SLiMe
SLiMe is an innovative image segmentation method that employs PyTorch and is recognized for its one-shot capabilities using Stable Diffusion. Designed for training, testing, and validation, it necessitates precise image and mask name matching and is compatible with well-known datasets like PASCAL-Part and CelebAMask-HQ. It offers easy integration with Colab Notebooks and a setup process that involves creating a virtual environment and installing dependencies. SLiMe supports customizable patch-based testing configurations, fostering novel segmentation applications and is backed by trained text embeddings along with comprehensive guides for optimizing performance on various image datasets.
