?
- qqlu/Entity is on GitHub at https://github.com/qqlu/Entity.