EISeg: An Efficient Interactive Segmentation Tool based on PaddlePaddle

Understand

In recent years, the rapid development of deep learning has brought great advancements to image and video segmentation methods based on neural networks.

• However, to unleash the full potential of such models, large numbers of high-quality annotated images are necessary for model training.
• Currently, many widely used open-source image segmentation software relies heavily on manual annotation which is tedious and time-consuming.
• In this work, we introduce EISeg, an Efficient Interactive SEGmentation annotation tool that can drastically improve image segmentation annotation efficiency, generating highly accurate segmentation masks with only a few clicks.